WorldWideScience

Sample records for surface identification algorithms

  1. Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm.

    Science.gov (United States)

    Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

    2018-04-09

    To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

  2. Tau reconstruction and identification algorithm

    Indian Academy of Sciences (India)

    CMS has developed sophisticated tau identification algorithms for tau hadronic decay modes. Production of tau lepton decaying to hadrons are studied at 7 TeV centre-of-mass energy with 2011 collision data collected by CMS detector and has been used to measure the performance of tau identification algorithms by ...

  3. Improved autonomous star identification algorithm

    International Nuclear Information System (INIS)

    Luo Li-Yan; Xu Lu-Ping; Zhang Hua; Sun Jing-Rong

    2015-01-01

    The log–polar transform (LPT) is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm. (paper)

  4. Library correlation nuclide identification algorithm

    International Nuclear Information System (INIS)

    Russ, William R.

    2007-01-01

    A novel nuclide identification algorithm, Library Correlation Nuclide Identification (LibCorNID), is proposed. In addition to the spectrum, LibCorNID requires the standard energy, peak shape and peak efficiency calibrations. Input parameters include tolerances for some expected variations in the calibrations, a minimum relative nuclide peak area threshold, and a correlation threshold. Initially, the measured peak spectrum is obtained as the residual after baseline estimation via peak erosion, removing the continuum. Library nuclides are filtered by examining the possible nuclide peak areas in terms of the measured peak spectrum and applying the specified relative area threshold. Remaining candidates are used to create a set of theoretical peak spectra based on the calibrations and library entries. These candidate spectra are then simultaneously fit to the measured peak spectrum while also optimizing the calibrations within the bounds of the specified tolerances. Each candidate with optimized area still exceeding the area threshold undergoes a correlation test. The normalized Pearson's correlation value is calculated as a comparison of the optimized nuclide peak spectrum to the measured peak spectrum with the other optimized peak spectra subtracted. Those candidates with correlation values that exceed the specified threshold are identified and their optimized activities are output. An evaluation of LibCorNID was conducted to verify identification performance in terms of detection probability and false alarm rate. LibCorNID has been shown to perform well compared to standard peak-based analyses

  5. Star identification methods, techniques and algorithms

    CERN Document Server

    Zhang, Guangjun

    2017-01-01

    This book summarizes the research advances in star identification that the author’s team has made over the past 10 years, systematically introducing the principles of star identification, general methods, key techniques and practicable algorithms. It also offers examples of hardware implementation and performance evaluation for the star identification algorithms. Star identification is the key step for celestial navigation and greatly improves the performance of star sensors, and as such the book include the fundamentals of star sensors and celestial navigation, the processing of the star catalog and star images, star identification using modified triangle algorithms, star identification using star patterns and using neural networks, rapid star tracking using star matching between adjacent frames, as well as implementation hardware and using performance tests for star identification. It is not only valuable as a reference book for star sensor designers and researchers working in pattern recognition and othe...

  6. A new adaptive blind channel identification algorithm

    International Nuclear Information System (INIS)

    Peng Dezhong; Xiang Yong; Yi Zhang

    2009-01-01

    This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.

  7. A Source Identification Algorithm for INTEGRAL

    Science.gov (United States)

    Scaringi, Simone; Bird, Antony J.; Clark, David J.; Dean, Anthony J.; Hill, Adam B.; McBride, Vanessa A.; Shaw, Simon E.

    2008-12-01

    We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using Random Forests, is applied to the IBIS/ISGRI dataset in order to ease the production of unbiased future soft gamma-ray source catalogues. The key steps of candidate searching, filtering and feature extraction are described. Three training and testing sets are created in order to deal with the diverse timescales and diverse objects encountered when dealing with the gamma-ray sky. Three independent Random Forest are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the Transient Matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples.

  8. Algorithm improvement program nuclide identification algorithm scoring criteria and scoring application.

    Energy Technology Data Exchange (ETDEWEB)

    Enghauser, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-02-01

    The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

  9. ISINA: INTEGRAL Source Identification Network Algorithm

    Science.gov (United States)

    Scaringi, S.; Bird, A. J.; Clark, D. J.; Dean, A. J.; Hill, A. B.; McBride, V. A.; Shaw, S. E.

    2008-11-01

    We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. Based on observations with INTEGRAL, an ESA project with instruments and science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain), Czech Republic and Poland, and the participation of Russia and the USA. E-mail: simo@astro.soton.ac.uk

  10. Induction Motor Parameter Identification Using a Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    Omar Avalos

    2016-04-01

    Full Text Available The efficient use of electrical energy is a topic that has attracted attention for its environmental consequences. On the other hand, induction motors represent the main component in most industries. They consume the highest energy percentages in industrial facilities. This energy consumption depends on the operation conditions of the induction motor imposed by its internal parameters. Since the internal parameters of an induction motor are not directly measurable, an identification process must be conducted to obtain them. In the identification process, the parameter estimation is transformed into a multidimensional optimization problem where the internal parameters of the induction motor are considered as decision variables. Under this approach, the complexity of the optimization problem tends to produce multimodal error surfaces for which their cost functions are significantly difficult to minimize. Several algorithms based on evolutionary computation principles have been successfully applied to identify the optimal parameters of induction motors. However, most of them maintain an important limitation: They frequently obtain sub-optimal solutions as a result of an improper equilibrium between exploitation and exploration in their search strategies. This paper presents an algorithm for the optimal parameter identification of induction motors. To determine the parameters, the proposed method uses a recent evolutionary method called the gravitational search algorithm (GSA. Different from most of the existent evolutionary algorithms, the GSA presents a better performance in multimodal problems, avoiding critical flaws such as the premature convergence to sub-optimal solutions. Numerical simulations have been conducted on several models to show the effectiveness of the proposed scheme.

  11. Collective probabilities algorithm for surface hopping calculations

    International Nuclear Information System (INIS)

    Bastida, Adolfo; Cruz, Carlos; Zuniga, Jose; Requena, Alberto

    2003-01-01

    General equations that transition probabilities of the hopping algorithms in surface hopping calculations must obey to assure the equality between the average quantum and classical populations are derived. These equations are solved for two particular cases. In the first it is assumed that probabilities are the same for all trajectories and that the number of hops is kept to a minimum. These assumptions specify the collective probabilities (CP) algorithm, for which the transition probabilities depend on the average populations for all trajectories. In the second case, the probabilities for each trajectory are supposed to be completely independent of the results from the other trajectories. There is, then, a unique solution of the general equations assuring that the transition probabilities are equal to the quantum population of the target state, which is referred to as the independent probabilities (IP) algorithm. The fewest switches (FS) algorithm developed by Tully is accordingly understood as an approximate hopping algorithm which takes elements from the accurate CP and IP solutions. A numerical test of all these hopping algorithms is carried out for a one-dimensional two-state problem with two avoiding crossings which shows the accuracy and computational efficiency of the collective probabilities algorithm proposed, the limitations of the FS algorithm and the similarity between the results offered by the IP algorithm and those obtained with the Ehrenfest method

  12. System parameter identification information criteria and algorithms

    CERN Document Server

    Chen, Badong; Hu, Jinchun; Principe, Jose C

    2013-01-01

    Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors' research pr

  13. On flexible CAD of adaptive control and identification algorithms

    DEFF Research Database (Denmark)

    Christensen, Anders; Ravn, Ole

    1988-01-01

    a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define......SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...

  14. Time-Delay System Identification Using Genetic Algorithm

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Seested, Glen Thane

    2013-01-01

    Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique. The qual......Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique...

  15. A robust firearm identification algorithm of forensic ballistics specimens

    Science.gov (United States)

    Chuan, Z. L.; Jemain, A. A.; Liong, C.-Y.; Ghani, N. A. M.; Tan, L. K.

    2017-09-01

    There are several inherent difficulties in the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%.

  16. Parameter identification for structural dynamics based on interval analysis algorithm

    Science.gov (United States)

    Yang, Chen; Lu, Zixing; Yang, Zhenyu; Liang, Ke

    2018-04-01

    A parameter identification method using interval analysis algorithm for structural dynamics is presented in this paper. The proposed uncertain identification method is investigated by using central difference method and ARMA system. With the help of the fixed memory least square method and matrix inverse lemma, a set-membership identification technology is applied to obtain the best estimation of the identified parameters in a tight and accurate region. To overcome the lack of insufficient statistical description of the uncertain parameters, this paper treats uncertainties as non-probabilistic intervals. As long as we know the bounds of uncertainties, this algorithm can obtain not only the center estimations of parameters, but also the bounds of errors. To improve the efficiency of the proposed method, a time-saving algorithm is presented by recursive formula. At last, to verify the accuracy of the proposed method, two numerical examples are applied and evaluated by three identification criteria respectively.

  17. Genetic Algorithm-Based Identification of Fractional-Order Systems

    Directory of Open Access Journals (Sweden)

    Shengxi Zhou

    2013-05-01

    Full Text Available Fractional calculus has become an increasingly popular tool for modeling the complex behaviors of physical systems from diverse domains. One of the key issues to apply fractional calculus to engineering problems is to achieve the parameter identification of fractional-order systems. A time-domain identification algorithm based on a genetic algorithm (GA is proposed in this paper. The multi-variable parameter identification is converted into a parameter optimization by applying GA to the identification of fractional-order systems. To evaluate the identification accuracy and stability, the time-domain output error considering the condition variation is designed as the fitness function for parameter optimization. The identification process is established under various noise levels and excitation levels. The effects of external excitation and the noise level on the identification accuracy are analyzed in detail. The simulation results show that the proposed method could identify the parameters of both commensurate rate and non-commensurate rate fractional-order systems from the data with noise. It is also observed that excitation signal is an important factor influencing the identification accuracy of fractional-order systems.

  18. Merged Search Algorithms for Radio Frequency Identification Anticollision

    Directory of Open Access Journals (Sweden)

    Bih-Yaw Shih

    2012-01-01

    The arbitration algorithm for RFID system is used to arbitrate all the tags to avoid the collision problem with the existence of multiple tags in the interrogation field of a transponder. A splitting algorithm which is called Binary Search Tree (BST is well known for multitags arbitration. In the current study, a splitting-based schema called Merged Search Tree is proposed to capture identification codes correctly for anticollision. Performance of the proposed algorithm is compared with the original BST according to time and power consumed during the arbitration process. The results show that the proposed model can reduce searching time and power consumed to achieve a better performance arbitration.

  19. Cover song identification by sequence alignment algorithms

    Science.gov (United States)

    Wang, Chih-Li; Zhong, Qian; Wang, Szu-Ying; Roychowdhury, Vwani

    2011-10-01

    Content-based music analysis has drawn much attention due to the rapidly growing digital music market. This paper describes a method that can be used to effectively identify cover songs. A cover song is a song that preserves only the crucial melody of its reference song but different in some other acoustic properties. Hence, the beat/chroma-synchronous chromagram, which is insensitive to the variation of the timber or rhythm of songs but sensitive to the melody, is chosen. The key transposition is achieved by cyclically shifting the chromatic domain of the chromagram. By using the Hidden Markov Model (HMM) to obtain the time sequences of songs, the system is made even more robust. Similar structure or length between the cover songs and its reference are not necessary by the Smith-Waterman Alignment Algorithm.

  20. Channel Access Algorithm Design for Automatic Identification System

    Institute of Scientific and Technical Information of China (English)

    Oh Sang-heon; Kim Seung-pum; Hwang Dong-hwan; Park Chan-sik; Lee Sang-jeong

    2003-01-01

    The Automatic Identification System (AIS) is a maritime equipment to allow an efficient exchange of the navigational data between ships and between ships and shore stations. It utilizes a channel access algorithm which can quickly resolve conflicts without any intervention from control stations. In this paper, a design of channel access algorithm for the AIS is presented. The input/output relationship of each access algorithm module is defined by drawing the state transition diagram, dataflow diagram and flowchart based on the technical standard, ITU-R M.1371. In order to verify the designed channel access algorithm, the simulator was developed using the C/C++ programming language. The results show that the proposed channel access algorithm can properly allocate transmission slots and meet the operational performance requirements specified by the technical standard.

  1. Time-Delay System Identification Using Genetic Algorithm

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Seested, Glen Thane

    2013-01-01

    problem through an identification approach using the real coded Genetic Algorithm (GA). The desired FOPDT/SOPDT model is directly identified based on the measured system's input and output data. In order to evaluate the quality and performance of this GA-based approach, the proposed method is compared...

  2. Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

    Directory of Open Access Journals (Sweden)

    Zongze Wu

    2015-08-01

    Full Text Available Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE criterion, which is optimal only when the measurement noise is Gaussian. However, this condition does not hold in most real-world environments. In this work, we use the minimum error entropy (MEE criterion, an alternative to the conventional MSE criterion, to develop the proportionate minimum error entropy (PMEE algorithm for sparse system identification, which may achieve much better performance than the MSE based methods especially in heavy-tailed non-Gaussian situations. Moreover, we analyze the convergence of the proposed algorithm and derive a sufficient condition that ensures the mean square convergence. Simulation results confirm the excellent performance of the new algorithm.

  3. Applications of surface metrology in firearm identification

    International Nuclear Information System (INIS)

    Zheng, X; Soons, J; Vorburger, T V; Song, J; Renegar, T; Thompson, R

    2014-01-01

    Surface metrology is commonly used to characterize functional engineering surfaces. The technologies developed offer opportunities to improve forensic toolmark identification. Toolmarks are created when a hard surface, the tool, comes into contact with a softer surface and causes plastic deformation. Toolmarks are commonly found on fired bullets and cartridge cases. Trained firearms examiners use these toolmarks to link an evidence bullet or cartridge case to a specific firearm, which can lead to a criminal conviction. Currently, identification is typically based on qualitative visual comparison by a trained examiner using a comparison microscope. In 2009, a report by the National Academies called this method into question. Amongst other issues, they questioned the objectivity of visual toolmark identification by firearms examiners. The National Academies recommended the development of objective toolmark identification criteria and confidence limits. The National Institute of Standards and Technology (NIST) have applied its experience in surface metrology to develop objective identification criteria, measurement methods, and reference artefacts for toolmark identification. NIST developed the Standard Reference Material SRM 2460 standard bullet and SRM 2461 standard cartridge case to facilitate quality control and traceability of identifications performed in crime laboratories. Objectivity is improved through measurement of surface topography and application of unambiguous surface similarity metrics, such as the maximum value (ACCF MAX ) of the areal cross correlation function. Case studies were performed on consecutively manufactured tools, such as gun barrels and breech faces, to demonstrate that, even in this worst case scenario, all the tested tools imparted unique surface topographies that were identifiable. These studies provide scientific support for toolmark evidence admissibility in criminal court cases. (paper)

  4. A new algorithmic approach for fingers detection and identification

    Science.gov (United States)

    Mubashar Khan, Arslan; Umar, Waqas; Choudhary, Taimoor; Hussain, Fawad; Haroon Yousaf, Muhammad

    2013-03-01

    Gesture recognition is concerned with the goal of interpreting human gestures through mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Hand gesture detection in a real time environment, where the time and memory are important issues, is a critical operation. Hand gesture recognition largely depends on the accurate detection of the fingers. This paper presents a new algorithmic approach to detect and identify fingers of human hand. The proposed algorithm does not depend upon the prior knowledge of the scene. It detects the active fingers and Metacarpophalangeal (MCP) of the inactive fingers from an already detected hand. Dynamic thresholding technique and connected component labeling scheme are employed for background elimination and hand detection respectively. Algorithm proposed a new approach for finger identification in real time environment keeping the memory and time constraint as low as possible.

  5. Automatic identification of otological drilling faults: an intelligent recognition algorithm.

    Science.gov (United States)

    Cao, Tianyang; Li, Xisheng; Gao, Zhiqiang; Feng, Guodong; Shen, Peng

    2010-06-01

    This article presents an intelligent recognition algorithm that can recognize milling states of the otological drill by fusing multi-sensor information. An otological drill was modified by the addition of sensors. The algorithm was designed according to features of the milling process and is composed of a characteristic curve, an adaptive filter and a rule base. The characteristic curve can weaken the impact of the unstable normal milling process and reserve the features of drilling faults. The adaptive filter is capable of suppressing interference in the characteristic curve by fusing multi-sensor information. The rule base can identify drilling faults through the filtering result data. The experiments were repeated on fresh porcine scapulas, including normal milling and two drilling faults. The algorithm has high rates of identification. This study shows that the intelligent recognition algorithm can identify drilling faults under interference conditions. (c) 2010 John Wiley & Sons, Ltd.

  6. Biofilms and Wounds: An Identification Algorithm and Potential Treatment Options

    Science.gov (United States)

    Percival, Steven L.; Vuotto, Claudia; Donelli, Gianfranco; Lipsky, Benjamin A.

    2015-01-01

    Significance: The presence of a “pathogenic” or “highly virulent” biofilm is a fundamental risk factor that prevents a chronic wound from healing and increases the risk of the wound becoming clinically infected. There is presently no unequivocal gold standard method available for clinicians to confirm the presence of biofilms in a wound. Thus, to help support clinician practice, we devised an algorithm intended to demonstrate evidence of the presence of a biofilm in a wound to assist with wound management. Recent Advances: A variety of histological and microscopic methods applied to tissue biopsies are currently the most informative techniques available for demonstrating the presence of generic (not classified as pathogenic or commensal) biofilms and the effect they are having in promoting inflammation and downregulating cellular functions. Critical Issues: Even as we rely on microscopic techniques to visualize biofilms, they are entities which are patchy and dispersed rather than confluent, particularly on biotic surfaces. Consequently, detection of biofilms by microscopic techniques alone can lead to frequent false-negative results. Furthermore, visual identification using the naked eye of a pathogenic biofilm on a macroscopic level on the wound will not be possible, unlike with biofilms on abiotic surfaces. Future Direction: Lacking specific biomarkers to demonstrate microscopic, nonconfluent, virulent biofilms in wounds, the present focus on biofilm research should be placed on changing clinical practice. This is best done by utilizing an anti-biofilm toolbox approach, rather than speculating on unscientific approaches to identifying biofilms, with or without staining, in wounds with the naked eye. The approach to controlling biofilm should include initial wound cleansing, periodic debridement, followed by the application of appropriate antimicrobial wound dressings. This approach appears to be effective in removing pathogenic biofilms. PMID:26155381

  7. A robust star identification algorithm with star shortlisting

    Science.gov (United States)

    Mehta, Deval Samirbhai; Chen, Shoushun; Low, Kay Soon

    2018-05-01

    A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in "Lost-In-Space (LIS)" mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications.

  8. Algorithm of Dynamic Model Structural Identification of the Multivariable Plant

    Directory of Open Access Journals (Sweden)

    Л.М. Блохін

    2004-02-01

    Full Text Available  The new algorithm of dynamic model structural identification of the multivariable stabilized plant with observable and unobservable disturbances in the regular operating  modes is offered in this paper. With the help of the offered algorithm it is possible to define the “perturbed” models of dynamics not only of the plant, but also the dynamics characteristics of observable and unobservable casual disturbances taking into account the absence of correlation between themselves and control inputs with the unobservable perturbations.

  9. Particle identification algorithms for the PANDA Endcap Disc DIRC

    Science.gov (United States)

    Schmidt, M.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwarz, C.; Schwiening, J.; Traxler, M.; Böhm, M.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Merle, O.; Rieke, J.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.

    2017-12-01

    The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5o to 22o. This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

  10. Development of an automatic identification algorithm for antibiogram analysis

    OpenAIRE

    Costa, LFR; Eduardo Silva; Noronha, VT; Ivone Vaz-Moreira; Olga C Nunes; de Andrade, MM

    2015-01-01

    Routinely, diagnostic and microbiology laboratories perform antibiogram analysis which can present some difficulties leading to misreadings and intra and inter-reader deviations. An Automatic Identification Algorithm (AIA) has been proposed as a solution to overcome some issues associated with the disc diffusion method, which is the main goal of this work. ALA allows automatic scanning of inhibition zones obtained by antibiograms. More than 60 environmental isolates were tested using suscepti...

  11. Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System

    Directory of Open Access Journals (Sweden)

    Jingbo Zhang

    2017-11-01

    Full Text Available Collaborative spectral sensing can fuse the perceived results of multiple cognitive users, and thus will improve the accuracy of perceived results. However, the multi-source features of the perceived results result in security problems in the system. When there is a high probability of a malicious user attack, the traditional algorithm can correctly identify the malicious users. However, when the probability of attack by malicious users is reduced, it is almost impossible to use the traditional algorithm to correctly distinguish between honest users and malicious users, which greatly reduces the perceived performance. To address the problem above, based on the β function and the feedback iteration mathematical method, this paper proposes a malicious user identification algorithm under multi-channel cooperative conditions (β-MIAMC, which involves comprehensively assessing the cognitive user’s performance on multiple sub-channels to identify the malicious user. Simulation results show under the same attack probability, compared with the traditional algorithm, the β-MIAMC algorithm can more accurately identify the malicious users, reducing the false alarm probability of malicious users by more than 20%. When the attack probability is greater than 7%, the proposed algorithm can identify the malicious users with 100% certainty.

  12. LHCb - Novel Muon Identification Algorithms for the LHCb Upgrade

    CERN Multimedia

    Cogoni, Violetta

    2016-01-01

    The present LHCb Muon Identification procedure was optimised to guarantee high muon detection efficiency at the istantaneous luminosity $\\mathcal{L}$ of $2\\cdot10^{32}$~cm$^{-2}$~s$^{-1}$. In the current data taking conditions, the luminosity is higher than foreseen and the low energy background contribution to the visible rate in the muon system is larger than expected. A worse situation is expected for Run III when LHCb will operate at $\\mathcal{L} = 2\\cdot10^{33}$~cm$^{-2}$~s$^{-1}$ causing the high particle fluxes to deteriorate the muon detection efficiency, because of the increased dead time of the electronics, and in particular to worsen the muon identification capabilities, due to the increased contribution of the background, with deleterious consequences especially for the analyses requiring high purity signal. In this context, possible new algorithms for the muon identification will be illustrated. In particular, the performance on combinatorial background rejection will be shown, together with the ...

  13. Comparing Different Fault Identification Algorithms in Distributed Power System

    Science.gov (United States)

    Alkaabi, Salim

    A power system is a huge complex system that delivers the electrical power from the generation units to the consumers. As the demand for electrical power increases, distributed power generation was introduced to the power system. Faults may occur in the power system at any time in different locations. These faults cause a huge damage to the system as they might lead to full failure of the power system. Using distributed generation in the power system made it even harder to identify the location of the faults in the system. The main objective of this work is to test the different fault location identification algorithms while tested on a power system with the different amount of power injected using distributed generators. As faults may lead the system to full failure, this is an important area for research. In this thesis different fault location identification algorithms have been tested and compared while the different amount of power is injected from distributed generators. The algorithms were tested on IEEE 34 node test feeder using MATLAB and the results were compared to find when these algorithms might fail and the reliability of these methods.

  14. A simple algorithm for the identification of clinical COPD phenotypes

    DEFF Research Database (Denmark)

    Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim

    2017-01-01

    This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses. Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification...... of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative...... International Assessment (3CIA) initiative. Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated...

  15. Energy Efficient Distributed Fault Identification Algorithm in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Meenakshi Panda

    2014-01-01

    Full Text Available A distributed fault identification algorithm is proposed here to find both hard and soft faulty sensor nodes present in wireless sensor networks. The algorithm is distributed, self-detectable, and can detect the most common byzantine faults such as stuck at zero, stuck at one, and random data. In the proposed approach, each sensor node gathered the observed data from the neighbors and computed the mean to check whether faulty sensor node is present or not. If a node found the presence of faulty sensor node, then compares observed data with the data of the neighbors and predict probable fault status. The final fault status is determined by diffusing the fault information from the neighbors. The accuracy and completeness of the algorithm are verified with the help of statistical model of the sensors data. The performance is evaluated in terms of detection accuracy, false alarm rate, detection latency and message complexity.

  16. An intelligent identification algorithm for the monoclonal picking instrument

    Science.gov (United States)

    Yan, Hua; Zhang, Rongfu; Yuan, Xujun; Wang, Qun

    2017-11-01

    The traditional colony selection is mainly operated by manual mode, which takes on low efficiency and strong subjectivity. Therefore, it is important to develop an automatic monoclonal-picking instrument. The critical stage of the automatic monoclonal-picking and intelligent optimal selection is intelligent identification algorithm. An auto-screening algorithm based on Support Vector Machine (SVM) is proposed in this paper, which uses the supervised learning method, which combined with the colony morphological characteristics to classify the colony accurately. Furthermore, through the basic morphological features of the colony, system can figure out a series of morphological parameters step by step. Through the establishment of maximal margin classifier, and based on the analysis of the growth trend of the colony, the selection of the monoclonal colony was carried out. The experimental results showed that the auto-screening algorithm could screen out the regular colony from the other, which meets the requirement of various parameters.

  17. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are op...

  18. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    Wade T. Tinkham; Hongyu Huang; Alistair M.S. Smith; Rupesh Shrestha; Michael J. Falkowski; Andrew T. Hudak; Timothy E. Link; Nancy F. Glenn; Danny G. Marks

    2011-01-01

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results....

  19. Improved algorithm for surface display from volumetric data

    International Nuclear Information System (INIS)

    Lobregt, S.; Schaars, H.W.G.K.; OpdeBeek, J.C.A.; Zonneveld, F.W.

    1988-01-01

    A high-resolution surface display is produced from three-dimensional datasets (computed tomography or magnetic resonance imaging). Unlike other voxel-based methods, this algorithm does not show a cuberille surface structure, because the surface orientation is calculated from original gray values. The applied surface shading is a function of local orientation and position of the surface and of a virtual light source, giving a realistic impression of the surface of bone and soft tissue. The projection and shading are table driven, combining variable viewpoint and illumination conditions with speed. Other options are cutplane gray-level display and surface transparency. Combined with volume scanning, this algorithm offers powerful application possibilities

  20. WATERSHED ALGORITHM BASED SEGMENTATION FOR HANDWRITTEN TEXT IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    P. Mathivanan

    2014-02-01

    Full Text Available In this paper we develop a system for writer identification which involves four processing steps like preprocessing, segmentation, feature extraction and writer identification using neural network. In the preprocessing phase the handwritten text is subjected to slant removal process for segmentation and feature extraction. After this step the text image enters into the process of noise removal and gray level conversion. The preprocessed image is further segmented by using morphological watershed algorithm, where the text lines are segmented into single words and then into single letters. The segmented image is feature extracted by Daubechies’5/3 integer wavelet transform to reduce training complexity [1, 6]. This process is lossless and reversible [10], [14]. These extracted features are given as input to our neural network for writer identification process and a target image is selected for each training process in the 2-layer neural network. With the several trained output data obtained from different target help in text identification. It is a multilingual text analysis which provides simple and efficient text segmentation.

  1. Application of image recognition algorithms for statistical description of nano- and microstructured surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Mărăscu, V.; Dinescu, G. [National Institute for Lasers, Plasma and Radiation Physics, 409 Atomistilor Street, Bucharest– Magurele (Romania); Faculty of Physics, University of Bucharest, 405 Atomistilor Street, Bucharest-Magurele (Romania); Chiţescu, I. [Faculty of Mathematics and Computer Science, University of Bucharest, 14 Academiei Street, Bucharest (Romania); Barna, V. [Faculty of Physics, University of Bucharest, 405 Atomistilor Street, Bucharest-Magurele (Romania); Ioniţă, M. D.; Lazea-Stoyanova, A.; Mitu, B., E-mail: mitub@infim.ro [National Institute for Lasers, Plasma and Radiation Physics, 409 Atomistilor Street, Bucharest– Magurele (Romania)

    2016-03-25

    In this paper we propose a statistical approach for describing the self-assembling of sub-micronic polystyrene beads on silicon surfaces, as well as the evolution of surface topography due to plasma treatments. Algorithms for image recognition are used in conjunction with Scanning Electron Microscopy (SEM) imaging of surfaces. In a first step, greyscale images of the surface covered by the polystyrene beads are obtained. Further, an adaptive thresholding method was applied for obtaining binary images. The next step consisted in automatic identification of polystyrene beads dimensions, by using Hough transform algorithm, according to beads radius. In order to analyze the uniformity of the self–assembled polystyrene beads, the squared modulus of 2-dimensional Fast Fourier Transform (2- D FFT) was applied. By combining these algorithms we obtain a powerful and fast statistical tool for analysis of micro and nanomaterials with aspect features regularly distributed on surface upon SEM examination.

  2. Application of image recognition algorithms for statistical description of nano- and microstructured surfaces

    International Nuclear Information System (INIS)

    Mărăscu, V.; Dinescu, G.; Chiţescu, I.; Barna, V.; Ioniţă, M. D.; Lazea-Stoyanova, A.; Mitu, B.

    2016-01-01

    In this paper we propose a statistical approach for describing the self-assembling of sub-micronic polystyrene beads on silicon surfaces, as well as the evolution of surface topography due to plasma treatments. Algorithms for image recognition are used in conjunction with Scanning Electron Microscopy (SEM) imaging of surfaces. In a first step, greyscale images of the surface covered by the polystyrene beads are obtained. Further, an adaptive thresholding method was applied for obtaining binary images. The next step consisted in automatic identification of polystyrene beads dimensions, by using Hough transform algorithm, according to beads radius. In order to analyze the uniformity of the self–assembled polystyrene beads, the squared modulus of 2-dimensional Fast Fourier Transform (2- D FFT) was applied. By combining these algorithms we obtain a powerful and fast statistical tool for analysis of micro and nanomaterials with aspect features regularly distributed on surface upon SEM examination.

  3. Improved chemical identification from sensor arrays using intelligent algorithms

    Science.gov (United States)

    Roppel, Thaddeus A.; Wilson, Denise M.

    2001-02-01

    Intelligent signal processing algorithms are shown to improve identification rates significantly in chemical sensor arrays. This paper focuses on the use of independently derived sensor status information to modify the processing of sensor array data by using a fast, easily-implemented "best-match" approach to filling in missing sensor data. Most fault conditions of interest (e.g., stuck high, stuck low, sudden jumps, excess noise, etc.) can be detected relatively simply by adjunct data processing, or by on-board circuitry. The objective then is to devise, implement, and test methods for using this information to improve the identification rates in the presence of faulted sensors. In one typical example studied, utilizing separately derived, a-priori knowledge about the health of the sensors in the array improved the chemical identification rate by an artificial neural network from below 10 percent correct to over 99 percent correct. While this study focuses experimentally on chemical sensor arrays, the results are readily extensible to other types of sensor platforms.

  4. Mode Identification of Guided Ultrasonic Wave using Time- Frequency Algorithm

    International Nuclear Information System (INIS)

    Yoon, Byung Sik; Yang, Seung Han; Cho, Yong Sang; Kim, Yong Sik; Lee, Hee Jong

    2007-01-01

    The ultrasonic guided waves are waves whose propagation characteristics depend on structural thickness and shape such as those in plates, tubes, rods, and embedded layers. If the angle of incidence or the frequency of sound is adjusted properly, the reflected and refracted energy within the structure will constructively interfere, thereby launching the guided wave. Because these waves penetrate the entire thickness of the tube and propagate parallel to the surface, a large portion of the material can be examined from a single transducer location. The guided ultrasonic wave has various merits like above. But various kind of modes are propagating through the entire thickness, so we don't know the which mode is received. Most of applications are limited from mode selection and mode identification. So the mode identification is very important process for guided ultrasonic inspection application. In this study, various time-frequency analysis methodologies are developed and compared for mode identification tool of guided ultrasonic signal. For this study, a high power tone-burst ultrasonic system set up for the generation and receive of guided waves. And artificial notches were fabricated on the Aluminum plate for the experiment on the mode identification

  5. Applying Intelligent Algorithms to Automate the Identification of Error Factors.

    Science.gov (United States)

    Jin, Haizhe; Qu, Qingxing; Munechika, Masahiko; Sano, Masataka; Kajihara, Chisato; Duffy, Vincent G; Chen, Han

    2018-05-03

    Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a difficult and time-consuming task and requires an analyst with a professional medical background. The issues of identifying a method to extract medical error factors and reduce the extraction difficulty need to be resolved. In this research, a systematic methodology to extract and identify error factors in the medical administration process was proposed. The design of the error report, extraction of the error factors, and identification of the error factors were analyzed. Based on 624 medical error cases across four medical institutes in both Japan and China, 19 error-related items and their levels were extracted. After which, they were closely related to 12 error factors. The relational model between the error-related items and error factors was established based on a genetic algorithm (GA)-back-propagation neural network (BPNN) model. Additionally, compared to GA-BPNN, BPNN, partial least squares regression and support vector regression, GA-BPNN exhibited a higher overall prediction accuracy, being able to promptly identify the error factors from the error-related items. The combination of "error-related items, their different levels, and the GA-BPNN model" was proposed as an error-factor identification technology, which could automatically identify medical error factors.

  6. Identification tibia and fibula bone fracture location using scanline algorithm

    Science.gov (United States)

    Muchtar, M. A.; Simanjuntak, S. E.; Rahmat, R. F.; Mawengkang, H.; Zarlis, M.; Sitompul, O. S.; Winanto, I. D.; Andayani, U.; Syahputra, M. F.; Siregar, I.; Nasution, T. H.

    2018-03-01

    Fracture is a condition that there is a damage in the continuity of the bone, usually caused by stress, trauma or weak bones. The tibia and fibula are two separated-long bones in the lower leg, closely linked at the knee and ankle. Tibia/fibula fracture often happen when there is too much force applied to the bone that it can withstand. One of the way to identify the location of tibia/fibula fracture is to read X-ray image manually. Visual examination requires more time and allows for errors in identification due to the noise in image. In addition, reading X-ray needs highlighting background to make the objects in X-ray image appear more clearly. Therefore, a method is required to help radiologist to identify the location of tibia/fibula fracture. We propose some image-processing techniques for processing cruris image and Scan line algorithm for the identification of fracture location. The result shows that our proposed method is able to identify it and reach up to 87.5% of accuracy.

  7. TADtool: visual parameter identification for TAD-calling algorithms.

    Science.gov (United States)

    Kruse, Kai; Hug, Clemens B; Hernández-Rodríguez, Benjamín; Vaquerizas, Juan M

    2016-10-15

    Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD-calling parameters with immediate visual feedback. TADtool allows the direct export of TADs called with a chosen set of parameters for two of the most common TAD calling algorithms: directionality and insulation index. It can be used as an intuitive, standalone application or as a Python package for maximum flexibility. TADtool is available as a Python package from GitHub (https://github.com/vaquerizaslab/tadtool) or can be installed directly via PyPI, the Python package index (tadtool). kai.kruse@mpi-muenster.mpg.de, jmv@mpi-muenster.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  8. Algorithms and tools for system identification using prior knowledge

    International Nuclear Information System (INIS)

    Lindskog, P.

    1994-01-01

    One of the hardest problems in system identification is that of model structure selection. In this thesis two different kinds of a priori process knowledge are used to address this fundamental problem. Concentrating on linear model structures, the first prior advantage of is knowledge about the systems' dominating time constants and resonance frequencies. The idea is to generalize FIR modelling by replacing the usual delay operator with discrete so-called Laguerre or Kautz filters. The generalization is such that stability, the linear regression structure and the approximation ability of the FIR model structure is retained, whereas the prior is used to reduce the number of parameters needed to arrive at a reasonable model. Tailorized and efficient system identification algorithms for these model structures are detailed in this work. The usefulness of the proposed methods is demonstrated through concrete simulation and application studies. The other approach is referred to as semi-physical modelling. The main idea is to use simple physical insight into the application, often in terms of a set of unstructured equations, in order to come up with suitable nonlinear transformation of the raw measurements, so as to allow for a good model structure. Semi-physical modelling is less ''ambitious'' than physical modelling in that no complete physical structure is sought, just combinations of inputs and outputs that can be subjected to more or less standard model structures, such as linear regressions. The suggested modelling procedure shows a first step where symbolic computations are employed to determine a suitable model structure - a set of regressors. We show how constructive methods from commutative and differential algebra can be applied for this. Subsequently, different numerical schemes for finding a subset of ''good'' regressors and for estimating the corresponding linear-in-the-parameters model are discussed. 107 refs, figs, tabs

  9. An Algorithm for Investigating the Structure of Material Surfaces

    Directory of Open Access Journals (Sweden)

    M. Toman

    2003-01-01

    Full Text Available The aim of this paper is to summarize the algorithm and the experience that have been achieved in the investigation of grain structure of surfaces of certain materials, particularly from samples of gold. The main parts of the algorithm to be discussed are:1. acquisition of input data,2. localization of grain region,3. representation of grain size,4. representation of outputs (postprocessing.

  10. Fast algorithm for the rendering of three-dimensional surfaces

    Science.gov (United States)

    Pritt, Mark D.

    1994-02-01

    It is often desirable to draw a detailed and realistic representation of surface data on a computer graphics display. One such representation is a 3D shaded surface. Conventional techniques for rendering shaded surfaces are slow, however, and require substantial computational power. Furthermore, many techniques suffer from aliasing effects, which appear as jagged lines and edges. This paper describes an algorithm for the fast rendering of shaded surfaces without aliasing effects. It is much faster than conventional ray tracing and polygon-based rendering techniques and is suitable for interactive use. On an IBM RISC System/6000TM workstation it renders a 1000 X 1000 surface in about 7 seconds.

  11. A voting-based star identification algorithm utilizing local and global distribution

    Science.gov (United States)

    Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

    2018-03-01

    A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

  12. A Low Delay and Fast Converging Improved Proportionate Algorithm for Sparse System Identification

    Directory of Open Access Journals (Sweden)

    Benesty Jacob

    2007-01-01

    Full Text Available A sparse system identification algorithm for network echo cancellation is presented. This new approach exploits both the fast convergence of the improved proportionate normalized least mean square (IPNLMS algorithm and the efficient implementation of the multidelay adaptive filtering (MDF algorithm inheriting the beneficial properties of both. The proposed IPMDF algorithm is evaluated using impulse responses with various degrees of sparseness. Simulation results are also presented for both speech and white Gaussian noise input sequences. It has been shown that the IPMDF algorithm outperforms the MDF and IPNLMS algorithms for both sparse and dispersive echo path impulse responses. Computational complexity of the proposed algorithm is also discussed.

  13. Firefly Algorithm for Polynomial Bézier Surface Parameterization

    Directory of Open Access Journals (Sweden)

    Akemi Gálvez

    2013-01-01

    reality, medical imaging, computer graphics, computer animation, and many others. Very often, the preferred approximating surface is polynomial, usually described in parametric form. This leads to the problem of determining suitable parametric values for the data points, the so-called surface parameterization. In real-world settings, data points are generally irregularly sampled and subjected to measurement noise, leading to a very difficult nonlinear continuous optimization problem, unsolvable with standard optimization techniques. This paper solves the parameterization problem for polynomial Bézier surfaces by applying the firefly algorithm, a powerful nature-inspired metaheuristic algorithm introduced recently to address difficult optimization problems. The method has been successfully applied to some illustrative examples of open and closed surfaces, including shapes with singularities. Our results show that the method performs very well, being able to yield the best approximating surface with a high degree of accuracy.

  14. Research on Palmprint Identification Method Based on Quantum Algorithms

    Directory of Open Access Journals (Sweden)

    Hui Li

    2014-01-01

    Full Text Available Quantum image recognition is a technology by using quantum algorithm to process the image information. It can obtain better effect than classical algorithm. In this paper, four different quantum algorithms are used in the three stages of palmprint recognition. First, quantum adaptive median filtering algorithm is presented in palmprint filtering processing. Quantum filtering algorithm can get a better filtering result than classical algorithm through the comparison. Next, quantum Fourier transform (QFT is used to extract pattern features by only one operation due to quantum parallelism. The proposed algorithm exhibits an exponential speed-up compared with discrete Fourier transform in the feature extraction. Finally, quantum set operations and Grover algorithm are used in palmprint matching. According to the experimental results, quantum algorithm only needs to apply square of N operations to find out the target palmprint, but the traditional method needs N times of calculation. At the same time, the matching accuracy of quantum algorithm is almost 100%.

  15. Global structural optimizations of surface systems with a genetic algorithm

    International Nuclear Information System (INIS)

    Chuang, Feng-Chuan

    2005-01-01

    Global structural optimizations with a genetic algorithm were performed for atomic cluster and surface systems including aluminum atomic clusters, Si magic clusters on the Si(111) 7 x 7 surface, silicon high-index surfaces, and Ag-induced Si(111) reconstructions. First, the global structural optimizations of neutral aluminum clusters Al n (n up to 23) were performed using a genetic algorithm coupled with a tight-binding potential. Second, a genetic algorithm in combination with tight-binding and first-principles calculations were performed to study the structures of magic clusters on the Si(111) 7 x 7 surface. Extensive calculations show that the magic cluster observed in scanning tunneling microscopy (STM) experiments consist of eight Si atoms. Simulated STM images of the Si magic cluster exhibit a ring-like feature similar to STM experiments. Third, a genetic algorithm coupled with a highly optimized empirical potential were used to determine the lowest energy structure of high-index semiconductor surfaces. The lowest energy structures of Si(105) and Si(114) were determined successfully. The results of Si(105) and Si(114) are reported within the framework of highly optimized empirical potential and first-principles calculations. Finally, a genetic algorithm coupled with Si and Ag tight-binding potentials were used to search for Ag-induced Si(111) reconstructions at various Ag and Si coverages. The optimized structural models of √3 x √3, 3 x 1, and 5 x 2 phases were reported using first-principles calculations. A novel model is found to have lower surface energy than the proposed double-honeycomb chained (DHC) model both for Au/Si(111) 5 x 2 and Ag/Si(111) 5 x 2 systems

  16. Radioactivity nuclide identification based on BP and LM algorithm neural network

    International Nuclear Information System (INIS)

    Wang Jihong; Sun Jian; Wang Lianghou

    2012-01-01

    The paper provides the method which can identify radioactive nuclide based on the BP and LM algorithm neural network. Then, this paper compares the above-mentioned method with FR algorithm. Through the result of the Matlab simulation, the method of radioactivity nuclide identification based on the BP and LM algorithm neural network is superior to the FR algorithm. With the better effect and the higher accuracy, it will be the best choice. (authors)

  17. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-07-07

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

  18. An Algorithm for Managing Aircraft Movement on an Airport Surface

    Directory of Open Access Journals (Sweden)

    Giuseppe Maresca

    2013-08-01

    Full Text Available The present paper focuses on the development of an algorithm for safely and optimally managing the routing of aircraft on an airport surface in future airport operations. This tool is intended to support air traffic controllers’ decision-making in selecting the paths of all aircraft and the engine startup approval time for departing ones. Optimal routes are sought for minimizing the time both arriving and departing aircraft spend on an airport surface with engines on, with benefits in terms of safety, efficiency and costs. The proposed algorithm first computes a standalone, shortest path solution from runway to apron or vice versa, depending on the aircraft being inbound or outbound, respectively. For taking into account the constraints due to other traffic on an airport surface, this solution is amended by a conflict detection and resolution task that attempts to reduce and possibly nullify the number of conflicts generated in the first phase. An example application on a simple Italian airport exemplifies how the algorithm can be applied to true-world applications. Emphasis is given on how to model an airport surface as a weighted and directed graph with non-negative weights, as required for the input to the algorithm.

  19. A Novel Algorithm of Surface Eliminating in Undersurface Optoacoustic Imaging

    Directory of Open Access Journals (Sweden)

    Zhulina Yulia V

    2004-01-01

    Full Text Available This paper analyzes the task of optoacoustic imaging of the objects located under the surface covering them. In this paper, we suggest the algorithm of the surface eliminating based on the fact that the intensity of the image as a function of the spatial point should change slowly inside the local objects, and will suffer a discontinuity of the spatial gradients on their boundaries. The algorithm forms the 2-dimensional curves along which the discontinuity of the signal derivatives is detected. Then, the algorithm divides the signal space into the areas along these curves. The signals inside the areas with the maximum level of the signal amplitudes and the maximal gradient absolute values on their edges are put equal to zero. The rest of the signals are used for the image restoration. This method permits to reconstruct the picture of the surface boundaries with a higher contrast than that of the surface detection technique based on the maximums of the received signals. This algorithm does not require any prior knowledge of the signals' statistics inside and outside the local objects. It may be used for reconstructing any images with the help of the signals representing the integral over the object's volume. Simulation and real data are also provided to validate the proposed method.

  20. Identification of Fuzzy Inference Systems by Means of a Multiobjective Opposition-Based Space Search Algorithm

    Directory of Open Access Journals (Sweden)

    Wei Huang

    2013-01-01

    Full Text Available We introduce a new category of fuzzy inference systems with the aid of a multiobjective opposition-based space search algorithm (MOSSA. The proposed MOSSA is essentially a multiobjective space search algorithm improved by using an opposition-based learning that employs a so-called opposite numbers mechanism to speed up the convergence of the optimization algorithm. In the identification of fuzzy inference system, the MOSSA is exploited to carry out the parametric identification of the fuzzy model as well as to realize its structural identification. Experimental results demonstrate the effectiveness of the proposed fuzzy models.

  1. Linear-time general decoding algorithm for the surface code

    Science.gov (United States)

    Darmawan, Andrew S.; Poulin, David

    2018-05-01

    A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.

  2. Bouc–Wen hysteresis model identification using Modified Firefly Algorithm

    International Nuclear Information System (INIS)

    Zaman, Mohammad Asif; Sikder, Urmita

    2015-01-01

    The parameters of Bouc–Wen hysteresis model are identified using a Modified Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to improve its performance. The algorithm is used to find the model parameter values that results in the least amount of error between a set of given data points and points obtained from the Bouc–Wen model. The performance of the algorithm is compared with the performance of conventional Firefly Algorithm, Genetic Algorithm and Differential Evolution algorithm in terms of convergence rate and accuracy. Compared to the other three optimization algorithms, the proposed algorithm is found to have good convergence rate with high degree of accuracy in identifying Bouc–Wen model parameters. Finally, the proposed method is used to find the Bouc–Wen model parameters from experimental data. The obtained model is found to be in good agreement with measured data. - Highlights: • We describe a new method to find the Bouc–Wen hysteresis model parameters. • We propose a Modified Firefly Algorithm. • We compare our method with existing methods to find that the proposed method performs better. • We use our model to fit experimental results. Good agreement is found

  3. Bouc–Wen hysteresis model identification using Modified Firefly Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Zaman, Mohammad Asif, E-mail: zaman@stanford.edu [Department of Electrical Engineering, Stanford University (United States); Sikder, Urmita [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (United States)

    2015-12-01

    The parameters of Bouc–Wen hysteresis model are identified using a Modified Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to improve its performance. The algorithm is used to find the model parameter values that results in the least amount of error between a set of given data points and points obtained from the Bouc–Wen model. The performance of the algorithm is compared with the performance of conventional Firefly Algorithm, Genetic Algorithm and Differential Evolution algorithm in terms of convergence rate and accuracy. Compared to the other three optimization algorithms, the proposed algorithm is found to have good convergence rate with high degree of accuracy in identifying Bouc–Wen model parameters. Finally, the proposed method is used to find the Bouc–Wen model parameters from experimental data. The obtained model is found to be in good agreement with measured data. - Highlights: • We describe a new method to find the Bouc–Wen hysteresis model parameters. • We propose a Modified Firefly Algorithm. • We compare our method with existing methods to find that the proposed method performs better. • We use our model to fit experimental results. Good agreement is found.

  4. Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chaoshun Li; Jianzhong Zhou [College of Hydroelectric Digitization Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2011-01-15

    Parameter identification of hydraulic turbine governing system (HTGS) is crucial in precise modeling of hydropower plant and provides support for the analysis of stability of power system. In this paper, a newly developed optimization algorithm, called gravitational search algorithm (GSA), is introduced and applied in parameter identification of HTGS, and the GSA is improved by combination of the search strategy of particle swarm optimization. Furthermore, a new weighted objective function is proposed in the identification frame. The improved gravitational search algorithm (IGSA), together with genetic algorithm, particle swarm optimization and GSA, is employed in parameter identification experiments and the procedure is validated by comparing experimental and simulated results. Consequently, IGSA is shown to locate more precise parameter values than the compared methods with higher efficiency. (author)

  5. Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm

    International Nuclear Information System (INIS)

    Li Chaoshun; Zhou Jianzhong

    2011-01-01

    Parameter identification of hydraulic turbine governing system (HTGS) is crucial in precise modeling of hydropower plant and provides support for the analysis of stability of power system. In this paper, a newly developed optimization algorithm, called gravitational search algorithm (GSA), is introduced and applied in parameter identification of HTGS, and the GSA is improved by combination of the search strategy of particle swarm optimization. Furthermore, a new weighted objective function is proposed in the identification frame. The improved gravitational search algorithm (IGSA), together with genetic algorithm, particle swarm optimization and GSA, is employed in parameter identification experiments and the procedure is validated by comparing experimental and simulated results. Consequently, IGSA is shown to locate more precise parameter values than the compared methods with higher efficiency.

  6. Particle Identification algorithm for the CLIC ILD and CLIC SiD detectors

    CERN Document Server

    Nardulli, J

    2011-01-01

    This note describes the algorithm presently used to determine the particle identification performance for single particles for the CLIC ILD and CLIC SiD detector concepts as prepared in the CLIC Conceptual Design Report.

  7. Verification of Single-Peptide Protein Identifications by the Application of Complementary Database Search Algorithms

    National Research Council Canada - National Science Library

    Rohrbough, James G; Breci, Linda; Merchant, Nirav; Miller, Susan; Haynes, Paul A

    2005-01-01

    .... One such technique, known as the Multi-Dimensional Protein Identification Technique, or MudPIT, involves the use of computer search algorithms that automate the process of identifying proteins...

  8. Particle mis-identification rate algorithm for the CLIC ILD and CLIC SiD detectors

    CERN Document Server

    Nardulli, J

    2011-01-01

    This note describes the algorithm presently used to determine the particle mis- identification rate and gives results for single particles for the CLIC ILD and CLIC SiD detector concepts as prepared for the CLIC Conceptual Design Report.

  9. Improved gravitational search algorithm for parameter identification of water turbine regulation system

    International Nuclear Information System (INIS)

    Chen, Zhihuan; Yuan, Xiaohui; Tian, Hao; Ji, Bin

    2014-01-01

    Highlights: • We propose an improved gravitational search algorithm (IGSA). • IGSA is applied to parameter identification of water turbine regulation system (WTRS). • WTRS is modeled by considering the impact of turbine speed on torque and water flow. • Weighted objective function strategy is applied to parameter identification of WTRS. - Abstract: Parameter identification of water turbine regulation system (WTRS) is crucial in precise modeling hydropower generating unit (HGU) and provides support for the adaptive control and stability analysis of power system. In this paper, an improved gravitational search algorithm (IGSA) is proposed and applied to solve the identification problem for WTRS system under load and no-load running conditions. This newly algorithm which is based on standard gravitational search algorithm (GSA) accelerates convergence speed with combination of the search strategy of particle swarm optimization and elastic-ball method. Chaotic mutation which is devised to stepping out the local optimal with a certain probability is also added into the algorithm to avoid premature. Furthermore, a new kind of model associated to the engineering practices is built and analyzed in the simulation tests. An illustrative example for parameter identification of WTRS is used to verify the feasibility and effectiveness of the proposed IGSA, as compared with standard GSA and particle swarm optimization in terms of parameter identification accuracy and convergence speed. The simulation results show that IGSA performs best for all identification indicators

  10. Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

    Science.gov (United States)

    Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

    2017-10-01

    Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

  11. DNA evolutionary algorithm (DNAEA) for source term identification in convection-diffusion equation

    International Nuclear Information System (INIS)

    Yang, X-H; Hu, X-X; Shen, Z-Y

    2008-01-01

    The source identification problem is changed into an optimization problem in this paper. This is a complicated nonlinear optimization problem. It is very intractable with traditional optimization methods. So DNA evolutionary algorithm (DNAEA) is presented to solve the discussed problem. In this algorithm, an initial population is generated by a chaos algorithm. With the shrinking of searching range, DNAEA gradually directs to an optimal result with excellent individuals obtained by DNAEA. The position and intensity of pollution source are well found with DNAEA. Compared with Gray-coded genetic algorithm and pure random search algorithm, DNAEA has rapider convergent speed and higher calculation precision

  12. Enhanced backpropagation training algorithm for transient event identification

    International Nuclear Information System (INIS)

    Vitela, J.; Reifman, J.

    1993-01-01

    We present an enhanced backpropagation (BP) algorithm for training feedforward neural networks that avoids the undesirable premature saturation of the network output nodes and accelerates the training process even in cases where premature saturation is not present. When the standard BP algorithm is applied to train patterns of nuclear power plant (NPP) transients, the network output nodes often become prematurely saturated causing the already slow rate of convergence of the algorithm to become even slower. When premature saturation occurs, the gradient of the prediction error becomes very small, although the prediction error itself is still large, yielding negligible weight updates and hence no significant decrease in the prediction error until the eventual recovery of the output nodes from saturation. By defining the onset of premature saturation and systematically modifying the gradient of the prediction error at saturation, we developed an enhanced BP algorithm that is compared with the standard BP algorithm in training a network to identify NPP transients

  13. Identification of chaotic systems by neural network with hybrid learning algorithm

    International Nuclear Information System (INIS)

    Pan, S.-T.; Lai, C.-C.

    2008-01-01

    Based on the genetic algorithm (GA) and steepest descent method (SDM), this paper proposes a hybrid algorithm for the learning of neural networks to identify chaotic systems. The systems in question are the logistic map and the Duffing equation. Different identification schemes are used to identify both the logistic map and the Duffing equation, respectively. Simulation results show that our hybrid algorithm is more efficient than that of other methods

  14. Regularization algorithm within two-parameters for identification heat-coefficient in the parabolic equation

    International Nuclear Information System (INIS)

    Hinestroza Gutierrez, D.

    2006-08-01

    In this work a new and promising algorithm based on the minimization of especial functional that depends on two regularization parameters is considered for the identification of the heat conduction coefficient in the parabolic equation. This algorithm uses the adjoint and sensibility equations. One of the regularization parameters is associated with the heat-coefficient (as in conventional Tikhonov algorithms) but the other is associated with the calculated solution. (author)

  15. Regularization algorithm within two-parameters for identification heat-coefficient in the parabolic equation

    International Nuclear Information System (INIS)

    Hinestroza Gutierrez, D.

    2006-12-01

    In this work a new and promising algorithm based in the minimization of especial functional that depends on two regularization parameters is considered for identification of the heat conduction coefficient in the parabolic equation. This algorithm uses the adjoint and sensibility equations. One of the regularization parameters is associated with the heat-coefficient (as in conventional Tikhonov algorithms) but the other is associated with the calculated solution. (author)

  16. An efficient attack identification and risk prediction algorithm for ...

    African Journals Online (AJOL)

    The social media is highly utilized cloud for storing huge amount of data. ... However, the adversarial scenario did not design properly to maintain the privacy of the ... Information Retrieval, Security Evaluation, Efficient Attack Identification and ...

  17. Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

    International Nuclear Information System (INIS)

    Canedo Medeiros, Jose Antonio Carlos; Schirru, Roberto

    2008-01-01

    In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results

  18. Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems

    Directory of Open Access Journals (Sweden)

    Ignacio Santamaría

    2008-04-01

    Full Text Available This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.

  19. Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Canedo Medeiros, Jose Antonio Carlos [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: canedo@lmp.ufrj.br; Schirru, Roberto [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: schirru@lmp.ufrj.br

    2008-04-15

    In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results.

  20. Word-length algorithm for language identification of under-resourced languages

    Directory of Open Access Journals (Sweden)

    Ali Selamat

    2016-10-01

    Full Text Available Language identification is widely used in machine learning, text mining, information retrieval, and speech processing. Available techniques for solving the problem of language identification do require large amount of training text that are not available for under-resourced languages which form the bulk of the World’s languages. The primary objective of this study is to propose a lexicon based algorithm which is able to perform language identification using minimal training data. Because language identification is often the first step in many natural language processing tasks, it is necessary to explore techniques that will perform language identification in the shortest possible time. Hence, the second objective of this research is to study the effect of the proposed algorithm on the run-time performance of language identification. Precision, recall, and F1 measures were used to determine the effectiveness of the proposed word length algorithm using datasets drawn from the Universal Declaration of Human Rights Act in 15 languages. The experimental results show good accuracy on language identification at the document level and at the sentence level based on the available dataset. The improved algorithm also showed significant improvement in run time performance compared with the spelling checker approach.

  1. Theoretical algorithms for satellite-derived sea surface temperatures

    Science.gov (United States)

    Barton, I. J.; Zavody, A. M.; O'Brien, D. M.; Cutten, D. R.; Saunders, R. W.; Llewellyn-Jones, D. T.

    1989-03-01

    Reliable climate forecasting using numerical models of the ocean-atmosphere system requires accurate data sets of sea surface temperature (SST) and surface wind stress. Global sets of these data will be supplied by the instruments to fly on the ERS 1 satellite in 1990. One of these instruments, the Along-Track Scanning Radiometer (ATSR), has been specifically designed to provide SST in cloud-free areas with an accuracy of 0.3 K. The expected capabilities of the ATSR can be assessed using transmission models of infrared radiative transfer through the atmosphere. The performances of several different models are compared by estimating the infrared brightness temperatures measured by the NOAA 9 AVHRR for three standard atmospheres. Of these, a computationally quick spectral band model is used to derive typical AVHRR and ATSR SST algorithms in the form of linear equations. These algorithms show that a low-noise 3.7-μm channel is required to give the best satellite-derived SST and that the design accuracy of the ATSR is likely to be achievable. The inclusion of extra water vapor information in the analysis did not improve the accuracy of multiwavelength SST algorithms, but some improvement was noted with the multiangle technique. Further modeling is required with atmospheric data that include both aerosol variations and abnormal vertical profiles of water vapor and temperature.

  2. A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

    Science.gov (United States)

    Kazemi, Mahdi; Arefi, Mohammad Mehdi

    2017-03-01

    In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  3. An AUTONOMOUS STAR IDENTIFICATION ALGORITHM BASED ON THE DIRECTED CIRCULARITY PATTERN

    Directory of Open Access Journals (Sweden)

    J. Xie

    2012-07-01

    Full Text Available The accuracy of the angular distance may decrease due to lots of factors, such as the parameters of the stellar camera aren't calibrated on-orbit, or the location accuracy of the star image points is low, and so on, which can cause the low success rates of star identification. A robust directed circularity pattern algorithm is proposed in this paper, which is developed on basis of the matching probability algorithm. The improved algorithm retains the matching probability strategy to identify master star, and constructs a directed circularity pattern with the adjacent stars for unitary matching. The candidate matching group which has the longest chain will be selected as the final result. Simulation experiments indicate that the improved algorithm has high successful identification and reliability etc, compared with the original algorithm. The experiments with real data are used to verify it.

  4. Neuro-diffuse algorithm for neutronic power identification of TRIGA Mark III reactor

    International Nuclear Information System (INIS)

    Rojas R, E.; Benitez R, J. S.; Segovia de los Rios, J. A.; Rivero G, T.

    2009-10-01

    In this work are presented the results of design and implementation of an algorithm based on diffuse logic systems and neural networks like method of neutronic power identification of TRIGA Mark III reactor. This algorithm uses the punctual kinetics equation as data generator of training, a cost function and a learning stage based on the descending gradient algorithm allow to optimize the parameters of membership functions of a diffuse system. Also, a series of criteria like part of the initial conditions of training algorithm are established. These criteria according to the carried out simulations show a quick convergence of neutronic power estimated from the first iterations. (Author)

  5. Lost-in-Space Star Identification Using Planar Triangle Principal Component Analysis Algorithm

    Directory of Open Access Journals (Sweden)

    Fuqiang Zhou

    2015-01-01

    Full Text Available It is a challenging task for a star sensor to implement star identification and determine the attitude of a spacecraft in the lost-in-space mode. Several algorithms based on triangle method are proposed for star identification in this mode. However, these methods hold great time consumption and large guide star catalog memory size. The star identification performance of these methods requires improvements. To address these problems, a star identification algorithm using planar triangle principal component analysis is presented here. A star pattern is generated based on the planar triangle created by stars within the field of view of a star sensor and the projection of the triangle. Since a projection can determine an index for a unique triangle in the catalog, the adoption of the k-vector range search technique makes this algorithm very fast. In addition, a sharing star validation method is constructed to verify the identification results. Simulation results show that the proposed algorithm is more robust than the planar triangle and P-vector algorithms under the same conditions.

  6. A simple algorithm for the identification of clinical COPD phenotypes

    NARCIS (Netherlands)

    Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim; Piquet, Jacques; ter Riet, Gerben; Garcia-Aymerich, Judith; Cosio, Borja; Bakke, Per; Puhan, Milo A.; Langhammer, Arnulf; Alfageme, Inmaculada; Almagro, Pere; Ancochea, Julio; Celli, Bartolome R.; Casanova, Ciro; de-Torres, Juan P.; Decramer, Marc; Echazarreta, Andrés; Esteban, Cristobal; Gomez Punter, Rosa Mar; Han, MeiLan K.; Johannessen, Ane; Kaiser, Bernhard; Lamprecht, Bernd; Lange, Peter; Leivseth, Linda; Marin, Jose M.; Martin, Francis; Martinez-Camblor, Pablo; Miravitlles, Marc; Oga, Toru; Sofia Ramírez, Ana; Sin, Don D.; Sobradillo, Patricia; Soler-Cataluña, Juan J.; Turner, Alice M.; Verdu Rivera, Francisco Javier; Soriano, Joan B.; Roche, Nicolas

    2017-01-01

    This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses. Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of

  7. Tau Reconstruction, Identification Algorithms and Performance in ATLAS

    DEFF Research Database (Denmark)

    Simonyan, M.

    2013-01-01

    identification of hadronically decaying tau leptons is achieved by using detailed information from tracking and calorimeter detector components. Variables describing the properties of calorimeter energy deposits and track reconstruction within tau candidates are combined in multi-variate discriminants...... by investigating single hadron calorimeter response, as well as kinematic distributions in Z¿ tt events....

  8. Identification of partial blockages in pipelines using genetic algorithms

    Indian Academy of Sciences (India)

    A methodology to identify the partial blockages in a simple pipeline using genetic algorithms for non-harmonic flows is presented in this paper. A sinusoidal flow generated by the periodic on-and-off operation of a valve at the outlet is investigated in the time domain and it is observed that pressure variation at the valve is ...

  9. Computer vision algorithm for diabetic foot injury identification and evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Castaneda M, C. L.; Solis S, L. O.; Martinez B, M. R.; Ortiz R, J. M.; Garza V, I.; Martinez F, M.; Castaneda M, R.; Vega C, H. R., E-mail: lsolis@uaz.edu.mx [Universidad Autonoma de Zacatecas, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Diabetic foot is one of the most devastating consequences related to diabetes. It is relevant because of its incidence and the elevated percentage of amputations and deaths that the disease implies. Given the fact that the existing tests and laboratories designed to diagnose it are limited and expensive, the most common evaluation is still based on signs and symptoms. This means that the specialist completes a questionnaire based solely on observation and an invasive wound measurement. Using the questionnaire, the physician issues a diagnosis. In the sense, the diagnosis relies only on the criteria and the specialists experience. For some variables such as the lesions area or their location, this dependency is not acceptable. Currently bio-engineering has played a key role on the diagnose of different chronic degenerative diseases. A timely diagnose has proven to be the best tool against diabetic foot. The diabetics foot clinical evaluation, increases the possibility to identify risks and further complications. The main goal of this paper is to present the development of an algorithm based on digital image processing techniques, which enables to optimize the results on the diabetics foot lesion evaluation. Using advanced techniques for object segmentation and adjusting the sensibility parameter, allows the correlation between the algorithms identified wounds and those observed by the physician. Using the developed algorithm it is possible to identify and assess the wounds, their size, and location, in a non-invasive way. (Author)

  10. Computer vision algorithm for diabetic foot injury identification and evaluation

    International Nuclear Information System (INIS)

    Castaneda M, C. L.; Solis S, L. O.; Martinez B, M. R.; Ortiz R, J. M.; Garza V, I.; Martinez F, M.; Castaneda M, R.; Vega C, H. R.

    2016-10-01

    Diabetic foot is one of the most devastating consequences related to diabetes. It is relevant because of its incidence and the elevated percentage of amputations and deaths that the disease implies. Given the fact that the existing tests and laboratories designed to diagnose it are limited and expensive, the most common evaluation is still based on signs and symptoms. This means that the specialist completes a questionnaire based solely on observation and an invasive wound measurement. Using the questionnaire, the physician issues a diagnosis. In the sense, the diagnosis relies only on the criteria and the specialists experience. For some variables such as the lesions area or their location, this dependency is not acceptable. Currently bio-engineering has played a key role on the diagnose of different chronic degenerative diseases. A timely diagnose has proven to be the best tool against diabetic foot. The diabetics foot clinical evaluation, increases the possibility to identify risks and further complications. The main goal of this paper is to present the development of an algorithm based on digital image processing techniques, which enables to optimize the results on the diabetics foot lesion evaluation. Using advanced techniques for object segmentation and adjusting the sensibility parameter, allows the correlation between the algorithms identified wounds and those observed by the physician. Using the developed algorithm it is possible to identify and assess the wounds, their size, and location, in a non-invasive way. (Author)

  11. Performance study of LMS based adaptive algorithms for unknown system identification

    International Nuclear Information System (INIS)

    Javed, Shazia; Ahmad, Noor Atinah

    2014-01-01

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment

  12. Performance study of LMS based adaptive algorithms for unknown system identification

    Energy Technology Data Exchange (ETDEWEB)

    Javed, Shazia; Ahmad, Noor Atinah [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 Penang (Malaysia)

    2014-07-10

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  13. Chaotic Artificial Bee Colony Algorithm for System Identification of a Small-Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Li Ding

    2015-01-01

    Full Text Available The purpose of this paper is devoted to developing a chaotic artificial bee colony algorithm (CABC for the system identification of a small-scale unmanned helicopter state-space model in hover condition. In order to avoid the premature of traditional artificial bee colony algorithm (ABC, which is stuck in local optimum and can not reach the global optimum, a novel chaotic operator with the characteristics of ergodicity and irregularity was introduced to enhance its performance. With input-output data collected from actual flight experiments, the identification results showed the superiority of CABC over the ABC and the genetic algorithm (GA. Simulations are presented to demonstrate the effectiveness of our proposed algorithm and the accuracy of the identified helicopter model.

  14. A gradient based algorithm to solve inverse plane bimodular problems of identification

    Science.gov (United States)

    Ran, Chunjiang; Yang, Haitian; Zhang, Guoqing

    2018-02-01

    This paper presents a gradient based algorithm to solve inverse plane bimodular problems of identifying constitutive parameters, including tensile/compressive moduli and tensile/compressive Poisson's ratios. For the forward bimodular problem, a FE tangent stiffness matrix is derived facilitating the implementation of gradient based algorithms, for the inverse bimodular problem of identification, a two-level sensitivity analysis based strategy is proposed. Numerical verification in term of accuracy and efficiency is provided, and the impacts of initial guess, number of measurement points, regional inhomogeneity, and noisy data on the identification are taken into accounts.

  15. Identification of chaotic systems with hidden variables (modified Bock's algorithm)

    International Nuclear Information System (INIS)

    Bezruchko, Boris P.; Smirnov, Dmitry A.; Sysoev, Ilya V.

    2006-01-01

    We address the problem of estimating parameters of chaotic dynamical systems from a time series in a situation when some of state variables are not observed and/or the data are very noisy. Using specially developed quantitative criteria, we compare performance of the original multiple shooting approach (Bock's algorithm) and its modified version. The latter is shown to be significantly superior for long chaotic time series. In particular, it allows to obtain accurate estimates for much worse starting guesses for the estimated parameters

  16. ALGORITHMS FOR IDENTIFICATION OF CUES WITH AUTHORS’ TEXT INSERTIONS IN BELARUSIAN ELECTRONIC BOOKS

    Directory of Open Access Journals (Sweden)

    Y. S. Hetsevich

    2014-01-01

    Full Text Available The main stages of algorithms for characters’ gender identification in Belarusian electronic texts are described. The algorithms are based on punctuation marking and gender indicators detection, such as past tense verbs and nouns with gender attributes. For indicators, special dictionaries are developed, thus making the algorithms more language-independent and allowing to create dictionaries for cognate languages. Testing showed the following results: the mean harmonic quantity for masculine gender detection makes up 92,2 %, and for feminine gender detection – 90,4%.

  17. E-Waste recycling: new algorithm for hyper spectral identification

    International Nuclear Information System (INIS)

    Picon-Ruiz, A.; Echazarra-Higuet, J.; Bereciartua-Perez, A.

    2010-01-01

    Waste electrical and Electronic Equipment (WEEE) constitutes 4% of the municipal waste in Europe, being increased by 16-28% every five years. Nowadays, Europe produces 6,5 million tonnes of WEEE per year and currently 90% goes to landfill. WEEE waste is growing 3 times faster than municipal waste and this figure is expected to be increased up to 12 million tones by 2015. Applying a new technology to separate non-ferrous metal Waste from WEEE is the aim of this paper, by identifying multi-and hyper-spectral materials and inserting them in a recycling plant. This technology will overcome the shortcomings passed by current methods, which are unable to separate valuable materials very similar in colour, size or shape. For this reason, it is necessary to develop new algorithms able to distinguish among these materials and to face the timing requirements. (Author). 22 refs.

  18. Cloud identification using genetic algorithms and massively parallel computation

    Science.gov (United States)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

  19. Efficient algorithms for maximum likelihood decoding in the surface code

    Science.gov (United States)

    Bravyi, Sergey; Suchara, Martin; Vargo, Alexander

    2014-09-01

    We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the two-dimensional surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time O (n2), where n is the number of code qubits. Our implementation uses a reduction from MLD to simulation of matchgate quantum circuits. This reduction however requires a special noise model with independent bit-flip and phase-flip errors. Secondly, we show how to implement MLD approximately for more general noise models using matrix product states (MPS). Our implementation has running time O (nχ3), where χ is a parameter that controls the approximation precision. The key step of our algorithm, borrowed from the density matrix renormalization-group method, is a subroutine for contracting a tensor network on the two-dimensional grid. The subroutine uses MPS with a bond dimension χ to approximate the sequence of tensors arising in the course of contraction. We benchmark the MPS-based decoder against the standard minimum weight matching decoder observing a significant reduction of the logical error probability for χ ≥4.

  20. An airport surface surveillance solution based on fusion algorithm

    Science.gov (United States)

    Liu, Jianliang; Xu, Yang; Liang, Xuelin; Yang, Yihuang

    2017-01-01

    In this paper, we propose an airport surface surveillance solution combined with Multilateration (MLAT) and Automatic Dependent Surveillance Broadcast (ADS-B). The moving target to be monitored is regarded as a linear stochastic hybrid system moving freely and each surveillance technology is simplified as a sensor with white Gaussian noise. The dynamic model of target and the observation model of sensor are established in this paper. The measurements of sensors are filtered properly by estimators to get the estimation results for current time. Then, we analysis the characteristics of two fusion solutions proposed, and decide to use the scheme based on sensor estimation fusion for our surveillance solution. In the proposed fusion algorithm, according to the output of estimators, the estimation error is quantified, and the fusion weight of each sensor is calculated. The two estimation results are fused with weights, and the position estimation of target is computed accurately. Finally the proposed solution and algorithm are validated by an illustrative target tracking simulation.

  1. Coherency Identification of Generators Using a PAM Algorithm for Dynamic Reduction of Power Systems

    Directory of Open Access Journals (Sweden)

    Seung-Il Moon

    2012-11-01

    Full Text Available This paper presents a new coherency identification method for dynamic reduction of a power system. To achieve dynamic reduction, coherency-based equivalence techniques divide generators into groups according to coherency, and then aggregate them. In order to minimize the changes in the dynamic response of the reduced equivalent system, coherency identification of the generators should be clearly defined. The objective of the proposed coherency identification method is to determine the optimal coherent groups of generators with respect to the dynamic response, using the Partitioning Around Medoids (PAM algorithm. For this purpose, the coherency between generators is first evaluated from the dynamic simulation time response, and in the proposed method this result is then used to define a dissimilarity index. Based on the PAM algorithm, the coherent generator groups are then determined so that the sum of the index in each group is minimized. This approach ensures that the dynamic characteristics of the original system are preserved, by providing the optimized coherency identification. To validate the effectiveness of the technique, simulated cases with an IEEE 39-bus test system are evaluated using PSS/E. The proposed method is compared with an existing coherency identification method, which uses the K-means algorithm, and is found to provide a better estimate of the original system. 

  2. Radionuclide identification algorithm for organic scintillator-based radiation portal monitor

    Energy Technology Data Exchange (ETDEWEB)

    Paff, Marc Gerrit, E-mail: mpaff@umich.edu; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.

    2017-03-21

    We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.

  3. Radionuclide identification algorithm for organic scintillator-based radiation portal monitor

    Science.gov (United States)

    Paff, Marc Gerrit; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.

    2017-03-01

    We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.

  4. Sensor placement optimization for structural modal identification of flexible structures using genetic algorithm

    International Nuclear Information System (INIS)

    Jung, B. K.; Cho, J. R.; Jeong, W. B.

    2015-01-01

    The position of vibration sensors influences the modal identification quality of flexible structures for a given number of sensors, and the quality of modal identification is usually estimated in terms of correlation between the natural modes using the modal assurance criterion (MAC). The sensor placement optimization is characterized by the fact that the design variables are not continuous but discrete, implying that the conventional sensitivity-driven optimization methods are not applicable. In this context, this paper presents the application of genetic algorithm to the sensor placement optimization for improving the modal identification quality of flexible structures. A discrete-type optimization problem using genetic algorithm is formulated by defining the sensor positions and the MAC as the design variables and the objective function, respectively. The proposed GA-based evolutionary optimization method is validated through the numerical experiment with a rectangular plate, and its excellence is verified from the comparison with the cases using different modal correlation measures.

  5. A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation

    Directory of Open Access Journals (Sweden)

    Olympia Roeva

    2004-10-01

    Full Text Available This paper presents the use of genetic algorithms for identification of Escherichia coli fed-batch fermentation process. Genetic algorithms are a directed random search technique, based on the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search space. The dynamic behavior of considered process has known nonlinear structure, described with a system of deterministic nonlinear differential equations according to the mass balance. The parameters of the model are estimated using genetic algorithms. Simulation examples for demonstration of the effectiveness and robustness of the proposed identification scheme are included. As a result, the model accurately predicts the process of cultivation of E. coli.

  6. Performance Comparison of Different System Identification Algorithms for FACET and ATF2

    CERN Document Server

    Pfingstner, J; Schulte, D

    2013-01-01

    Good system knowledge is an essential ingredient for the operation of modern accelerator facilities. For example, beam-based alignment algorithms and orbit feedbacks rely strongly on a precise measurement of the orbit response matrix. The quality of the measurement of this matrix can be improved over time by statistically combining the effects of small system excitations with the help of system identification algorithms. These small excitations can be applied in a parasitic mode without stopping the accelerator operation (on-line). In this work, different system identification algorithms are used in simulation studies for the response matrix measurement at ATF2. The results for ATF2 are finally compared with the results for FACET, latter originating from an earlier work.

  7. Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm

    International Nuclear Information System (INIS)

    Sun, Zhe; Wang, Ning; Bi, Yunrui; Srinivasan, Dipti

    2015-01-01

    In this paper, a HADE (hybrid adaptive differential evolution) algorithm is proposed for the identification problem of PEMFC (proton exchange membrane fuel cell). Inspired by biological genetic strategy, a novel adaptive scaling factor and a dynamic crossover probability are presented to improve the adaptive and dynamic performance of differential evolution algorithm. Moreover, two kinds of neighborhood search operations based on the bee colony foraging mechanism are introduced for enhancing local search efficiency. Through testing the benchmark functions, the proposed algorithm exhibits better performance in convergent accuracy and speed. Finally, the HADE algorithm is applied to identify the nonlinear parameters of PEMFC stack model. Through experimental comparison with other identified methods, the PEMFC model based on the HADE algorithm shows better performance. - Highlights: • We propose a hybrid adaptive differential evolution algorithm (HADE). • The search efficiency is enhanced in low and high dimension search space. • The effectiveness is confirmed by testing benchmark functions. • The identification of the PEMFC model is conducted by adopting HADE.

  8. Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model.

    Science.gov (United States)

    Laamiri, Imen; Khouaja, Anis; Messaoud, Hassani

    2015-03-01

    In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS). Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Identification of time-varying nonlinear systems using differential evolution algorithm

    DEFF Research Database (Denmark)

    Perisic, Nevena; Green, Peter L; Worden, Keith

    2013-01-01

    (DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...

  10. Comparison of Clustering Algorithms for the Identification of Topics on Twitter

    Directory of Open Access Journals (Sweden)

    Marjori N. M. Klinczak

    2016-05-01

    Full Text Available Topic Identification in Social Networks has become an important task when dealing with event detection, particularly when global communities are affected. In order to attack this problem, text processing techniques and machine learning algorithms have been extensively used. In this paper we compare four clustering algorithms – k-means, k-medoids, DBSCAN and NMF (Non-negative Matrix Factorization – in order to detect topics related to textual messages obtained from Twitter. The algorithms were applied to a database initially composed by tweets having hashtags related to the recent Nepal earthquake as initial context. Obtained results suggest that the NMF clustering algorithm presents superior results, providing simpler clusters that are also easier to interpret.

  11. A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

    Science.gov (United States)

    Hong, Xia

    2006-07-01

    In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

  12. Parameter identification based on modified simulated annealing differential evolution algorithm for giant magnetostrictive actuator

    Science.gov (United States)

    Gao, Xiaohui; Liu, Yongguang

    2018-01-01

    There is a serious nonlinear relationship between input and output in the giant magnetostrictive actuator (GMA) and how to establish mathematical model and identify its parameters is very important to study characteristics and improve control accuracy. The current-displacement model is firstly built based on Jiles-Atherton (J-A) model theory, Ampere loop theorem and stress-magnetism coupling model. And then laws between unknown parameters and hysteresis loops are studied to determine the data-taking scope. The modified simulated annealing differential evolution algorithm (MSADEA) is proposed by taking full advantage of differential evolution algorithm's fast convergence and simulated annealing algorithm's jumping property to enhance the convergence speed and performance. Simulation and experiment results shows that this algorithm is not only simple and efficient, but also has fast convergence speed and high identification accuracy.

  13. Response-only modal identification using random decrement algorithm with time-varying threshold level

    International Nuclear Information System (INIS)

    Lin, Chang Sheng; Tseng, Tse Chuan

    2014-01-01

    Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional random decrement algorithm, the threshold level for evaluating random dec signatures is defined as the standard deviation value of response data of the reference channel. The distortion of random dec signatures may be, however, induced by the error involved in noise from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of available sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality, such as the time-varying amplitude (variance) of a nonstationary process in a seismic record. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.

  14. A Brightness-Referenced Star Identification Algorithm for APS Star Trackers

    Science.gov (United States)

    Zhang, Peng; Zhao, Qile; Liu, Jingnan; Liu, Ning

    2014-01-01

    Star trackers are currently the most accurate spacecraft attitude sensors. As a result, they are widely used in remote sensing satellites. Since traditional charge-coupled device (CCD)-based star trackers have a limited sensitivity range and dynamic range, the matching process for a star tracker is typically not very sensitive to star brightness. For active pixel sensor (APS) star trackers, the intensity of an imaged star is valuable information that can be used in star identification process. In this paper an improved brightness referenced star identification algorithm is presented. This algorithm utilizes the k-vector search theory and adds imaged stars' intensities to narrow the search scope and therefore increase the efficiency of the matching process. Based on different imaging conditions (slew, bright bodies, etc.) the developed matching algorithm operates in one of two identification modes: a three-star mode, and a four-star mode. If the reference bright stars (the stars brighter than three magnitude) show up, the algorithm runs the three-star mode and efficiency is further improved. The proposed method was compared with other two distinctive methods the pyramid and geometric voting methods. All three methods were tested with simulation data and actual in orbit data from the APS star tracker of ZY-3. Using a catalog composed of 1500 stars, the results show that without false stars the efficiency of this new method is 4∼5 times that of the pyramid method and 35∼37 times that of the geometric method. PMID:25299950

  15. Multivariate algorithms for initiating event detection and identification in nuclear power plants

    International Nuclear Information System (INIS)

    Wu, Shun-Chi; Chen, Kuang-You; Lin, Ting-Han; Chou, Hwai-Pwu

    2018-01-01

    Highlights: •Multivariate algorithms for NPP initiating event detection and identification. •Recordings from multiple sensors are simultaneously considered for detection. •Both spatial and temporal information is used for event identification. •Untrained event isolation avoids falsely relating an untrained event. •Efficacy of the algorithms is verified with data from the Maanshan NPP simulator. -- Abstract: To prevent escalation of an initiating event into a severe accident, promptly detecting its occurrence and precisely identifying its type are essential. In this study, several multivariate algorithms for initiating event detection and identification are proposed to help maintain safe operations of nuclear power plants (NPPs). By monitoring changes in the NPP sensing variables, an event is detected when the preset thresholds are exceeded. Unlike existing approaches, recordings from sensors of the same type are simultaneously considered for detection, and no subjective reasoning is involved in setting these thresholds. To facilitate efficient event identification, a spatiotemporal feature extractor is proposed. The extracted features consist of the temporal traits used by existing techniques and the spatial signature of an event. Through an F-score-based feature ranking, only those that are most discriminant in classifying the events under consideration will be retained for identification. Moreover, an untrained event isolation scheme is introduced to avoid relating an untrained event to those in the event dataset so that improper recovery actions can be prevented. Results from experiments containing data of 12 event classes and a total of 125 events generated using a Taiwan’s Maanshan NPP simulator are provided to illustrate the efficacy of the proposed algorithms.

  16. A New Algorithm for Radioisotope Identification of Shielded and Masked SNM/RDD Materials

    International Nuclear Information System (INIS)

    Jeffcoat, R.

    2012-01-01

    Detection and identification of shielded and masked nuclear materials is crucial to national security, but vast borders and high volumes of traffic impose stringent requirements for practical detection systems. Such tools must be be mobile, and hence low power, provide a low false alarm rate, and be sufficiently robust to be operable by non-technical personnel. Currently fielded systems have not achieved all of these requirements simultaneously. Transport modeling such as that done in GADRAS is able to predict observed spectra to a high degree of fidelity; our research is focusing on a radionuclide identification algorithm that inverts this modeling within the constraints imposed by a handheld device. Key components of this work include incorporation of uncertainty as a function of both the background radiation estimate and the hypothesized sources, dimensionality reduction, and nonnegative matrix factorization. We have partially evaluated performance of our algorithm on a third-party data collection made with two different sodium iodide detection devices. Initial results indicate, with caveats, that our algorithm performs as good as or better than the on-board identification algorithms. The system developed was based on a probabilistic approach with an improved approach to variance modeling relative to past work. This system was chosen based on technical innovation and system performance over algorithms developed at two competing research institutions. One key outcome of this probabilistic approach was the development of an intuitive measure of confidence which was indeed useful enough that a classification algorithm was developed based around alarming on high confidence targets. This paper will present and discuss results of this novel approach to accurately identifying shielded or masked radioisotopes with radiation detection systems.

  17. Online Identification of Photovoltaic Source Parameters by Using a Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Giovanni Petrone

    2017-12-01

    Full Text Available In this paper, an efficient method for the online identification of the photovoltaic single-diode model parameters is proposed. The combination of a genetic algorithm with explicit equations allows obtaining precise results without the direct measurement of short circuit current and open circuit voltage that is typically used in offline identification methods. Since the proposed method requires only voltage and current values close to the maximum power point, it can be easily integrated into any photovoltaic system, and it operates online without compromising the power production. The proposed approach has been implemented and tested on an embedded system, and it exhibits a good performance for monitoring/diagnosis applications.

  18. Parameter identification of Rossler's chaotic system by an evolutionary algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)]. E-mail: wdchang@mail.stu.edu.tw

    2006-09-15

    In this paper, a differential evolution (DE) algorithm is applied to parameter identification of Rossler's chaotic system. The differential evolution has been shown to possess a powerful searching capability for finding the solutions for a given optimization problem, and it allows for parameter solution to appear directly in the form of floating point without further numerical coding or decoding. Three unknown parameters of Rossler's Chaotic system are optimally estimated by using the DE algorithm. Finally, a numerical example is given to verify the effectiveness of the proposed method.

  19. A Novel Algorithm for Power Flow Transferring Identification Based on WAMS

    Directory of Open Access Journals (Sweden)

    Xu Yan

    2015-01-01

    Full Text Available After a faulted transmission line is removed, power flow on it will be transferred to other lines in the network. If those lines are heavily loaded beforehand, the transferred flow may cause the nonfault overload and the incorrect operation of far-ranging backup relays, which are considered as the key factors leading to cascading trips. In this paper, a novel algorithm for power flow transferring identification based on wide area measurement system (WAMS is proposed, through which the possible incorrect tripping of backup relays will be blocked in time. A new concept of Transferred Flow Characteristic Ratio (TFCR is presented and is applied to the identification criteria. Mathematical derivation of TFCR is carried out in detail by utilization of power system short circuit fault modeling. The feasibility and effectiveness of the proposed algorithm to prevent the malfunction of backup relays are demonstrated by a large number of simulations.

  20. Application of decision tree algorithm for identification of rock forming minerals using energy dispersive spectrometry

    Science.gov (United States)

    Akkaş, Efe; Çubukçu, H. Evren; Artuner, Harun

    2014-05-01

    C5.0 Decision Tree algorithm. The predictions of the decision tree classifier, namely the matching of the test data with the appropriate mineral group, yield an overall accuracy of >90%. Besides, the algorithm successfully discriminated some mineral (groups) despite their similar elemental composition such as orthopyroxene ((Mg,Fe)2[SiO6]) and olivine ((Mg,Fe)2[SiO4]). Furthermore, the effects of various operating conditions have been insignificant for the classifier. These results demonstrate that decision tree algorithm stands as an accurate, rapid and automated method for mineral classification/identification. Hence, decision tree algorithm would be a promising component of an expert system focused on real-time, automated mineral identification using energy dispersive spectrometers without being affected from the operating conditions. Keywords: mineral identification, energy dispersive spectrometry, decision tree algorithm.

  1. Load power device and system for real-time execution of hierarchical load identification algorithms

    Science.gov (United States)

    Yang, Yi; Madane, Mayura Arun; Zambare, Prachi Suresh

    2017-11-14

    A load power device includes a power input; at least one power output for at least one load; and a plurality of sensors structured to sense voltage and current at the at least one power output. A processor is structured to provide real-time execution of: (a) a plurality of load identification algorithms, and (b) event detection and operating mode detection for the at least one load.

  2. Online identification algorithms for integrated dielectric electroactive polymer sensors and self-sensing concepts

    International Nuclear Information System (INIS)

    Hoffstadt, Thorben; Griese, Martin; Maas, Jürgen

    2014-01-01

    Transducers based on dielectric electroactive polymers (DEAP) use electrostatic pressure to convert electric energy into strain energy or vice versa. Besides this, they are also designed for sensor applications in monitoring the actual stretch state on the basis of the deformation dependent capacitive–resistive behavior of the DEAP. In order to enable an efficient and proper closed loop control operation of these transducers, e.g. in positioning or energy harvesting applications, on the one hand, sensors based on DEAP material can be integrated into the transducers and evaluated externally, and on the other hand, the transducer itself can be used as a sensor, also in terms of self-sensing. For this purpose the characteristic electrical behavior of the transducer has to be evaluated in order to determine the mechanical state. Also, adequate online identification algorithms with sufficient accuracy and dynamics are required, independent from the sensor concept utilized, in order to determine the electrical DEAP parameters in real time. Therefore, in this contribution, algorithms are developed in the frequency domain for identifications of the capacitance as well as the electrode and polymer resistance of a DEAP, which are validated by measurements. These algorithms are designed for self-sensing applications, especially if the power electronics utilized is operated at a constant switching frequency, and parasitic harmonic oscillations are induced besides the desired DC value. These oscillations can be used for the online identification, so an additional superimposed excitation is no longer necessary. For this purpose a dual active bridge (DAB) is introduced to drive the DEAP transducer. The capabilities of the real-time identification algorithm in combination with the DAB are presented in detail and discussed, finally. (paper)

  3. An integer optimization algorithm for robust identification of non-linear gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Chemmangattuvalappil Nishanth

    2012-09-01

    Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

  4. Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Yanbin Gao

    2015-01-01

    Full Text Available Artificial fish swarm algorithm (AFSA is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS. In this study, a novel artificial fish swarm algorithm (NAFSA that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification.

  5. Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

    Science.gov (United States)

    Zhang, Shou-ping; Xin, Xiao-kang

    2017-07-01

    Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

  6. High reliability - low noise radionuclide signature identification algorithms for border security applications

    Science.gov (United States)

    Lee, Sangkyu

    Illicit trafficking and smuggling of radioactive materials and special nuclear materials (SNM) are considered as one of the most important recent global nuclear threats. Monitoring the transport and safety of radioisotopes and SNM are challenging due to their weak signals and easy shielding. Great efforts worldwide are focused at developing and improving the detection technologies and algorithms, for accurate and reliable detection of radioisotopes of interest in thus better securing the borders against nuclear threats. In general, radiation portal monitors enable detection of gamma and neutron emitting radioisotopes. Passive or active interrogation techniques, present and/or under the development, are all aimed at increasing accuracy, reliability, and in shortening the time of interrogation as well as the cost of the equipment. Equally important efforts are aimed at advancing algorithms to process the imaging data in an efficient manner providing reliable "readings" of the interiors of the examined volumes of various sizes, ranging from cargos to suitcases. The main objective of this thesis is to develop two synergistic algorithms with the goal to provide highly reliable - low noise identification of radioisotope signatures. These algorithms combine analysis of passive radioactive detection technique with active interrogation imaging techniques such as gamma radiography or muon tomography. One algorithm consists of gamma spectroscopy and cosmic muon tomography, and the other algorithm is based on gamma spectroscopy and gamma radiography. The purpose of fusing two detection methodologies per algorithm is to find both heavy-Z radioisotopes and shielding materials, since radionuclides can be identified with gamma spectroscopy, and shielding materials can be detected using muon tomography or gamma radiography. These combined algorithms are created and analyzed based on numerically generated images of various cargo sizes and materials. In summary, the three detection

  7. Final Progress Report: Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes Feasibility Study

    International Nuclear Information System (INIS)

    Rawool-Sullivan, Mohini; Bounds, John Alan; Brumby, Steven P.; Prasad, Lakshman; Sullivan, John P.

    2012-01-01

    This is the final report of the project titled, 'Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes,' PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). Human analysts begin analyzing a spectrum based on features in the spectrum - lines and shapes that are present in a given spectrum. The proposed work was to carry out a feasibility study that will pick out all gamma ray peaks and other features such as Compton edges, bremsstrahlung, presence/absence of shielding and presence of neutrons and escape peaks. Ultimately success of this feasibility study will allow us to collectively explain identified features and form a realistic scenario that produced a given spectrum in the future. We wanted to develop and demonstrate machine learning algorithms that will qualitatively enhance the automated identification capabilities of portable radiological sensors that are currently being used in the field.

  8. [Algorithm of toxigenic genetically altered Vibrio cholerae El Tor biovar strain identification].

    Science.gov (United States)

    Smirnova, N I; Agafonov, D A; Zadnova, S P; Cherkasov, A V; Kutyrev, V V

    2014-01-01

    Development of an algorithm of genetically altered Vibrio cholerae biovar El Tor strai identification that ensures determination of serogroup, serovar and biovar of the studied isolate based on pheno- and genotypic properties, detection of genetically altered cholera El Tor causative agents, their differentiation by epidemic potential as well as evaluation of variability of key pathogenicity genes. Complex analysis of 28 natural V. cholerae strains was carried out by using traditional microbiological methods, PCR and fragmentary sequencing. An algorithm of toxigenic genetically altered V. cholerae biovar El Tor strain identification was developed that includes 4 stages: determination of serogroup, serovar and biovar based on phenotypic properties, confirmation of serogroup and biovar based on molecular-genetic properties determination of strains as genetically altered, differentiation of genetically altered strains by their epidemic potential and detection of ctxB and tcpA key pathogenicity gene polymorphism. The algorithm is based on the use of traditional microbiological methods, PCR and sequencing of gene fragments. The use of the developed algorithm will increase the effectiveness of detection of genetically altered variants of the cholera El Tor causative agent, their differentiation by epidemic potential and will ensure establishment of polymorphism of genes that code key pathogenicity factors for determination of origins of the strains and possible routes of introduction of the infection.

  9. An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

    Science.gov (United States)

    Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

    2015-11-01

    This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

    Directory of Open Access Journals (Sweden)

    Guang-zhou Chen

    2015-01-01

    Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.

  11. Implementation of an algorithm for cylindrical object identification using range data

    Science.gov (United States)

    Bozeman, Sylvia T.; Martin, Benjamin J.

    1989-01-01

    One of the problems in 3-D object identification and localization is addressed. In robotic and navigation applications the vision system must be able to distinguish cylindrical or spherical objects as well as those of other geometric shapes. An algorithm was developed to identify cylindrical objects in an image when range data is used. The algorithm incorporates the Hough transform for line detection using edge points which emerge from a Sobel mask. Slices of the data are examined to locate arcs of circles using the normal equations of an over-determined linear system. Current efforts are devoted to testing the computer implementation of the algorithm. Refinements are expected to continue in order to accommodate cylinders in various positions. A technique is sought which is robust in the presence of noise and partial occlusions.

  12. Parameter identification of piezoelectric hysteresis model based on improved artificial bee colony algorithm

    Science.gov (United States)

    Wang, Geng; Zhou, Kexin; Zhang, Yeming

    2018-04-01

    The widely used Bouc-Wen hysteresis model can be utilized to accurately simulate the voltage-displacement curves of piezoelectric actuators. In order to identify the unknown parameters of the Bouc-Wen model, an improved artificial bee colony (IABC) algorithm is proposed in this paper. A guiding strategy for searching the current optimal position of the food source is proposed in the method, which can help balance the local search ability and global exploitation capability. And the formula for the scout bees to search for the food source is modified to increase the convergence speed. Some experiments were conducted to verify the effectiveness of the IABC algorithm. The results show that the identified hysteresis model agreed well with the actual actuator response. Moreover, the identification results were compared with the standard particle swarm optimization (PSO) method, and it can be seen that the search performance in convergence rate of the IABC algorithm is better than that of the standard PSO method.

  13. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.

    Science.gov (United States)

    Lai, Fu-Jou; Chang, Hong-Tsun; Huang, Yueh-Min; Wu, Wei-Sheng

    2014-01-01

    Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to measure the performance of new

  14. Automatic vertebral identification using surface-based registration

    Science.gov (United States)

    Herring, Jeannette L.; Dawant, Benoit M.

    2000-06-01

    This work introduces an enhancement to currently existing methods of intra-operative vertebral registration by allowing the portion of the spinal column surface that correctly matches a set of physical vertebral points to be automatically selected from several possible choices. Automatic selection is made possible by the shape variations that exist among lumbar vertebrae. In our experiments, we register vertebral points representing physical space to spinal column surfaces extracted from computed tomography images. The vertebral points are taken from the posterior elements of a single vertebra to represent the region of surgical interest. The surface is extracted using an improved version of the fully automatic marching cubes algorithm, which results in a triangulated surface that contains multiple vertebrae. We find the correct portion of the surface by registering the set of physical points to multiple surface areas, including all vertebral surfaces that potentially match the physical point set. We then compute the standard deviation of the surface error for the set of points registered to each vertebral surface that is a possible match, and the registration that corresponds to the lowest standard deviation designates the correct match. We have performed our current experiments on two plastic spine phantoms and one patient.

  15. Algorithms

    Indian Academy of Sciences (India)

    polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

  16. Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

    Directory of Open Access Journals (Sweden)

    Xiuchun Ge

    2010-07-01

    Full Text Available Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species.We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity.The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

  17. Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

    Science.gov (United States)

    Ge, Xiuchun; Kitten, Todd; Munro, Cindy L; Conrad, Daniel H; Xu, Ping

    2010-07-26

    Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species. We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity. The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

  18. Identification of Forested Landslides Using LiDar Data, Object-based Image Analysis, and Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Xianju Li

    2015-07-01

    Full Text Available For identification of forested landslides, most studies focus on knowledge-based and pixel-based analysis (PBA of LiDar data, while few studies have examined (semi- automated methods and object-based image analysis (OBIA. Moreover, most of them are focused on soil-covered areas with gentle hillslopes. In bedrock-covered mountains with steep and rugged terrain, it is so difficult to identify landslides that there is currently no research on whether combining semi-automated methods and OBIA with only LiDar derivatives could be more effective. In this study, a semi-automatic object-based landslide identification approach was developed and implemented in a forested area, the Three Gorges of China. Comparisons of OBIA and PBA, two different machine learning algorithms and their respective sensitivity to feature selection (FS, were first investigated. Based on the classification result, the landslide inventory was finally obtained according to (1 inclusion of holes encircled by the landslide body; (2 removal of isolated segments, and (3 delineation of closed envelope curves for landslide objects by manual digitizing operation. The proposed method achieved the following: (1 the filter features of surface roughness were first applied for calculating object features, and proved useful; (2 FS improved classification accuracy and reduced features; (3 the random forest algorithm achieved higher accuracy and was less sensitive to FS than a support vector machine; (4 compared to PBA, OBIA was more sensitive to FS, remarkably reduced computing time, and depicted more contiguous terrain segments; (5 based on the classification result with an overall accuracy of 89.11% ± 0.03%, the obtained inventory map was consistent with the referenced landslide inventory map, with a position mismatch value of 9%. The outlined approach would be helpful for forested landslide identification in steep and rugged terrain.

  19. Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

    Science.gov (United States)

    Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

    2017-01-01

    Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance. PMID:28874909

  20. Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms.

    Science.gov (United States)

    Liu, Rensong; Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

    2017-01-01

    Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K -nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance.

  1. Surface roughness optimization in machining of AZ31 magnesium alloy using ABC algorithm

    Directory of Open Access Journals (Sweden)

    Abhijith

    2018-01-01

    Full Text Available Magnesium alloys serve as excellent substitutes for materials traditionally used for engine block heads in automobiles and gear housings in aircraft industries. AZ31 is a magnesium alloy finds its applications in orthopedic implants and cardiovascular stents. Surface roughness is an important parameter in the present manufacturing sector. In this work optimization techniques namely firefly algorithm (FA, particle swarm optimization (PSO and artificial bee colony algorithm (ABC which are based on swarm intelligence techniques, have been implemented to optimize the machining parameters namely cutting speed, feed rate and depth of cut in order to achieve minimum surface roughness. The parameter Ra has been considered for evaluating the surface roughness. Comparing the performance of ABC algorithm with FA and PSO algorithm, which is a widely used optimization algorithm in machining studies, the results conclude that ABC produces better optimization when compared to FA and PSO for optimizing surface roughness of AZ 31.

  2. Detection of surface algal blooms using the newly developed algorithm surface algal bloom index (SABI)

    Science.gov (United States)

    Alawadi, Fahad

    2010-10-01

    Quantifying ocean colour properties has evolved over the past two decades from being able to merely detect their biological activity to the ability to estimate chlorophyll concentration using optical satellite sensors like MODIS and MERIS. The production of chlorophyll spatial distribution maps is a good indicator of plankton biomass (primary production) and is useful for the tracing of oceanographic currents, jets and blooms, including harmful algal blooms (HABs). Depending on the type of HABs involved and the environmental conditions, if their concentration rises above a critical threshold, it can impact the flora and fauna of the aquatic habitat through the introduction of the so called "red tide" phenomenon. The estimation of chlorophyll concentration is derived from quantifying the spectral relationship between the blue and the green bands reflected from the water column. This spectral relationship is employed in the standard ocean colour chlorophyll-a (Chlor-a) product, but is incapable of detecting certain macro-algal species that float near to or at the water surface in the form of dense filaments or mats. The ability to accurately identify algal formations that sometimes appear as oil spill look-alikes in satellite imagery, contributes towards the reduction of false-positive incidents arising from oil spill monitoring operations. Such algal formations that occur in relatively high concentrations may experience, as in land vegetation, what is known as the "red-edge" effect. This phenomena occurs at the highest reflectance slope between the maximum absorption in the red due to the surrounding ocean water and the maximum reflectance in the infra-red due to the photosynthetic pigments present in the surface algae. A new algorithm termed the surface algal bloom index (SABI), has been proposed to delineate the spatial distributions of floating micro-algal species like for example cyanobacteria or exposed inter-tidal vegetation like seagrass. This algorithm was

  3. Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

    Science.gov (United States)

    An, Lu; Guo, Baolong

    2018-03-01

    Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

  4. An algorithm and program for finding sequence specific oligo-nucleotide probes for species identification

    Directory of Open Access Journals (Sweden)

    Tautz Diethard

    2002-03-01

    Full Text Available Abstract Background The identification of species or species groups with specific oligo-nucleotides as molecular signatures is becoming increasingly popular for bacterial samples. However, it shows also great promise for other small organisms that are taxonomically difficult to tract. Results We have devised here an algorithm that aims to find the optimal probes for any given set of sequences. The program requires only a crude alignment of these sequences as input and is optimized for performance to deal also with very large datasets. The algorithm is designed such that the position of mismatches in the probes influences the selection and makes provision of single nucleotide outloops. Program implementations are available for Linux and Windows.

  5. Partial fingerprint identification algorithm based on the modified generalized Hough transform on mobile device

    Science.gov (United States)

    Qin, Jin; Tang, Siqi; Han, Congying; Guo, Tiande

    2018-04-01

    Partial fingerprint identification technology which is mainly used in device with small sensor area like cellphone, U disk and computer, has taken more attention in recent years with its unique advantages. However, owing to the lack of sufficient minutiae points, the conventional method do not perform well in the above situation. We propose a new fingerprint matching technique which utilizes ridges as features to deal with partial fingerprint images and combines the modified generalized Hough transform and scoring strategy based on machine learning. The algorithm can effectively meet the real-time and space-saving requirements of the resource constrained devices. Experiments on in-house database indicate that the proposed algorithm have an excellent performance.

  6. Algorithm for personal identification in distance learning system based on registration of keyboard rhythm

    Science.gov (United States)

    Nikitin, P. V.; Savinov, A. N.; Bazhenov, R. I.; Sivandaev, S. V.

    2018-05-01

    The article describes the method of identifying a person in distance learning systems based on a keyboard rhythm. An algorithm for the organization of access control is proposed, which implements authentication, identification and verification of a person using the keyboard rhythm. Authentication methods based on biometric personal parameters, including those based on the keyboard rhythm, due to the inexistence of biometric characteristics without a particular person, are able to provide an advanced accuracy and inability to refuse authorship and convenience for operators of automated systems, in comparison with other methods of conformity checking. Methods of permanent hidden keyboard monitoring allow detecting the substitution of a student and blocking the key system.

  7. Method of transient identification based on a possibilistic approach, optimized by genetic algorithm

    International Nuclear Information System (INIS)

    Almeida, Jose Carlos Soares de

    2001-02-01

    This work develops a method for transient identification based on a possible approach, optimized by Genetic Algorithm to optimize the number of the centroids of the classes that represent the transients. The basic idea of the proposed method is to optimize the partition of the search space, generating subsets in the classes within a partition, defined as subclasses, whose centroids are able to distinguish the classes with the maximum correct classifications. The interpretation of the subclasses as fuzzy sets and the possible approach provided a heuristic to establish influence zones of the centroids, allowing to achieve the 'don't know' answer for unknown transients, that is, outside the training set. (author)

  8. Adaptive Algorithm For Identification Of The Environment Parameters In Contact Tasks

    International Nuclear Information System (INIS)

    Tuneski, Atanasko; Babunski, Darko

    2003-01-01

    An adaptive algorithm for identification of the unknown parameters of the dynamic environment in contact tasks is proposed in this paper using the augmented least square estimation method. An approximate environment digital simulator for the continuous environment dynamics is derived, i.e. a discrete transfer function which has the approximately the same characteristics as the continuous environment dynamics is found. For solving this task a method named hold equivalence is used. The general model of the environment dynamics is given and the case when the environment dynamics is represented by second order models with parameter uncertainties is considered. (Author)

  9. Adaptive Algorithm For Identification Of The Environment Parameters In Contact Tasks

    Energy Technology Data Exchange (ETDEWEB)

    Tuneski, Atanasko; Babunski, Darko [Faculty of Mechanical Engineering, ' St. Cyril and Methodius' University, Skopje (Macedonia, The Former Yugoslav Republic of)

    2003-07-01

    An adaptive algorithm for identification of the unknown parameters of the dynamic environment in contact tasks is proposed in this paper using the augmented least square estimation method. An approximate environment digital simulator for the continuous environment dynamics is derived, i.e. a discrete transfer function which has the approximately the same characteristics as the continuous environment dynamics is found. For solving this task a method named hold equivalence is used. The general model of the environment dynamics is given and the case when the environment dynamics is represented by second order models with parameter uncertainties is considered. (Author)

  10. Computerized Dental Comparison: A Critical Review of Dental Coding and Ranking Algorithms Used in Victim Identification.

    Science.gov (United States)

    Adams, Bradley J; Aschheim, Kenneth W

    2016-01-01

    Comparison of antemortem and postmortem dental records is a leading method of victim identification, especially for incidents involving a large number of decedents. This process may be expedited with computer software that provides a ranked list of best possible matches. This study provides a comparison of the most commonly used conventional coding and sorting algorithms used in the United States (WinID3) with a simplified coding format that utilizes an optimized sorting algorithm. The simplified system consists of seven basic codes and utilizes an optimized algorithm based largely on the percentage of matches. To perform this research, a large reference database of approximately 50,000 antemortem and postmortem records was created. For most disaster scenarios, the proposed simplified codes, paired with the optimized algorithm, performed better than WinID3 which uses more complex codes. The detailed coding system does show better performance with extremely large numbers of records and/or significant body fragmentation. © 2015 American Academy of Forensic Sciences.

  11. MIDAS: a database-searching algorithm for metabolite identification in metabolomics.

    Science.gov (United States)

    Wang, Yingfeng; Kora, Guruprasad; Bowen, Benjamin P; Pan, Chongle

    2014-10-07

    A database searching approach can be used for metabolite identification in metabolomics by matching measured tandem mass spectra (MS/MS) against the predicted fragments of metabolites in a database. Here, we present the open-source MIDAS algorithm (Metabolite Identification via Database Searching). To evaluate a metabolite-spectrum match (MSM), MIDAS first enumerates possible fragments from a metabolite by systematic bond dissociation, then calculates the plausibility of the fragments based on their fragmentation pathways, and finally scores the MSM to assess how well the experimental MS/MS spectrum from collision-induced dissociation (CID) is explained by the metabolite's predicted CID MS/MS spectrum. MIDAS was designed to search high-resolution tandem mass spectra acquired on time-of-flight or Orbitrap mass spectrometer against a metabolite database in an automated and high-throughput manner. The accuracy of metabolite identification by MIDAS was benchmarked using four sets of standard tandem mass spectra from MassBank. On average, for 77% of original spectra and 84% of composite spectra, MIDAS correctly ranked the true compounds as the first MSMs out of all MetaCyc metabolites as decoys. MIDAS correctly identified 46% more original spectra and 59% more composite spectra at the first MSMs than an existing database-searching algorithm, MetFrag. MIDAS was showcased by searching a published real-world measurement of a metabolome from Synechococcus sp. PCC 7002 against the MetaCyc metabolite database. MIDAS identified many metabolites missed in the previous study. MIDAS identifications should be considered only as candidate metabolites, which need to be confirmed using standard compounds. To facilitate manual validation, MIDAS provides annotated spectra for MSMs and labels observed mass spectral peaks with predicted fragments. The database searching and manual validation can be performed online at http://midas.omicsbio.org.

  12. Identification of alternative splice variants in Aspergillus flavus through comparison of multiple tandem MS search algorithms

    Directory of Open Access Journals (Sweden)

    Chang Kung-Yen

    2011-07-01

    Full Text Available Abstract Background Database searching is the most frequently used approach for automated peptide assignment and protein inference of tandem mass spectra. The results, however, depend on the sequences in target databases and on search algorithms. Recently by using an alternative splicing database, we identified more proteins than with the annotated proteins in Aspergillus flavus. In this study, we aimed at finding a greater number of eligible splice variants based on newly available transcript sequences and the latest genome annotation. The improved database was then used to compare four search algorithms: Mascot, OMSSA, X! Tandem, and InsPecT. Results The updated alternative splicing database predicted 15833 putative protein variants, 61% more than the previous results. There was transcript evidence for 50% of the updated genes compared to the previous 35% coverage. Database searches were conducted using the same set of spectral data, search parameters, and protein database but with different algorithms. The false discovery rates of the peptide-spectrum matches were estimated Conclusions We were able to detect dozens of new peptides using the improved alternative splicing database with the recently updated annotation of the A. flavus genome. Unlike the identifications of the peptides and the RefSeq proteins, large variations existed between the putative splice variants identified by different algorithms. 12 candidates of putative isoforms were reported based on the consensus peptide-spectrum matches. This suggests that applications of multiple search engines effectively reduced the possible false positive results and validated the protein identifications from tandem mass spectra using an alternative splicing database.

  13. Parameters identification of photovoltaic models using an improved JAYA optimization algorithm

    International Nuclear Information System (INIS)

    Yu, Kunjie; Liang, J.J.; Qu, B.Y.; Chen, Xu; Wang, Heshan

    2017-01-01

    Highlights: • IJAYA algorithm is proposed to identify the PV model parameters efficiently. • A self-adaptive weight is introduced to purposefully adjust the search process. • Experience-based learning strategy is developed to enhance the population diversity. • Chaotic learning method is proposed to refine the quality of the best solution. • IJAYA features the superior performance in identifying parameters of PV models. - Abstract: Parameters identification of photovoltaic (PV) models based on measured current-voltage characteristic curves is significant for the simulation, evaluation, and control of PV systems. To accurately and reliably identify the parameters of different PV models, an improved JAYA (IJAYA) optimization algorithm is proposed in the paper. In IJAYA, a self-adaptive weight is introduced to adjust the tendency of approaching the best solution and avoiding the worst solution at different search stages, which enables the algorithm to approach the promising area at the early stage and implement the local search at the later stage. Furthermore, an experience-based learning strategy is developed and employed randomly to maintain the population diversity and enhance the exploration ability. A chaotic elite learning method is proposed to refine the quality of the best solution in each generation. The proposed IJAYA is used to solve the parameters identification problems of different PV models, i.e., single diode, double diode, and PV module. Comprehensive experiment results and analyses indicate that IJAYA can obtain a highly competitive performance compared with other state-of-the-state algorithms, especially in terms of accuracy and reliability.

  14. Identification of individual features in areal surface topography data by means of template matching and the ring projection transform

    International Nuclear Information System (INIS)

    Senin, Nicola; Moretti, Michele; Blunt, Liam A

    2014-01-01

    Starting from areal surface topography data as provided by current commercial three-dimensional (3D) profilometers and 3D digital microscopes, this work investigates the problem of automatically identifying and extracting functionally relevant, individual features within the acquisition area. Feature identification is achieved by adopting an original template-matching algorithmic procedure, based on applying the ring projection transform in combination with a parametric template. The proposed algorithmic procedure addresses in particular template-matching scenarios where significant variability may be associated with the features to be compared to the reference template. The algorithm is applied to a test case involving the characterization of the surface texture of a superabrasive polishing tool used in hard-disk manufacturing. (paper)

  15. A new surface fractal dimension for displacement mode shape-based damage identification of plate-type structures

    Science.gov (United States)

    Shi, Binkai; Qiao, Pizhong

    2018-03-01

    Vibration-based nondestructive testing is an area of growing interest and worthy of exploring new and innovative approaches. The displacement mode shape is often chosen to identify damage due to its local detailed characteristic and less sensitivity to surrounding noise. Requirement for baseline mode shape in most vibration-based damage identification limits application of such a strategy. In this study, a new surface fractal dimension called edge perimeter dimension (EPD) is formulated, from which an EPD-based window dimension locus (EPD-WDL) algorithm for irregularity or damage identification of plate-type structures is established. An analytical notch-type damage model of simply-supported plates is proposed to evaluate notch effect on plate vibration performance; while a sub-domain of notch cases with less effect is selected to investigate robustness of the proposed damage identification algorithm. Then, fundamental aspects of EPD-WDL algorithm in term of notch localization, notch quantification, and noise immunity are assessed. A mathematical solution called isomorphism is implemented to remove false peaks caused by inflexions of mode shapes when applying the EPD-WDL algorithm to higher mode shapes. The effectiveness and practicability of the EPD-WDL algorithm are demonstrated by an experimental procedure on damage identification of an artificially-induced notched aluminum cantilever plate using a measurement system of piezoelectric lead-zirconate (PZT) actuator and scanning laser Doppler vibrometer (SLDV). As demonstrated in both the analytical and experimental evaluations, the new surface fractal dimension technique developed is capable of effectively identifying damage in plate-type structures.

  16. Identification of surface proteins in Enterococcus faecalis V583

    Directory of Open Access Journals (Sweden)

    Eijsink Vincent GH

    2011-03-01

    Full Text Available Abstract Background Surface proteins are a key to a deeper understanding of the behaviour of Gram-positive bacteria interacting with the human gastro-intestinal tract. Such proteins contribute to cell wall synthesis and maintenance and are important for interactions between the bacterial cell and the human host. Since they are exposed and may play roles in pathogenicity, surface proteins are interesting targets for drug design. Results Using methods based on proteolytic "shaving" of bacterial cells and subsequent mass spectrometry-based protein identification, we have identified surface-located proteins in Enterococcus faecalis V583. In total 69 unique proteins were identified, few of which have been identified and characterized previously. 33 of these proteins are predicted to be cytoplasmic, whereas the other 36 are predicted to have surface locations (31 or to be secreted (5. Lipid-anchored proteins were the most dominant among the identified surface proteins. The seemingly most abundant surface proteins included a membrane protein with a potentially shedded extracellular sulfatase domain that could act on the sulfate groups in mucin and a lipid-anchored fumarate reductase that could contribute to generation of reactive oxygen species. Conclusions The present proteome analysis gives an experimental impression of the protein landscape on the cell surface of the pathogenic bacterium E. faecalis. The 36 identified secreted (5 and surface (31 proteins included several proteins involved in cell wall synthesis, pheromone-regulated processes, and transport of solutes, as well as proteins with unknown function. These proteins stand out as interesting targets for further investigation of the interaction between E. faecalis and its environment.

  17. Algorithms for singularities and real structures of weak Del Pezzo surfaces

    KAUST Repository

    Lubbes, Niels

    2014-01-01

    . Wall, Real forms of smooth del Pezzo surfaces, J. Reine Angew. Math. 1987(375/376) (1987) 47-66, ISSN 0075-4102] of weak Del Pezzo surfaces from an algorithmic point of view. It is well-known that the singularities of weak Del Pezzo surfaces correspond

  18. Algorithms

    Indian Academy of Sciences (India)

    to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...

  19. Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

    Directory of Open Access Journals (Sweden)

    Ying Qu

    2015-01-01

    Full Text Available Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces, gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

  20. A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

    Science.gov (United States)

    Xia, Youshen; Kamel, Mohamed S

    2007-06-01

    Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

  1. Evaluation of sensor placement algorithms for on-orbit identification of space platforms

    Science.gov (United States)

    Glassburn, Robin S.; Smith, Suzanne Weaver

    1994-01-01

    Anticipating the construction of the international space station, on-orbit modal identification of space platforms through optimally placed accelerometers is an area of recent activity. Unwanted vibrations in the platform could affect the results of experiments which are planned. Therefore, it is important that sensors (accelerometers) be strategically placed to identify the amount and extent of these unwanted vibrations, and to validate the mathematical models used to predict the loads and dynamic response. Due to cost, installation, and data management issues, only a limited number of sensors will be available for placement. This work evaluates and compares four representative sensor placement algorithms for modal identification. Most of the sensor placement work to date has employed only numerical simulations for comparison. This work uses experimental data from a fully-instrumented truss structure which was one of a series of structures designed for research in dynamic scale model ground testing of large space structures at NASA Langley Research Center. Results from this comparison show that for this cantilevered structure, the algorithm based on Guyan reduction is rated slightly better than that based on Effective Independence.

  2. An algorithm for three-dimensional Monte-Carlo simulation of charge distribution at biofunctionalized surfaces

    KAUST Repository

    Bulyha, Alena; Heitzinger, Clemens

    2011-01-01

    In this work, a Monte-Carlo algorithm in the constant-voltage ensemble for the calculation of 3d charge concentrations at charged surfaces functionalized with biomolecules is presented. The motivation for this work is the theoretical understanding

  3. An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data.

    Science.gov (United States)

    Ping, Bo; Su, Fenzhen; Meng, Yunshan

    2016-01-01

    In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time.

  4. Multi-Scale Parameter Identification of Lithium-Ion Battery Electric Models Using a PSO-LM Algorithm

    Directory of Open Access Journals (Sweden)

    Wen-Jing Shen

    2017-03-01

    Full Text Available This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB electric model by using a combination of particle swarm optimization (PSO and Levenberg-Marquardt (LM algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD of the positive and negative electrodes in the LIB electric model. The model parameters are difficult to determine in the simulation due to the nonlinear complexity of the model. In the proposed identification algorithm, PSO is used for the coarse-scale parameter identification and the LM algorithm is applied for the fine-scale parameter identification. The experiment results show that the multi-scale identification not only improves the convergence rate and effectively escapes from the stagnation of PSO, but also overcomes the local minimum entrapment drawback of the LM algorithm. The terminal voltage curves from the PDD model with the identified parameter values are in good agreement with those from the experiments at different discharge/charge rates.

  5. Muon identification algorithms in ATLAS Poster for EPS-HEP 2009

    CERN Document Server

    Resende, B; The ATLAS collaboration

    2009-01-01

    In the midst of the intense activity that will arise from the proton-proton collisions at the LHC, muons will be very useful to spot rare events of interest. The good resolution expected for their momentum measurement shall also make them powerful tools in event reconstruction. Muon identification will thus be a crucial issue in the ATLAS experiment at the LHC. Their charged tracks can be reconstructed in the external spectrometer only, but the combination of such "stand-alone" tracks with tracks from the inner detector shall increase the precision and reliablilty of the reconstructed muon. This is particularly true in the lower part of the pT spectrum, where the inner detector is more performant. We will present here the various strategies for combined muon identification in the ATLAS experiment. The main algorithms, called Staco and Muid, perform the combination of existing tracks in the inner detector and in the muon spectrometer, allowing the best identification of muon tracks. Their efficiency is complet...

  6. A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

    Science.gov (United States)

    Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

    2013-03-01

    Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

  7. GPR identification of voids inside concrete based on the support vector machine algorithm

    International Nuclear Information System (INIS)

    Xie, Xiongyao; Li, Pan; Qin, Hui; Liu, Lanbo; Nobes, David C

    2013-01-01

    Voids inside reinforced concrete, which affect structural safety, are identified from ground penetrating radar (GPR) images using a completely automatic method based on the support vector machine (SVM) algorithm. The entire process can be characterized into four steps: (1) the original SVM model is built by training synthetic GPR data generated by finite difference time domain simulation and after data preprocessing, segmentation and feature extraction. (2) The classification accuracy of different kernel functions is compared with the cross-validation method and the penalty factor (c) of the SVM and the coefficient (σ2) of kernel functions are optimized by using the grid algorithm and the genetic algorithm. (3) To test the success of classification, this model is then verified and validated by applying it to another set of synthetic GPR data. The result shows a high success rate for classification. (4) This original classifier model is finally applied to a set of real GPR data to identify and classify voids. The result is less than ideal when compared with its application to synthetic data before the original model is improved. In general, this study shows that the SVM exhibits promising performance in the GPR identification of voids inside reinforced concrete. Nevertheless, the recognition of shape and distribution of voids may need further improvement. (paper)

  8. Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm

    Directory of Open Access Journals (Sweden)

    Shui-Hua Wang

    2018-04-01

    Full Text Available Aim: Currently, identifying multiple sclerosis (MS by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, a specificity of 97.39 ± 0.65%, and an accuracy of 97.39 ± 0.59%. Conclusions: We validated by experiments that the proposed improved Jaya performs better than plain Jaya algorithm and other latest bioinspired algorithms in terms of classification performance and training speed. In addition, our method is superior to four state-of-the-art MS identification approaches.

  9. Fault Identification Algorithm Based on Zone-Division Wide Area Protection System

    Directory of Open Access Journals (Sweden)

    Xiaojun Liu

    2014-04-01

    Full Text Available As the power grid becomes more magnified and complicated, wide-area protection system in the practical engineering application is more and more restricted by the communication level. Based on the concept of limitedness of wide-area protection system, the grid with complex structure is divided orderly in this paper, and fault identification and protection action are executed in each divided zone to reduce the pressure of the communication system. In protection zone, a new wide-area protection algorithm based on positive sequence fault components directional comparison principle is proposed. The special associated intelligent electronic devices (IEDs zones which contain buses and transmission lines are created according to the installation location of the IEDs. When a fault occurs, with the help of the fault information collecting and sharing from associated zones with the fault discrimination principle defined in this paper, the IEDs can identify the fault location and remove the fault according to the predetermined action strategy. The algorithm will not be impacted by the load changes and transition resistance and also has good adaptability in open phase running power system. It can be used as a main protection, and it also can be taken into account for the back-up protection function. The results of cases study show that, the division method of the wide-area protection system and the proposed algorithm are effective.

  10. From Massively Parallel Algorithms and Fluctuating Time Horizons to Nonequilibrium Surface Growth

    International Nuclear Information System (INIS)

    Korniss, G.; Toroczkai, Z.; Novotny, M. A.; Rikvold, P. A.

    2000-01-01

    We study the asymptotic scaling properties of a massively parallel algorithm for discrete-event simulations where the discrete events are Poisson arrivals. The evolution of the simulated time horizon is analogous to a nonequilibrium surface. Monte Carlo simulations and a coarse-grained approximation indicate that the macroscopic landscape in the steady state is governed by the Edwards-Wilkinson Hamiltonian. Since the efficiency of the algorithm corresponds to the density of local minima in the associated surface, our results imply that the algorithm is asymptotically scalable. (c) 2000 The American Physical Society

  11. Braking distance algorithm for autonomous cars using road surface recognition

    Science.gov (United States)

    Kavitha, C.; Ashok, B.; Nanthagopal, K.; Desai, Rohan; Rastogi, Nisha; Shetty, Siddhanth

    2017-11-01

    India is yet to accept semi/fully - autonomous cars and one of the reasons, was loss of control on bad roads. For a better handling on these roads we require advanced braking and that can be done by adapting electronics into the conventional type of braking. In Recent years, the automation in braking system led us to various benefits like traction control system, anti-lock braking system etc. This research work describes and experiments the method for recognizing road surface profile and calculating braking distance. An ultra-sonic surface recognition sensor, mounted underneath the car will send a high frequency wave on to the road surface, which is received by a receiver with in the sensor, it calculates the time taken for the wave to rebound and thus calculates the distance from the point where sensor is mounted. A displacement graph will be plotted based on the output of the sensor. A relationship can be derived between the displacement plot and roughness index through which the friction coefficient can be derived in Matlab for continuous calculation throughout the distance travelled. Since it is a non-contact type of profiling, it is non-destructive. The friction coefficient values received in real-time is used to calculate optimum braking distance. This system, when installed on normal cars can also be used to create a database of road surfaces, especially in cities, which can be shared with other cars. This will help in navigation as well as making the cars more efficient.

  12. An algorithm to retrieve Land Surface Temperature using Landsat-8 ...

    African Journals Online (AJOL)

    Ayodeji Ogunode;Mulemwa Akombelwa

    The results show temperature variation over a long period of time can be ... Remote sensing of LST using infrared radiation gives the average surface temperature of the scene ... advantage over previous Landsat series. ..... Li, F., Jackson, T. J., Kustas, W. P., Schmugge, T. J., French, A. N., Cosh, M. H. & Bindlish, R. 2004.

  13. Validation of ICD-9-CM coding algorithm for improved identification of hypoglycemia visits

    Directory of Open Access Journals (Sweden)

    Lieberman Rebecca M

    2008-04-01

    Full Text Available Abstract Background Accurate identification of hypoglycemia cases by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM codes will help to describe epidemiology, monitor trends, and propose interventions for this important complication in patients with diabetes. Prior hypoglycemia studies utilized incomplete search strategies and may be methodologically flawed. We sought to validate a new ICD-9-CM coding algorithm for accurate identification of hypoglycemia visits. Methods This was a multicenter, retrospective cohort study using a structured medical record review at three academic emergency departments from July 1, 2005 to June 30, 2006. We prospectively derived a coding algorithm to identify hypoglycemia visits using ICD-9-CM codes (250.3, 250.8, 251.0, 251.1, 251.2, 270.3, 775.0, 775.6, and 962.3. We confirmed hypoglycemia cases by chart review identified by candidate ICD-9-CM codes during the study period. The case definition for hypoglycemia was documented blood glucose 3.9 mmol/l or emergency physician charted diagnosis of hypoglycemia. We evaluated individual components and calculated the positive predictive value. Results We reviewed 636 charts identified by the candidate ICD-9-CM codes and confirmed 436 (64% cases of hypoglycemia by chart review. Diabetes with other specified manifestations (250.8, often excluded in prior hypoglycemia analyses, identified 83% of hypoglycemia visits, and unspecified hypoglycemia (251.2 identified 13% of hypoglycemia visits. The absence of any predetermined co-diagnosis codes improved the positive predictive value of code 250.8 from 62% to 92%, while excluding only 10 (2% true hypoglycemia visits. Although prior analyses included only the first-listed ICD-9 code, more than one-quarter of identified hypoglycemia visits were outside this primary diagnosis field. Overall, the proposed algorithm had 89% positive predictive value (95% confidence interval, 86–92 for

  14. Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia

    Science.gov (United States)

    Bunai, Tasya; Rokhmatuloh; Wibowo, Adi

    2018-05-01

    In this paper, two methods to retrieve the Land Surface Temperature (LST) from thermal infrared data supplied by band 10 and 11 of the Thermal Infrared Sensor (TIRS) onboard the Landsat 8 is compared. The first is mono window algorithm developed by Qin et al. and the second is split window algorithm by Rozenstein et al. The purpose of this study is to perform the spatial distribution of land surface temperature, as well as to determine more accurate algorithm for retrieving land surface temperature by calculated root mean square error (RMSE). Finally, we present comparison the spatial distribution of land surface temperature by both of algorithm, and more accurate algorithm is split window algorithm refers to the root mean square error (RMSE) is 7.69° C.

  15. An Algorithm for Online Inertia Identification and Load Torque Observation via Adaptive Kalman Observer-Recursive Least Squares

    Directory of Open Access Journals (Sweden)

    Ming Yang

    2018-03-01

    Full Text Available In this paper, an on-line parameter identification algorithm to iteratively compute the numerical values of inertia and load torque is proposed. Since inertia and load torque are strongly coupled variables due to the degenerate-rank problem, it is hard to estimate relatively accurate values for them in the cases such as when load torque variation presents or one cannot obtain a relatively accurate priori knowledge of inertia. This paper eliminates this problem and realizes ideal online inertia identification regardless of load condition and initial error. The algorithm in this paper integrates a full-order Kalman Observer and Recursive Least Squares, and introduces adaptive controllers to enhance the robustness. It has a better performance when iteratively computing load torque and moment of inertia. Theoretical sensitivity analysis of the proposed algorithm is conducted. Compared to traditional methods, the validity of the proposed algorithm is proved by simulation and experiment results.

  16. WH-EA: An Evolutionary Algorithm for Wiener-Hammerstein System Identification

    Directory of Open Access Journals (Sweden)

    J. Zambrano

    2018-01-01

    Full Text Available Current methods to identify Wiener-Hammerstein systems using Best Linear Approximation (BLA involve at least two steps. First, BLA is divided into obtaining front and back linear dynamics of the Wiener-Hammerstein model. Second, a refitting procedure of all parameters is carried out to reduce modelling errors. In this paper, a novel approach to identify Wiener-Hammerstein systems in a single step is proposed. This approach is based on a customized evolutionary algorithm (WH-EA able to look for the best BLA split, capturing at the same time the process static nonlinearity with high precision. Furthermore, to correct possible errors in BLA estimation, the locations of poles and zeros are subtly modified within an adequate search space to allow a fine-tuning of the model. The performance of the proposed approach is analysed by using a demonstration example and a nonlinear system identification benchmark.

  17. A MUSIC-Based Algorithm for Blind User Identification in Multiuser DS-CDMA

    Directory of Open Access Journals (Sweden)

    M. Reza Soleymani

    2005-04-01

    Full Text Available A blind scheme based on multiple-signal classification (MUSIC algorithm for user identification in a synchronous multiuser code-division multiple-access (CDMA system is suggested. The scheme is blind in the sense that it does not require prior knowledge of the spreading codes. Spreading codes and users' power are acquired by the scheme. Eigenvalue decomposition (EVD is performed on the received signal, and then all the valid possible signature sequences are projected onto the subspaces. However, as a result of this process, some false solutions are also produced and the ambiguity seems unresolvable. Our approach is to apply a transformation derived from the results of the subspace decomposition on the received signal and then to inspect their statistics. It is shown that the second-order statistics of the transformed signal provides a reliable means for removing the false solutions.

  18. Direct instrumental identification of catalytically active surface sites

    Science.gov (United States)

    Pfisterer, Jonas H. K.; Liang, Yunchang; Schneider, Oliver; Bandarenka, Aliaksandr S.

    2017-09-01

    The activity of heterogeneous catalysts—which are involved in some 80 per cent of processes in the chemical and energy industries—is determined by the electronic structure of specific surface sites that offer optimal binding of reaction intermediates. Directly identifying and monitoring these sites during a reaction should therefore provide insight that might aid the targeted development of heterogeneous catalysts and electrocatalysts (those that participate in electrochemical reactions) for practical applications. The invention of the scanning tunnelling microscope (STM) and the electrochemical STM promised to deliver such imaging capabilities, and both have indeed contributed greatly to our atomistic understanding of heterogeneous catalysis. But although the STM has been used to probe and initiate surface reactions, and has even enabled local measurements of reactivity in some systems, it is not generally thought to be suited to the direct identification of catalytically active surface sites under reaction conditions. Here we demonstrate, however, that common STMs can readily map the catalytic activity of surfaces with high spatial resolution: we show that by monitoring relative changes in the tunnelling current noise, active sites can be distinguished in an almost quantitative fashion according to their ability to catalyse the hydrogen-evolution reaction or the oxygen-reduction reaction. These data allow us to evaluate directly the importance and relative contribution to overall catalyst activity of different defects and sites at the boundaries between two materials. With its ability to deliver such information and its ready applicability to different systems, we anticipate that our method will aid the rational design of heterogeneous catalysts.

  19. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    Science.gov (United States)

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  20. Modified SIMPLE algorithm for the numerical analysis of incompressible flows with free surface

    International Nuclear Information System (INIS)

    Mok, Jin Ho; Hong, Chun Pyo; Lee, Jin Ho

    2005-01-01

    While the SIMPLE algorithm is most widely used for the simulations of flow phenomena that take place in the industrial equipment or the manufacturing processes, it is less adopted for the simulations of the free surface flow. Though the SIMPLE algorithm is free from the limitation of time step, the free surface behavior imposes the restriction on the time step. As a result, the explicit schemes are faster than the implicit scheme in terms of computation time when the same time step is applied to, since the implicit scheme includes the numerical method to solve the simultaneous equations in its procedure. If the computation time of SIMPLE algorithm can be reduced when it is applied to the unsteady free surface flow problems, the calculation can be carried out in the more stable way and, in the design process, the process variables can be controlled based on the more accurate data base. In this study, a modified SIMPLE algorithm is presented for the free surface flow. The broken water column problem is adopted for the validation of the modified algorithm (MoSIMPLE) and for comparison to the conventional SIMPLE algorithm

  1. Damage identification in beams by a response surface based technique

    Directory of Open Access Journals (Sweden)

    Teidj S.

    2014-01-01

    Full Text Available In this work, identification of damage in uniform homogeneous metallic beams was considered through the propagation of non dispersive elastic torsional waves. The proposed damage detection procedure consisted of the following sequence. Giving a localized torque excitation, having the form of a short half-sine pulse, the first step was calculating the transient solution of the resulting torsional wave. This torque could be generated in practice by means of asymmetric laser irradiation of the beam surface. Then, a localized defect assumed to be characterized by an abrupt reduction of beam section area with a given height and extent was placed at a known location of the beam. Next, the response in terms of transverse section rotation rate was obtained for a point situated afterwards the defect, where the sensor was positioned. This last could utilize in practice the concept of laser vibrometry. A parametric study has been conducted after that by using a full factorial design of experiments table and numerical simulations based on a finite difference characteristic scheme. This has enabled the derivation of a response surface model that was shown to represent adequately the response of the system in terms of the following factors: defect extent and severity. The final step was performing the inverse problem solution in order to identify the defect characteristics by using measurement.

  2. Technical note: Efficient online source identification algorithm for integration within a contamination event management system

    Science.gov (United States)

    Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

    2017-07-01

    Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

  3. Damage identification on spatial Timoshenko arches by means of genetic algorithms

    Science.gov (United States)

    Greco, A.; D'Urso, D.; Cannizzaro, F.; Pluchino, A.

    2018-05-01

    In this paper a procedure for the dynamic identification of damage in spatial Timoshenko arches is presented. The proposed approach is based on the calculation of an arbitrary number of exact eigen-properties of a damaged spatial arch by means of the Wittrick and Williams algorithm. The proposed damage model considers a reduction of the volume in a part of the arch, and is therefore suitable, differently than what is commonly proposed in the main part of the dedicated literature, not only for concentrated cracks but also for diffused damaged zones which may involve a loss of mass. Different damage scenarios can be taken into account with variable location, intensity and extension of the damage as well as number of damaged segments. An optimization procedure, aiming at identifying which damage configuration minimizes the difference between its eigen-properties and a set of measured modal quantities for the structure, is implemented making use of genetic algorithms. In this context, an initial random population of chromosomes, representing different damage distributions along the arch, is forced to evolve towards the fittest solution. Several applications with different, single or multiple, damaged zones and boundary conditions confirm the validity and the applicability of the proposed procedure even in presence of instrumental errors on the measured data.

  4. Lining seam elimination algorithm and surface crack detection in concrete tunnel lining

    Science.gov (United States)

    Qu, Zhong; Bai, Ling; An, Shi-Quan; Ju, Fang-Rong; Liu, Ling

    2016-11-01

    Due to the particularity of the surface of concrete tunnel lining and the diversity of detection environments such as uneven illumination, smudges, localized rock falls, water leakage, and the inherent seams of the lining structure, existing crack detection algorithms cannot detect real cracks accurately. This paper proposed an algorithm that combines lining seam elimination with the improved percolation detection algorithm based on grid cell analysis for surface crack detection in concrete tunnel lining. First, check the characteristics of pixels within the overlapping grid to remove the background noise and generate the percolation seed map (PSM). Second, cracks are detected based on the PSM by the accelerated percolation algorithm so that the fracture unit areas can be scanned and connected. Finally, the real surface cracks in concrete tunnel lining can be obtained by removing the lining seam and performing percolation denoising. Experimental results show that the proposed algorithm can accurately, quickly, and effectively detect the real surface cracks. Furthermore, it can fill the gap in the existing concrete tunnel lining surface crack detection by removing the lining seam.

  5. Algorithms

    Indian Academy of Sciences (India)

    ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

  6. The sensitivity of characteristics of cyclone activity to identification procedures in tracking algorithms

    Directory of Open Access Journals (Sweden)

    Irina Rudeva

    2014-12-01

    Full Text Available The IMILAST project (‘Intercomparison of Mid-Latitude Storm Diagnostics’ was set up to compare low-level cyclone climatologies derived from a number of objective identification algorithms. This paper is a contribution to that effort where we determine the sensitivity of three key aspects of Northern Hemisphere cyclone behaviour [namely the number of cyclones, their intensity (defined here in terms of the central pressure and their deepening rates] to specific features in the automatic cyclone identification. The sensitivity is assessed with respect to three such features which may be thought to influence the ultimate climatology produced (namely performance in areas of complicated orography, time of the detection of a cyclone, and the representation of rapidly propagating cyclones. We make use of 13 tracking methods in this analysis. We find that the filtering of cyclones in regions where the topography exceeds 1500 m can significantly change the total number of cyclones detected by a scheme, but has little impact on the cyclone intensity distribution. More dramatically, late identification of cyclones (simulated by the truncation of the first 12 hours of cyclone life cycle leads to a large reduction in cyclone numbers over the both continents and oceans (up to 80 and 40%, respectively. Finally, the potential splitting of the trajectories at times of the fastest propagation has a negligible climatological effect on geographical distribution of cyclone numbers. Overall, it has been found that the averaged deepening rates and averaged cyclone central pressure are rather insensitive to the specifics of the tracking procedure, being more sensitive to the data set used (as shown in previous studies and the geographical location of a cyclone.

  7. New Advanced Source Identification Algorithm (ASIA-NEW) for radiation monitors with plastic detectors

    Energy Technology Data Exchange (ETDEWEB)

    Stavrov, Andrei; Yamamoto, Eugene [Rapiscan Systems, Inc., 14000 Mead Street, Longmont, CO, 80504 (United States)

    2015-07-01

    Radiation Portal Monitors (RPM) with plastic detectors represent the main instruments used for primary border (customs) radiation control. RPM are widely used because they are simple, reliable, relatively inexpensive and have a high sensitivity. However, experience using the RPM in various countries has revealed the systems have some grave shortcomings. There is a dramatic decrease of the probability of detection of radioactive sources under high suppression of the natural gamma background (radiation control of heavy cargoes, containers and, especially, trains). NORM (Naturally Occurring Radioactive Material) existing in objects under control trigger the so-called 'nuisance alarms', requiring a secondary inspection for source verification. At a number of sites, the rate of such alarms is so high it significantly complicates the work of customs and border officers. This paper presents a brief description of new variant of algorithm ASIA-New (New Advanced Source Identification Algorithm), which was developed by the authors and based on some experimental test results. It also demonstrates results of different tests and the capability of a new system to overcome the shortcomings stated above. New electronics and ASIA-New enables RPM to detect radioactive sources under a high background suppression (tested at 15-30%) and to verify the detected NORM (KCl) and the artificial isotopes (Co-57, Ba-133 and other). New variant of ASIA is based on physical principles and does not require a lot of special tests to attain statistical data for its parameters. That is why this system can be easily installed into any RPM with plastic detectors. This algorithm was tested for 1,395 passages of different transports (cars, trucks and trailers) without radioactive sources. It also was tested for 4,015 passages of these transports with radioactive sources of different activity (Co-57, Ba-133, Cs-137, Co-60, Ra-226, Th-232) and these sources masked by NORM (K-40) as well

  8. Identification of astrocytoma associated genes including cell surface markers

    International Nuclear Information System (INIS)

    Boon, Kathy; Edwards, Jennifer B; Eberhart, Charles G; Riggins, Gregory J

    2004-01-01

    Despite intense effort the treatment options for the invasive astrocytic tumors are still limited to surgery and radiation therapy, with chemotherapy showing little or no increase in survival. The generation of Serial Analysis of Gene Expression (SAGE) profiles is expected to aid in the identification of astrocytoma-associated genes and highly expressed cell surface genes as molecular therapeutic targets. SAGE tag counts can be easily added to public expression databases and quickly disseminated to research efforts worldwide. We generated and analyzed the SAGE transcription profiles of 25 primary grade II, III and IV astrocytomas [1]. These profiles were produced as part of the Cancer Genome Anatomy Project's SAGE Genie [2], and were used in an in silico search for candidate therapeutic targets by comparing astrocytoma to normal brain transcription. Real-time PCR and immunohistochemistry were used for the validation of selected candidate target genes in 2 independent sets of primary tumors. A restricted set of tumor-associated genes was identified for each grade that included genes not previously associated with astrocytomas (e.g. VCAM1, SMOC1, and thymidylate synthetase), with a high percentage of cell surface genes. Two genes with available antibodies, Aquaporin 1 and Topoisomerase 2A, showed protein expression consistent with transcript level predictions. This survey of transcription in malignant and normal brain tissues reveals a small subset of human genes that are activated in malignant astrocytomas. In addition to providing insights into pathway biology, we have revealed and quantified expression for a significant portion of cell surface and extra-cellular astrocytoma genes

  9. An intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces.

    Science.gov (United States)

    Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

    2013-09-01

    Poisson disk sampling has excellent spatial and spectral properties, and plays an important role in a variety of visual computing. Although many promising algorithms have been proposed for multidimensional sampling in euclidean space, very few studies have been reported with regard to the problem of generating Poisson disks on surfaces due to the complicated nature of the surface. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. In sharp contrast to the conventional parallel approaches, our method neither partitions the given surface into small patches nor uses any spatial data structure to maintain the voids in the sampling domain. Instead, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. Our algorithm guarantees that the generated Poisson disks are uniformly and randomly distributed without bias. It is worth noting that our method is intrinsic and independent of the embedding space. This intrinsic feature allows us to generate Poisson disk patterns on arbitrary surfaces in IR(n). To our knowledge, this is the first intrinsic, parallel, and accurate algorithm for surface Poisson disk sampling. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

  10. Inverse Estimation of Surface Radiation Properties Using Repulsive Particle Swarm Optimization Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kyun Ho [Sejong University, Sejong (Korea, Republic of); Kim, Ki Wan [Agency for Defense Development, Daejeon (Korea, Republic of)

    2014-09-15

    The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface and gas radiation. In the present study, unknown radiation properties were estimated using an inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure. For efficiency, a repulsive particle swarm optimization (RPSO) algorithm, which is a relatively recent heuristic search method, was used as inverse solver. By comparing the convergence rates and accuracies with the results of a genetic algorithm (GA), the performances of the proposed RPSO algorithm as an inverse solver was verified when applied to the inverse analysis of the surface radiation problem.

  11. Inverse Estimation of Surface Radiation Properties Using Repulsive Particle Swarm Optimization Algorithm

    International Nuclear Information System (INIS)

    Lee, Kyun Ho; Kim, Ki Wan

    2014-01-01

    The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface and gas radiation. In the present study, unknown radiation properties were estimated using an inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure. For efficiency, a repulsive particle swarm optimization (RPSO) algorithm, which is a relatively recent heuristic search method, was used as inverse solver. By comparing the convergence rates and accuracies with the results of a genetic algorithm (GA), the performances of the proposed RPSO algorithm as an inverse solver was verified when applied to the inverse analysis of the surface radiation problem

  12. Research on the target coverage algorithms for 3D curved surface

    International Nuclear Information System (INIS)

    Sun, Shunyuan; Sun, Li; Chen, Shu

    2016-01-01

    To solve the target covering problems in three-dimensional space, putting forward a deployment strategies of the target points innovatively, and referencing to the differential evolution (DE) algorithm to optimize the location coordinates of the sensor nodes to realize coverage of all the target points in 3-D surface with minimal sensor nodes. Firstly, building the three-dimensional perception model of sensor nodes, and putting forward to the blind area existing in the process of the sensor nodes sensing the target points in 3-D surface innovatively, then proving the feasibility of solving the target coverage problems in 3-D surface with DE algorithm theoretically, and reflecting the fault tolerance of the algorithm.

  13. Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

    Science.gov (United States)

    Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

    2013-01-04

    Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

  14. Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

    Science.gov (United States)

    Wang, Jiao; Deng, Zhiqiang

    2017-06-01

    A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

  15. A free surface algorithm in the N3S finite element code for turbulent flows

    International Nuclear Information System (INIS)

    Nitrosso, B.; Pot, G.; Abbes, B.; Bidot, T.

    1995-08-01

    In this paper, we present a free surface algorithm which was implemented in the N3S code. Free surfaces are represented by marker particles which move through a mesh. It is assumed that the free surface is located inside each element that contains markers and surrounded by at least one element with no marker inside. The mesh is then locally adjusted in order to coincide with the free surface which is well defined by the forefront marker particles. After describing the governing equations and the N3S solving methods, we present the free surface algorithm. Results obtained for two-dimensional and three-dimensional industrial problems of mould filling are presented. (authors). 5 refs., 2 figs

  16. Algorithms for singularities and real structures of weak Del Pezzo surfaces

    KAUST Repository

    Lubbes, Niels

    2014-08-01

    In this paper, we consider the classification of singularities [P. Du Val, On isolated singularities of surfaces which do not affect the conditions of adjunction. I, II, III, Proc. Camb. Philos. Soc. 30 (1934) 453-491] and real structures [C. T. C. Wall, Real forms of smooth del Pezzo surfaces, J. Reine Angew. Math. 1987(375/376) (1987) 47-66, ISSN 0075-4102] of weak Del Pezzo surfaces from an algorithmic point of view. It is well-known that the singularities of weak Del Pezzo surfaces correspond to root subsystems. We present an algorithm which computes the classification of these root subsystems. We represent equivalence classes of root subsystems by unique labels. These labels allow us to construct examples of weak Del Pezzo surfaces with the corresponding singularity configuration. Equivalence classes of real structures of weak Del Pezzo surfaces are also represented by root subsystems. We present an algorithm which computes the classification of real structures. This leads to an alternative proof of the known classification for Del Pezzo surfaces and extends this classification to singular weak Del Pezzo surfaces. As an application we classify families of real conics on cyclides. © World Scientific Publishing Company.

  17. Network-based Type-2 Fuzzy System with Water Flow Like Algorithm for System Identification and Signal Processing

    Directory of Open Access Journals (Sweden)

    Che-Ting Kuo

    2015-02-01

    Full Text Available This paper introduces a network-based interval type-2 fuzzy inference system (NT2FIS with a dynamic solution agent algorithm water flow like algorithm (WFA, for nonlinear system identification and blind source separation (BSS problem. The NT2FIS consists of interval type-2 asymmetric fuzzy membership functions and TSK-type consequent parts to enhance the performance. The proposed scheme is optimized by a new heuristic learning algorithm, WFA, with dynamic solution agents. The proposed WFA is inspired by the natural behavior of water flow. Splitting, moving, merging, evaporation, and precipitation have all been introduced for optimization. Some modifications, including new moving strategies, such as the application of tabu searching and gradient-descent techniques, are proposed to enhance the performance of the WFA in training the NT2FIS systems. Simulation and comparison results for nonlinear system identification and blind signal separation are presented to illustrate the performance and effectiveness of the proposed approach.

  18. Algorithm for Identification Electromagnetic Parameters of an Induction Motor When Running on a Three-Phase Power Plant

    Directory of Open Access Journals (Sweden)

    D. S. Odnolko

    2013-01-01

    Full Text Available Synthesized algorithm for electromagnetic rotor time constant, active resistance and equivalent leakage inductance of stator induction motor for free rotating rotor. The problem is solved for induction motor model in the stationary stator frame α-β. The algorithm is based on the use of recursive least squares method, which ensures high accuracy of the parameter estimates for the minimum time. The observer does not assume prior information about the technical data machine and individual parameters of its equivalent circuit. Results of simulation demonstrated how effective of the proposed method of identification. The flexible structure of the algorithm allows it to be used for preliminary identification of an induction motor, and in the process operative work induction motor in the frequency-controlled electric drive with vector control.

  19. Initialization of a fractional order identification algorithm applied for Lithium-ion battery modeling in time domain

    Science.gov (United States)

    Nasser Eddine, Achraf; Huard, Benoît; Gabano, Jean-Denis; Poinot, Thierry

    2018-06-01

    This paper deals with the initialization of a non linear identification algorithm used to accurately estimate the physical parameters of Lithium-ion battery. A Randles electric equivalent circuit is used to describe the internal impedance of the battery. The diffusion phenomenon related to this modeling is presented using a fractional order method. The battery model is thus reformulated into a transfer function which can be identified through Levenberg-Marquardt algorithm to ensure the algorithm's convergence to the physical parameters. An initialization method is proposed in this paper by taking into account previously acquired information about the static and dynamic system behavior. The method is validated using noisy voltage response, while precision of the final identification results is evaluated using Monte-Carlo method.

  20. Algorithms

    Indian Academy of Sciences (India)

    algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).

  1. Algorithms

    Indian Academy of Sciences (India)

    algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...

  2. A new approach for visual identification of orange varieties using neural networks and metaheuristic algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Sabzi

    2018-03-01

    Full Text Available Accurate classification of fruit varieties in processing factories and during post-harvesting applications is a challenge that has been widely studied. This paper presents a novel approach to automatic fruit identification applied to three common varieties of oranges (Citrus sinensis L., namely Bam, Payvandi and Thomson. A total of 300 color images were used for the experiments, 100 samples for each orange variety, which are publicly available. After segmentation, 263 parameters, including texture, color and shape features, were extracted from each sample using image processing. Among them, the 6 most effective features were automatically selected by using a hybrid approach consisting of an artificial neural network and particle swarm optimization algorithm (ANN-PSO. Then, three different classifiers were applied and compared: hybrid artificial neural network – artificial bee colony (ANN-ABC; hybrid artificial neural network – harmony search (ANN-HS; and k-nearest neighbors (kNN. The experimental results show that the hybrid approaches outperform the results of kNN. The average correct classification rate of ANN-HS was 94.28%, while ANN-ABS achieved 96.70% accuracy with the available data, contrasting with the 70.9% baseline accuracy of kNN. Thus, this new proposed methodology provides a fast and accurate way to classify multiple fruits varieties, which can be easily implemented in processing factories. The main contribution of this work is that the method can be directly adapted to other use cases, since the selection of the optimal features and the configuration of the neural network are performed automatically using metaheuristic algorithms.

  3. Robust surface registration using salient anatomical features for image-guided liver surgery: Algorithm and validation

    OpenAIRE

    Clements, Logan W.; Chapman, William C.; Dawant, Benoit M.; Galloway, Robert L.; Miga, Michael I.

    2008-01-01

    A successful surface-based image-to-physical space registration in image-guided liver surgery (IGLS) is critical to provide reliable guidance information to surgeons and pertinent surface displacement data for use in deformation correction algorithms. The current protocol used to perform the image-to-physical space registration involves an initial pose estimation provided by a point based registration of anatomical landmarks identifiable in both the preoperative tomograms and the intraoperati...

  4. Weak Defect Identification for Centrifugal Compressor Blade Crack Based on Pressure Sensors and Genetic Algorithm.

    Science.gov (United States)

    Li, Hongkun; He, Changbo; Malekian, Reza; Li, Zhixiong

    2018-04-19

    pulsation signal. Genetic algorithm (GA) is used to obtain optimal parameters for this SR system to improve its feature enhancement performance. The analysis result of experimental signal shows the validity of the proposed method for the enhancement and identification of weak defect characteristic. In the end, strain test is carried out to further verify the accuracy and reliability of the analysis result obtained by pressure pulsation signal.

  5. Algorithms

    Indian Academy of Sciences (India)

    will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...

  6. Damage Identification of Trusses with Elastic Supports Using FEM and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Nam-Il Kim

    2013-01-01

    Full Text Available The computationally efficient damage identification technique for truss structures with elastic supports is proposed based on the force method. To transform the truss with supports into the equivalent free-standing model without supports, the novel zero-length dummy members are employed. General equilibrium equations and kinematic relations, in which the reaction forces and the displacements at the elastic supports are taken into account, are clearly formulated. The compatibility equations, in terms of forces in which the flexibilities of elastic supports are considered, are explicitly presented using the singular value decomposition (SVD technique. Both member and reaction forces are simultaneously and directly obtained. Then, all nodal displacements including constrained nodes are back calculated from the member and reaction forces. Next, the microgenetic algorithm (MGA is used to properly identify the site and the extent of multiple damages in truss structures. In order to verify the superiority of the current study, the numerical solutions are presented for the planar and space truss models with and without elastic supports. The numerical results indicate that the computational effort required by this study is found to be significantly lower than that of the displacement method.

  7. System Identification Algorithm Analysis of Acupuncture Effect on Mean Blood Flux of Contralateral Hegu Acupoint

    Directory of Open Access Journals (Sweden)

    Guangjun Wang

    2012-01-01

    Full Text Available Background. Acupoints (belonging to 12 meridians which have the same names are symmetrically distributed on the body. It has been proved that acupoints have certain biological specificities different from the normal parts of the body. However, there is little evidence that acupoints which have the same name and are located bilaterally and symmetrically have lateralized specificity. Thus, researching the lateralized specificity and the relationship between left-side and right-side acupuncture is of special importance. Methodology and Principal Findings. The mean blood flux (MBF in both Hegu acupoints was measured by Moor full-field laser perfusion imager. With the method of system identification algorithm, the output distribution in different groups was acquired, based on different acupoint stimulation and standard signal input. It is demonstrated that after stimulation of the right Hegu acupoint by needle, the output value of MBF in contralateral Hegu acupoint was strongly amplified, while after acupuncturing the left Hegu acupoint, the output value of MBF in either side Hegu acupoint was amplified moderately. Conclusions and Significance. This paper indicates that the Hegu acupoint has lateralized specificity. After stimulating the ipsilateral Hegu acupoint, symmetry breaking will be produced in contrast to contralateral Hegu acupoint stimulation.

  8. Implementation of a conjugate gradient algorithm for thermal diffusivity identification in a moving boundaries system

    International Nuclear Information System (INIS)

    Perez, L; Autrique, L; Gillet, M

    2008-01-01

    The aim of this paper is to investigate the thermal diffusivity identification of a multilayered material dedicated to fire protection. In a military framework, fire protection needs to meet specific requirements, and operational protective systems must be constantly improved in order to keep up with the development of new weapons. In the specific domain of passive fire protections, intumescent coatings can be an effective solution on the battlefield. Intumescent materials have the ability to swell up when they are heated, building a thick multi-layered coating which provides efficient thermal insulation to the underlying material. Due to the heat aggressions (fire or explosion) leading to the intumescent phenomena, high temperatures are considered and prevent from linearization of the mathematical model describing the system state evolution. Previous sensitivity analysis has shown that the thermal diffusivity of the multilayered intumescent coating is a key parameter in order to validate the predictive numerical tool and therefore for thermal protection optimisation. A conjugate gradient method is implemented in order to minimise the quadratic cost function related to the error between predicted temperature and measured temperature. This regularisation algorithm is well adapted for a large number of unknown parameters.

  9. A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

    Directory of Open Access Journals (Sweden)

    Dong-Sup Lee

    2015-01-01

    Full Text Available Independent Component Analysis (ICA, one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

  10. Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

    Directory of Open Access Journals (Sweden)

    Madlung Johannes

    2010-05-01

    Full Text Available Abstract Background Often high-quality MS/MS spectra of tryptic peptides do not match to any database entry because of only partially sequenced genomes and therefore, protein identification requires de novo peptide sequencing. To achieve protein identification of the economically important but still unsequenced plant pathogenic oomycete Plasmopara halstedii, we first evaluated the performance of three different de novo peptide sequencing algorithms applied to a protein digests of standard proteins using a quadrupole TOF (QStar Pulsar i. Results The performance order of the algorithms was PEAKS online > PepNovo > CompNovo. In summary, PEAKS online correctly predicted 45% of measured peptides for a protein test data set. All three de novo peptide sequencing algorithms were used to identify MS/MS spectra of tryptic peptides of an unknown 57 kDa protein of P. halstedii. We found ten de novo sequenced peptides that showed homology to a Phytophthora infestans protein, a closely related organism of P. halstedii. Employing a second complementary approach, verification of peptide prediction and protein identification was performed by creation of degenerate primers for RACE-PCR and led to an ORF of 1,589 bp for a hypothetical phosphoenolpyruvate carboxykinase. Conclusions Our study demonstrated that identification of proteins within minute amounts of sample material improved significantly by combining sensitive LC-MS methods with different de novo peptide sequencing algorithms. In addition, this is the first study that verified protein prediction from MS data by also employing a second complementary approach, in which RACE-PCR led to identification of a novel elicitor protein in P. halstedii.

  11. A Pre-Detection Based Anti-Collision Algorithm with Adjustable Slot Size Scheme for Tag Identification

    Directory of Open Access Journals (Sweden)

    Chiu-Kuo LIANG

    2015-06-01

    Full Text Available One of the research areas in RFID systems is a tag anti-collision protocol; how to reduce identification time with a given number of tags in the field of an RFID reader. There are two types of tag anti-collision protocols for RFID systems: tree based algorithms and slotted aloha based algorithms. Many anti-collision algorithms have been proposed in recent years, especially in tree based protocols. However, there still have challenges on enhancing the system throughput and stability due to the underlying technologies had faced different limitation in system performance when network density is high. Particularly, the tree based protocols had faced the long identification delay. Recently, a Hybrid Hyper Query Tree (H2QT protocol, which is a tree based approach, was proposed and aiming to speedup tag identification in large scale RFID systems. The main idea of H2QT is to track the tag response and try to predict the distribution of tag IDs in order to reduce collisions. In this paper, we propose a pre-detection tree based algorithm, called the Adaptive Pre-Detection Broadcasting Query Tree algorithm (APDBQT, to avoid those unnecessary queries. Our proposed APDBQT protocol can reduce not only the collisions but the idle cycles as well by using pre-detection scheme and adjustable slot size mechanism. The simulation results show that our proposed technique provides superior performance in high density environments. It is shown that the APDBQT is effective in terms of increasing system throughput and minimizing identification delay.

  12. Springback Simulation and Tool Surface Compensation Algorithm for Sheet Metal Forming

    International Nuclear Information System (INIS)

    Shen Guozhe; Hu Ping; Zhang Xiangkui; Chen Xiaobin; Li Xiaoda

    2005-01-01

    Springback is an unquenchable forming defect in the sheet metal forming process. How to calculate springback accurately is a big challenge for a lot of FEA software. Springback compensation makes the stamped final part accordant with the designed part shape by modifying tool surface, which depends on the accurate springback amount. How ever, the meshing data based on numerical simulation is expressed by nodes and elements, such data can not be supplied directly to tool surface CAD data. In this paper, a tool surface compensation algorithm based on numerical simulation technique of springback process is proposed in which the independently developed dynamic explicit springback algorithm (DESA) is used to simulate springback amount. When doing the tool surface compensation, the springback amount of the projected point can be obtained by interpolation of the springback amount of the projected element nodes. So the modified values of tool surface can be calculated reversely. After repeating the springback and compensation calculations for 1∼3 times, the reasonable tool surface mesh is gained. Finally, the FEM data on the compensated tool surface is fitted into the surface by CAD modeling software. The examination of a real industrial part shows the validity of the present method

  13. Development and validation of a novel algorithm based on the ECG magnet response for rapid identification of any unknown pacemaker.

    Science.gov (United States)

    Squara, Fabien; Chik, William W; Benhayon, Daniel; Maeda, Shingo; Latcu, Decebal Gabriel; Lacaze-Gadonneix, Jonathan; Tibi, Thierry; Thomas, Olivier; Cooper, Joshua M; Duthoit, Guillaume

    2014-08-01

    Pacemaker (PM) interrogation requires correct manufacturer identification. However, an unidentified PM is a frequent occurrence, requiring time-consuming steps to identify the device. The purpose of this study was to develop and validate a novel algorithm for PM manufacturer identification, using the ECG response to magnet application. Data on the magnet responses of all recent PM models (≤15 years) from the 5 major manufacturers were collected. An algorithm based on the ECG response to magnet application to identify the PM manufacturer was subsequently developed. Patients undergoing ECG during magnet application in various clinical situations were prospectively recruited in 7 centers. The algorithm was applied in the analysis of every ECG by a cardiologist blinded to PM information. A second blinded cardiologist analyzed a sample of randomly selected ECGs in order to assess the reproducibility of the results. A total of 250 ECGs were analyzed during magnet application. The algorithm led to the correct single manufacturer choice in 242 ECGs (96.8%), whereas 7 (2.8%) could only be narrowed to either 1 of 2 manufacturer possibilities. Only 2 (0.4%) incorrect manufacturer identifications occurred. The algorithm identified Medtronic and Sorin Group PMs with 100% sensitivity and specificity, Biotronik PMs with 100% sensitivity and 99.5% specificity, and St. Jude and Boston Scientific PMs with 92% sensitivity and 100% specificity. The results were reproducible between the 2 blinded cardiologists with 92% concordant findings. Unknown PM manufacturers can be accurately identified by analyzing the ECG magnet response using this newly developed algorithm. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

  14. Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

    Directory of Open Access Journals (Sweden)

    ZHU Xiaoxiao

    2018-02-01

    Full Text Available In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

  15. Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

    Science.gov (United States)

    Zhong, Chongquan; Lin, Yaoyao

    2017-11-01

    In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

  16. A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Loring, Burlen; Karimabadi, Homa; Rortershteyn, Vadim

    2014-07-01

    The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

  17. A fast Gaussian filtering algorithm for three-dimensional surface roughness measurements

    International Nuclear Information System (INIS)

    Yuan, Y B; Piao, W Y; Xu, J B

    2007-01-01

    The two-dimensional (2-D) Gaussian filter can be separated into two one-dimensional (1-D) Gaussian filters. The 1-D Gaussian filter can be implemented approximately by the cascaded Butterworth filters. The approximation accuracy will be improved with the increase of the number of the cascaded filters. A recursive algorithm for Gaussian filtering requires a relatively small number of simple mathematical operations such as addition, subtraction, multiplication, or division, so that it has considerable computational efficiency and it is very useful for three-dimensional (3-D) surface roughness measurements. The zero-phase-filtering technique is used in this algorithm, so there is no phase distortion in the Gaussian filtered mean surface. High-order approximation Gaussian filters are proposed for practical use to assure high accuracy of Gaussian filtering of 3-D surface roughness measurements

  18. A fast Gaussian filtering algorithm for three-dimensional surface roughness measurements

    Science.gov (United States)

    Yuan, Y. B.; Piao, W. Y.; Xu, J. B.

    2007-07-01

    The two-dimensional (2-D) Gaussian filter can be separated into two one-dimensional (1-D) Gaussian filters. The 1-D Gaussian filter can be implemented approximately by the cascaded Butterworth filters. The approximation accuracy will be improved with the increase of the number of the cascaded filters. A recursive algorithm for Gaussian filtering requires a relatively small number of simple mathematical operations such as addition, subtraction, multiplication, or division, so that it has considerable computational efficiency and it is very useful for three-dimensional (3-D) surface roughness measurements. The zero-phase-filtering technique is used in this algorithm, so there is no phase distortion in the Gaussian filtered mean surface. High-order approximation Gaussian filters are proposed for practical use to assure high accuracy of Gaussian filtering of 3-D surface roughness measurements.

  19. Inversion of Land Surface Temperature (LST Using Terra ASTER Data: A Comparison of Three Algorithms

    Directory of Open Access Journals (Sweden)

    Milton Isaya Ndossi

    2016-12-01

    Full Text Available Land Surface Temperature (LST is an important measurement in studies related to the Earth surface’s processes. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER instrument onboard the Terra spacecraft is the currently available Thermal Infrared (TIR imaging sensor with the highest spatial resolution. This study involves the comparison of LSTs inverted from the sensor using the Split Window Algorithm (SWA, the Single Channel Algorithm (SCA and the Planck function. This study has used the National Oceanic and Atmospheric Administration’s (NOAA data to model and compare the results from the three algorithms. The data from the sensor have been processed by the Python programming language in a free and open source software package (QGIS to enable users to make use of the algorithms. The study revealed that the three algorithms are suitable for LST inversion, whereby the Planck function showed the highest level of accuracy, the SWA had moderate level of accuracy and the SCA had the least accuracy. The algorithms produced results with Root Mean Square Errors (RMSE of 2.29 K, 3.77 K and 2.88 K for the Planck function, the SCA and SWA respectively.

  20. Genetic Algorithm-Based Optimization for Surface Roughness in Cylindrically Grinding Process Using Helically Grooved Wheels

    Science.gov (United States)

    Çaydaş, Ulaş; Çelik, Mahmut

    The present work is focused on the optimization of process parameters in cylindrical surface grinding of AISI 1050 steel with grooved wheels. Response surface methodology (RSM) and genetic algorithm (GA) techniques were merged to optimize the input variable parameters of grinding. The revolution speed of workpiece, depth of cut and number of grooves on the wheel were changed to explore their experimental effects on the surface roughness of machined bars. The mathematical models were established between the input parameters and response by using RSM. Then, the developed RSM model was used as objective functions on GA to optimize the process parameters.

  1. A feature-based approach for best arm identification in the case of the Monte Carlo search algorithm discovery for one-player games

    OpenAIRE

    Taralla, David

    2013-01-01

    The field of reinforcement learning recently received the contribution by Ernst et al. (2013) "Monte carlo search algorithm discovery for one player games" who introduced a new way to conceive completely new algorithms. Moreover, it brought an automatic method to find the best algorithm to use in a particular situation using a multi-arm bandit approach. We address here the problem of best arm identification. The main problem is that the generated algorithm space (ie. the arm space) can be qui...

  2. A general rough-surface inversion algorithm: Theory and application to SAR data

    Science.gov (United States)

    Moghaddam, M.

    1993-01-01

    Rough-surface inversion has significant applications in interpretation of SAR data obtained over bare soil surfaces and agricultural lands. Due to the sparsity of data and the large pixel size in SAR applications, it is not feasible to carry out inversions based on numerical scattering models. The alternative is to use parameter estimation techniques based on approximate analytical or empirical models. Hence, there are two issues to be addressed, namely, what model to choose and what estimation algorithm to apply. Here, a small perturbation model (SPM) is used to express the backscattering coefficients of the rough surface in terms of three surface parameters. The algorithm used to estimate these parameters is based on a nonlinear least-squares criterion. The least-squares optimization methods are widely used in estimation theory, but the distinguishing factor for SAR applications is incorporating the stochastic nature of both the unknown parameters and the data into formulation, which will be discussed in detail. The algorithm is tested with synthetic data, and several Newton-type least-squares minimization methods are discussed to compare their convergence characteristics. Finally, the algorithm is applied to multifrequency polarimetric SAR data obtained over some bare soil and agricultural fields. Results will be shown and compared to ground-truth measurements obtained from these areas. The strength of this general approach to inversion of SAR data is that it can be easily modified for use with any scattering model without changing any of the inversion steps. Note also that, for the same reason it is not limited to inversion of rough surfaces, and can be applied to any parameterized scattering process.

  3. Fast centroid algorithm for determining the surface plasmon resonance angle using the fixed-boundary method

    International Nuclear Information System (INIS)

    Zhan, Shuyue; Wang, Xiaoping; Liu, Yuling

    2011-01-01

    To simplify the algorithm for determining the surface plasmon resonance (SPR) angle for special applications and development trends, a fast method for determining an SPR angle, called the fixed-boundary centroid algorithm, has been proposed. Two experiments were conducted to compare three centroid algorithms from the aspects of the operation time, sensitivity to shot noise, signal-to-noise ratio (SNR), resolution, and measurement range. Although the measurement range of this method was narrower, the other performance indices were all better than the other two centroid methods. This method has outstanding performance, high speed, good conformity, low error and a high SNR and resolution. It thus has the potential to be widely adopted

  4. Zero-G experimental validation of a robotics-based inertia identification algorithm

    Science.gov (United States)

    Bruggemann, Jeremy J.; Ferrel, Ivann; Martinez, Gerardo; Xie, Pu; Ma, Ou

    2010-04-01

    The need to efficiently identify the changing inertial properties of on-orbit spacecraft is becoming more critical as satellite on-orbit services, such as refueling and repairing, become increasingly aggressive and complex. This need stems from the fact that a spacecraft's control system relies on the knowledge of the spacecraft's inertia parameters. However, the inertia parameters may change during flight for reasons such as fuel usage, payload deployment or retrieval, and docking/capturing operations. New Mexico State University's Dynamics, Controls, and Robotics Research Group has proposed a robotics-based method of identifying unknown spacecraft inertia properties1. Previous methods require firing known thrusts then measuring the thrust, and the velocity and acceleration changes. The new method utilizes the concept of momentum conservation, while employing a robotic device powered by renewable energy to excite the state of the satellite. Thus, it requires no fuel usage or force and acceleration measurements. The method has been well studied in theory and demonstrated by simulation. However its experimental validation is challenging because a 6- degree-of-freedom motion in a zero-gravity condition is required. This paper presents an on-going effort to test the inertia identification method onboard the NASA zero-G aircraft. The design and capability of the test unit will be discussed in addition to the flight data. This paper also introduces the design and development of an airbearing based test used to partially validate the method, in addition to the approach used to obtain reference value for the test system's inertia parameters that can be used for comparison with the algorithm results.

  5. Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm

    Science.gov (United States)

    Genovese, Mariangela; Napoli, Ettore

    2013-05-01

    The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.

  6. A new free-surface stabilization algorithm for geodynamical modelling: Theory and numerical tests

    Science.gov (United States)

    Andrés-Martínez, Miguel; Morgan, Jason P.; Pérez-Gussinyé, Marta; Rüpke, Lars

    2015-09-01

    The surface of the solid Earth is effectively stress free in its subaerial portions, and hydrostatic beneath the oceans. Unfortunately, this type of boundary condition is difficult to treat computationally, and for computational convenience, numerical models have often used simpler approximations that do not involve a normal stress-loaded, shear-stress free top surface that is free to move. Viscous flow models with a computational free surface typically confront stability problems when the time step is bigger than the viscous relaxation time. The small time step required for stability (develop strategies that mitigate the stability problem by making larger (at least ∼10 Kyr) time steps stable and accurate. Here we present a new free-surface stabilization algorithm for finite element codes which solves the stability problem by adding to the Stokes formulation an intrinsic penalization term equivalent to a portion of the future load at the surface nodes. Our algorithm is straightforward to implement and can be used with both Eulerian or Lagrangian grids. It includes α and β parameters to respectively control both the vertical and the horizontal slope-dependent penalization terms, and uses Uzawa-like iterations to solve the resulting system at a cost comparable to a non-stress free surface formulation. Four tests were carried out in order to study the accuracy and the stability of the algorithm: (1) a decaying first-order sinusoidal topography test, (2) a decaying high-order sinusoidal topography test, (3) a Rayleigh-Taylor instability test, and (4) a steep-slope test. For these tests, we investigate which α and β parameters give the best results in terms of both accuracy and stability. We also compare the accuracy and the stability of our algorithm with a similar implicit approach recently developed by Kaus et al. (2010). We find that our algorithm is slightly more accurate and stable for steep slopes, and also conclude that, for longer time steps, the optimal

  7. Effectoromics-based identification of cell surface receptors in potato

    NARCIS (Netherlands)

    Domazakis, Emmanouil; Lin, Xiao; Aguilera-Galvez, Carolina; Wouters, Doret; Bijsterbosch, Gerard; Wolters, Pieter J.; Vleeshouwers, Vivianne G.A.A.

    2017-01-01

    In modern resistance breeding, effectors have emerged as tools for accelerating and improving the identification of immune receptors. Effector-assisted breeding was pioneered for identifying resistance genes (R genes) against Phytophthora infestans in potato (Solanum tuberosum). Here we show that

  8. Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

    Science.gov (United States)

    Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

    2018-04-01

    Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

  9. The Development of a Parameterized Scatter Removal Algorithm for Nuclear Materials Identification System Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Grogan, Brandon Robert [Univ. of Tennessee, Knoxville, TN (United States)

    2010-03-01

    This dissertation presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects non-intrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross-sections of features inside the object can be determined. The cross sections can then be used to identify the materials and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons which are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using

  10. THE DEVELOPMENT OF A PARAMETERIZED SCATTER REMOVAL ALGORITHM FOR NUCLEAR MATERIALS IDENTIFICATION SYSTEM IMAGING

    Energy Technology Data Exchange (ETDEWEB)

    Grogan, Brandon R [ORNL

    2010-05-01

    This report presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects nonintrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross sections of features inside the object can be determined. The cross sections can then be used to identify the materials, and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons that are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized, and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements, and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using the

  11. Identification and characterization of the surface proteins of Clostridium difficile

    International Nuclear Information System (INIS)

    Dailey, D.C.

    1988-01-01

    Several clostridial proteins were detected on the clostridial cell surface by sensitive radioiodination techniques. Two major proteins and six minor proteins comprised the radioiodinated proteins on the clostridial cell surface. Cellular fractionation of surface radiolabeled C. difficile determined that the radioiodinated proteins were found in the cell wall fraction of C. difficile and surprisingly were also present in the clostridial membrane. Furthermore, an interesting phenomenon of disulfide-crosslinking of the cell surface proteins of C. difficile was observed. Disulfide-linked protein complexes were found in both the membrane and cell wall fractions. In addition, the cell surface proteins of C. difficile were found to be released into the culture medium. In attempts to further characterize the clostridial proteins recombinant DNA techniques were employed. In addition, the role of the clostridial cell surface proteins in the interactions of C. difficile with human PMNs was also investigated

  12. A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

    Directory of Open Access Journals (Sweden)

    Zunjian Bian

    2017-07-01

    Full Text Available The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 °C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

  13. Using subdivision surfaces and adaptive surface simplification algorithms for modeling chemical heterogeneities in geophysical flows

    Science.gov (United States)

    Schmalzl, JöRg; Loddoch, Alexander

    2003-09-01

    We present a new method for investigating the transport of an active chemical component in a convective flow. We apply a three-dimensional front tracking method using a triangular mesh. For the refinement of the mesh we use subdivision surfaces which have been developed over the last decade primarily in the field of computer graphics. We present two different subdivision schemes and discuss their applicability to problems related to fluid dynamics. For adaptive refinement we propose a weight function based on the length of triangle edge and the sum of the angles of the triangle formed with neighboring triangles. In order to remove excess triangles we apply an adaptive surface simplification method based on quadric error metrics. We test these schemes by advecting a blob of passive material in a steady state flow in which the total volume is well preserved over a long time. Since for time-dependent flows the number of triangles may increase exponentially in time we propose the use of a subdivision scheme with diffusive properties in order to remove the small scale features of the chemical field. By doing so we are able to follow the evolution of a heavy chemical component in a vigorously convecting field. This calculation is aimed at the fate of a heavy layer at the Earth's core-mantle boundary. Since the viscosity variation with temperature is of key importance we also present a calculation with a strongly temperature-dependent viscosity.

  14. Method for Walking Gait Identification in a Lower Extremity Exoskeleton Based on C4.5 Decision Tree Algorithm

    Directory of Open Access Journals (Sweden)

    Qing Guo

    2015-04-01

    Full Text Available A gait identification method for a lower extremity exoskeleton is presented in order to identify the gait sub-phases in human-machine coordinated motion. First, a sensor layout for the exoskeleton is introduced. Taking the difference between human lower limb motion and human-machine coordinated motion into account, the walking gait is divided into five sub-phases, which are ‘double standing’, ‘right leg swing and left leg stance’, ‘double stance with right leg front and left leg back’, ‘right leg stance and left leg swing’, and ‘double stance with left leg front and right leg back’. The sensors include shoe pressure sensors, knee encoders, and thigh and calf gyroscopes, and are used to measure the contact force of the foot, and the knee joint angle and its angular velocity. Then, five sub-phases of walking gait are identified by a C4.5 decision tree algorithm according to the data fusion of the sensors' information. Based on the simulation results for the gait division, identification accuracy can be guaranteed by the proposed algorithm. Through the exoskeleton control experiment, a division of five sub-phases for the human-machine coordinated walk is proposed. The experimental results verify this gait division and identification method. They can make hydraulic cylinders retract ahead of time and improve the maximal walking velocity when the exoskeleton follows the person's motion.

  15. An algorithm for detecting Trichodesmium surface blooms in the South Western Tropical Pacific

    Directory of Open Access Journals (Sweden)

    Y. Dandonneau

    2011-12-01

    Full Text Available Trichodesmium, a major colonial cyanobacterial nitrogen fixer, forms large blooms in NO3-depleted tropical oceans and enhances CO2 sequestration by the ocean due to its ability to fix dissolved dinitrogen. Thus, its importance in C and N cycles requires better estimates of its distribution at basin to global scales. However, existing algorithms to detect them from satellite have not yet been successful in the South Western Tropical Pacific (SP. Here, a novel algorithm (TRICHOdesmium SATellite based on radiance anomaly spectra (RAS observed in SeaWiFS imagery, is used to detect Trichodesmium during the austral summertime in the SP (5° S–25° S 160° E–170° W. Selected pixels are characterized by a restricted range of parameters quantifying RAS spectra (e.g. slope, intercept, curvature. The fraction of valid (non-cloudy pixels identified as Trichodesmium surface blooms in the region is low (between 0.01 and 0.2 %, but is about 100 times higher than deduced from previous algorithms. At daily scales in the SP, this fraction represents a total ocean surface area varying from 16 to 48 km2 in Winter and from 200 to 1000 km2 in Summer (and at monthly scale, from 500 to 1000 km2 in Winter and from 3100 to 10 890 km2 in Summer with a maximum of 26 432 km2 in January 1999. The daily distribution of Trichodesmium surface accumulations in the SP detected by TRICHOSAT is presented for the period 1998–2010 which demonstrates that the number of selected pixels peaks in November–February each year, consistent with field observations. This approach was validated with in situ observations of Trichodesmium surface accumulations in the Melanesian archipelago around New Caledonia, Vanuatu and Fiji Islands for the same period.

  16. Investigation of ALEGRA shock hydrocode algorithms using an exact free surface jet flow solution.

    Energy Technology Data Exchange (ETDEWEB)

    Hanks, Bradley Wright.; Robinson, Allen C

    2014-01-01

    Computational testing of the arbitrary Lagrangian-Eulerian shock physics code, ALEGRA, is presented using an exact solution that is very similar to a shaped charge jet flow. The solution is a steady, isentropic, subsonic free surface flow with significant compression and release and is provided as a steady state initial condition. There should be no shocks and no entropy production throughout the problem. The purpose of this test problem is to present a detailed and challenging computation in order to provide evidence for algorithmic strengths and weaknesses in ALEGRA which should be examined further. The results of this work are intended to be used to guide future algorithmic improvements in the spirit of test-driven development processes.

  17. Reproducibility of UAV-based earth surface topography based on structure-from-motion algorithms.

    Science.gov (United States)

    Clapuyt, François; Vanacker, Veerle; Van Oost, Kristof

    2014-05-01

    A representation of the earth surface at very high spatial resolution is crucial to accurately map small geomorphic landforms with high precision. Very high resolution digital surface models (DSM) can then be used to quantify changes in earth surface topography over time, based on differencing of DSMs taken at various moments in time. However, it is compulsory to have both high accuracy for each topographic representation and consistency between measurements over time, as DSM differencing automatically leads to error propagation. This study investigates the reproducibility of reconstructions of earth surface topography based on structure-from-motion (SFM) algorithms. To this end, we equipped an eight-propeller drone with a standard reflex camera. This equipment can easily be deployed in the field, as it is a lightweight, low-cost system in comparison with classic aerial photo surveys and terrestrial or airborne LiDAR scanning. Four sets of aerial photographs were created for one test field. The sets of airphotos differ in focal length, and viewing angles, i.e. nadir view and ground-level view. In addition, the importance of the accuracy of ground control points for the construction of a georeferenced point cloud was assessed using two different GPS devices with horizontal accuracy at resp. the sub-meter and sub-decimeter level. Airphoto datasets were processed with SFM algorithm and the resulting point clouds were georeferenced. Then, the surface representations were compared with each other to assess the reproducibility of the earth surface topography. Finally, consistency between independent datasets is discussed.

  18. Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation

    Directory of Open Access Journals (Sweden)

    Suk-Ju Kang

    2016-12-01

    Full Text Available This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple users, their detection accuracy is low and they cannot identify multiple users individually. The proposed algorithm solves these problems and enhances the detection accuracy. Specifically, the proposed algorithm adopts a classifier to detect faces for the red, green, and blue (RGB and depth images. Then, it calculates features based on the histogram of the oriented gradient for the detected facial region to identify multiple users, and selects the template that best matches the users from a pre-determined face database. Finally, the proposed algorithm extracts the final eye positions based on anatomical proportions. Simulation results show that the proposed algorithm improved the average F1 score by up to 0.490, compared with benchmark algorithms.

  19. Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

    Directory of Open Access Journals (Sweden)

    N. C. Wright

    2018-04-01

    Full Text Available Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

  20. Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

    Science.gov (United States)

    Wright, Nicholas C.; Polashenski, Chris M.

    2018-04-01

    Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

  1. Identification of individuals with ADHD using the Dean-Woodcock sensory motor battery and a boosted tree algorithm.

    Science.gov (United States)

    Finch, Holmes W; Davis, Andrew; Dean, Raymond S

    2015-03-01

    The accurate and early identification of individuals with pervasive conditions such as attention deficit hyperactivity disorder (ADHD) is crucial to ensuring that they receive appropriate and timely assistance and treatment. Heretofore, identification of such individuals has proven somewhat difficult, typically involving clinical decision making based on descriptions and observations of behavior, in conjunction with the administration of cognitive assessments. The present study reports on the use of a sensory motor battery in conjunction with a recursive partitioning computer algorithm, boosted trees, to develop a prediction heuristic for identifying individuals with ADHD. Results of the study demonstrate that this method is able to do so with accuracy rates of over 95 %, much higher than the popular logistic regression model against which it was compared. Implications of these results for practice are provided.

  2. The development of small-scale mechanization means positioning algorithm using radio frequency identification technology in industrial plants

    Science.gov (United States)

    Astafiev, A.; Orlov, A.; Privezencev, D.

    2018-01-01

    The article is devoted to the development of technology and software for the construction of positioning and control systems for small mechanization in industrial plants based on radio frequency identification methods, which will be the basis for creating highly efficient intelligent systems for controlling the product movement in industrial enterprises. The main standards that are applied in the field of product movement control automation and radio frequency identification are considered. The article reviews modern publications and automation systems for the control of product movement developed by domestic and foreign manufacturers. It describes the developed algorithm for positioning of small-scale mechanization means in an industrial enterprise. Experimental studies in laboratory and production conditions have been conducted and described in the article.

  3. An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

    Science.gov (United States)

    Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

    2013-03-08

    Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

  4. Testing the algorithms for automatic identification of errors on the measured quantities of the nuclear power plant. Verification tests

    International Nuclear Information System (INIS)

    Svatek, J.

    1999-12-01

    During the development and implementation of supporting software for the control room and emergency control centre at the Dukovany nuclear power plant it appeared necessary to validate the input quantities in order to assure operating reliability of the software tools. Therefore, the development of software for validation of the measured quantities of the plant data sources was initiated, and the software had to be debugged and verified. The report contains the proposal for and description of the verification tests for testing the algorithms of automatic identification of errors on the observed quantities of the NPP by means of homemade validation software. In particular, the algorithms treated serve the validation of the hot leg temperature at primary circuit loop no. 2 or 4 at the Dukovany-2 reactor unit using data from the URAN and VK3 information systems, recorded during 3 different days. (author)

  5. Evaluation of HIV-1 rapid tests and identification of alternative testing algorithms for use in Uganda.

    Science.gov (United States)

    Kaleebu, Pontiano; Kitandwe, Paul Kato; Lutalo, Tom; Kigozi, Aminah; Watera, Christine; Nanteza, Mary Bridget; Hughes, Peter; Musinguzi, Joshua; Opio, Alex; Downing, Robert; Mbidde, Edward Katongole

    2018-02-27

    The World Health Organization recommends that countries conduct two phase evaluations of HIV rapid tests (RTs) in order to come up with the best algorithms. In this report, we present the first ever such evaluation in Uganda, involving both blood and oral based RTs. The role of weak positive (WP) bands on the accuracy of the individual RT and on the algorithms was also investigated. In total 11 blood based and 3 oral transudate kits were evaluated. All together 2746 participants from seven sites, covering the four different regions of Uganda participated. Two enzyme immunoassays (EIAs) run in parallel were used as the gold standard. The performance and cost of the different algorithms was calculated, with a pre-determined price cut-off of either cheaper or within 20% price of the current algorithm of Determine + Statpak + Unigold. In the second phase, the three best algorithms selected in phase I were used at the point of care for purposes of quality control using finger stick whole blood. We identified three algorithms; Determine + SD Bioline + Statpak; Determine + Statpak + SD Bioline, both with the same sensitivity and specificity of 99.2% and 99.1% respectively and Determine + Statpak + Insti, with sensitivity and specificity of 99.1% and 99% respectively as having performed better and met the cost requirements. There were 15 other algorithms that performed better than the current one but rated more than the 20% price. None of the 3 oral mucosal transudate kits were suitable for inclusion in an algorithm because of their low sensitivities. Band intensity affected the performance of individual RTs but not the final algorithms. We have come up with three algorithms we recommend for public or Government procurement based on accuracy and cost. In case one algorithm is preferred, we recommend to replace Unigold, the current tie breaker with SD Bioline. We further recommend that all the 18 algorithms that have shown better performance than the current one are made

  6. An algorithm for three-dimensional Monte-Carlo simulation of charge distribution at biofunctionalized surfaces

    KAUST Repository

    Bulyha, Alena

    2011-01-01

    In this work, a Monte-Carlo algorithm in the constant-voltage ensemble for the calculation of 3d charge concentrations at charged surfaces functionalized with biomolecules is presented. The motivation for this work is the theoretical understanding of biofunctionalized surfaces in nanowire field-effect biosensors (BioFETs). This work provides the simulation capability for the boundary layer that is crucial in the detection mechanism of these sensors; slight changes in the charge concentration in the boundary layer upon binding of analyte molecules modulate the conductance of nanowire transducers. The simulation of biofunctionalized surfaces poses special requirements on the Monte-Carlo simulations and these are addressed by the algorithm. The constant-voltage ensemble enables us to include the right boundary conditions; the dna strands can be rotated with respect to the surface; and several molecules can be placed in a single simulation box to achieve good statistics in the case of low ionic concentrations relevant in experiments. Simulation results are presented for the leading example of surfaces functionalized with pna and with single- and double-stranded dna in a sodium-chloride electrolyte. These quantitative results make it possible to quantify the screening of the biomolecule charge due to the counter-ions around the biomolecules and the electrical double layer. The resulting concentration profiles show a three-layer structure and non-trivial interactions between the electric double layer and the counter-ions. The numerical results are also important as a reference for the development of simpler screening models. © 2011 The Royal Society of Chemistry.

  7. A general and Robust Ray-Casting-Based Algorithm for Triangulating Surfaces at the Nanoscale

    Science.gov (United States)

    Decherchi, Sergio; Rocchia, Walter

    2013-01-01

    We present a general, robust, and efficient ray-casting-based approach to triangulating complex manifold surfaces arising in the nano-bioscience field. This feature is inserted in a more extended framework that: i) builds the molecular surface of nanometric systems according to several existing definitions, ii) can import external meshes, iii) performs accurate surface area estimation, iv) performs volume estimation, cavity detection, and conditional volume filling, and v) can color the points of a grid according to their locations with respect to the given surface. We implemented our methods in the publicly available NanoShaper software suite (www.electrostaticszone.eu). Robustness is achieved using the CGAL library and an ad hoc ray-casting technique. Our approach can deal with any manifold surface (including nonmolecular ones). Those explicitly treated here are the Connolly-Richards (SES), the Skin, and the Gaussian surfaces. Test results indicate that it is robust to rotation, scale, and atom displacement. This last aspect is evidenced by cavity detection of the highly symmetric structure of fullerene, which fails when attempted by MSMS and has problems in EDTSurf. In terms of timings, NanoShaper builds the Skin surface three times faster than the single threaded version in Lindow et al. on a 100,000 atoms protein and triangulates it at least ten times more rapidly than the Kruithof algorithm. NanoShaper was integrated with the DelPhi Poisson-Boltzmann equation solver. Its SES grid coloring outperformed the DelPhi counterpart. To test the viability of our method on large systems, we chose one of the biggest molecular structures in the Protein Data Bank, namely the 1VSZ entry, which corresponds to the human adenovirus (180,000 atoms after Hydrogen addition). We were able to triangulate the corresponding SES and Skin surfaces (6.2 and 7.0 million triangles, respectively, at a scale of 2 grids per Å) on a middle-range workstation. PMID:23577073

  8. A comparison of semiglobal and local dense matching algorithms for surface reconstruction

    Directory of Open Access Journals (Sweden)

    E. Dall'Asta

    2014-06-01

    Full Text Available Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision. The paper is focused on the comparison of some stereo matching algorithms (local and global which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM, which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed. The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

  9. A comparison of semiglobal and local dense matching algorithms for surface reconstruction

    Science.gov (United States)

    Dall'Asta, E.; Roncella, R.

    2014-06-01

    Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision. The paper is focused on the comparison of some stereo matching algorithms (local and global) which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM), which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed. The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan) and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

  10. Locating Critical Circular and Unconstrained Failure Surface in Slope Stability Analysis with Tailored Genetic Algorithm

    Science.gov (United States)

    Pasik, Tomasz; van der Meij, Raymond

    2017-12-01

    This article presents an efficient search method for representative circular and unconstrained slip surfaces with the use of the tailored genetic algorithm. Searches for unconstrained slip planes with rigid equilibrium methods are yet uncommon in engineering practice, and little publications regarding truly free slip planes exist. The proposed method presents an effective procedure being the result of the right combination of initial population type, selection, crossover and mutation method. The procedure needs little computational effort to find the optimum, unconstrained slip plane. The methodology described in this paper is implemented using Mathematica. The implementation, along with further explanations, is fully presented so the results can be reproduced. Sample slope stability calculations are performed for four cases, along with a detailed result interpretation. Two cases are compared with analyses described in earlier publications. The remaining two are practical cases of slope stability analyses of dikes in Netherlands. These four cases show the benefits of analyzing slope stability with a rigid equilibrium method combined with a genetic algorithm. The paper concludes by describing possibilities and limitations of using the genetic algorithm in the context of the slope stability problem.

  11. Molecular identification of a malaria merozoite surface sheddase.

    Directory of Open Access Journals (Sweden)

    Philippa K Harris

    2005-11-01

    Full Text Available Proteolytic shedding of surface proteins during invasion by apicomplexan parasites is a widespread phenomenon, thought to represent a mechanism by which the parasites disengage adhesin-receptor complexes in order to gain entry into their host cell. Erythrocyte invasion by merozoites of the malaria parasite Plasmodium falciparum requires the shedding of ectodomain components of two essential surface proteins, called MSP1 and AMA1. Both are released by the same merozoite surface "sheddase," but the molecular identity and mode of action of this protease is unknown. Here we identify it as PfSUB2, an integral membrane subtilisin-like protease (subtilase. We show that PfSUB2 is stored in apical secretory organelles called micronemes. Upon merozoite release it is secreted onto the parasite surface and translocates to its posterior pole in an actin-dependent manner, a trafficking pattern predicted of the sheddase. Subtilase propeptides are usually selective inhibitors of their cognate protease, and the PfSUB2 propeptide is no exception; we show that recombinant PfSUB2 propeptide binds specifically to mature parasite-derived PfSUB2 and is a potent, selective inhibitor of MSP1 and AMA1 shedding, directly establishing PfSUB2 as the sheddase. PfSUB2 is a new potential target for drugs designed to prevent erythrocyte invasion by the malaria parasite.

  12. Identification of Surface Exposed Elementary Body Antigens of ...

    African Journals Online (AJOL)

    This study sought to identify the surface exposed antigenic components of Cowdria ruminantium elementary body (EB) by biotin labeling, determine effect of reducing and non-reducing conditions and heat on the mobility of these antigens and their reactivity to antibodies from immunized animals by Western blotting.

  13. An electron tomography algorithm for reconstructing 3D morphology using surface tangents of projected scattering interfaces

    Science.gov (United States)

    Petersen, T. C.; Ringer, S. P.

    2010-03-01

    Upon discerning the mere shape of an imaged object, as portrayed by projected perimeters, the full three-dimensional scattering density may not be of particular interest. In this situation considerable simplifications to the reconstruction problem are possible, allowing calculations based upon geometric principles. Here we describe and provide an algorithm which reconstructs the three-dimensional morphology of specimens from tilt series of images for application to electron tomography. Our algorithm uses a differential approach to infer the intersection of projected tangent lines with surfaces which define boundaries between regions of different scattering densities within and around the perimeters of specimens. Details of the algorithm implementation are given and explained using reconstruction calculations from simulations, which are built into the code. An experimental application of the algorithm to a nano-sized Aluminium tip is also presented to demonstrate practical analysis for a real specimen. Program summaryProgram title: STOMO version 1.0 Catalogue identifier: AEFS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2988 No. of bytes in distributed program, including test data, etc.: 191 605 Distribution format: tar.gz Programming language: C/C++ Computer: PC Operating system: Windows XP RAM: Depends upon the size of experimental data as input, ranging from 200 Mb to 1.5 Gb Supplementary material: Sample output files, for the test run provided, are available. Classification: 7.4, 14 External routines: Dev-C++ ( http://www.bloodshed.net/devcpp.html) Nature of problem: Electron tomography of specimens for which conventional back projection may fail and/or data for which there is a limited angular

  14. Constructing irregular surfaces to enclose macromolecular complexes for mesoscale modeling using the discrete surface charge optimization (DISCO) algorithm.

    Science.gov (United States)

    Zhang, Qing; Beard, Daniel A; Schlick, Tamar

    2003-12-01

    Salt-mediated electrostatics interactions play an essential role in biomolecular structures and dynamics. Because macromolecular systems modeled at atomic resolution contain thousands of solute atoms, the electrostatic computations constitute an expensive part of the force and energy calculations. Implicit solvent models are one way to simplify the model and associated calculations, but they are generally used in combination with standard atomic models for the solute. To approximate electrostatics interactions in models on the polymer level (e.g., supercoiled DNA) that are simulated over long times (e.g., milliseconds) using Brownian dynamics, Beard and Schlick have developed the DiSCO (Discrete Surface Charge Optimization) algorithm. DiSCO represents a macromolecular complex by a few hundred discrete charges on a surface enclosing the system modeled by the Debye-Hückel (screened Coulombic) approximation to the Poisson-Boltzmann equation, and treats the salt solution as continuum solvation. DiSCO can represent the nucleosome core particle (>12,000 atoms), for example, by 353 discrete surface charges distributed on the surfaces of a large disk for the nucleosome core particle and a slender cylinder for the histone tail; the charges are optimized with respect to the Poisson-Boltzmann solution for the electric field, yielding a approximately 5.5% residual. Because regular surfaces enclosing macromolecules are not sufficiently general and may be suboptimal for certain systems, we develop a general method to construct irregular models tailored to the geometry of macromolecules. We also compare charge optimization based on both the electric field and electrostatic potential refinement. Results indicate that irregular surfaces can lead to a more accurate approximation (lower residuals), and the refinement in terms of the electric field is more robust. We also show that surface smoothing for irregular models is important, that the charge optimization (by the TNPACK

  15. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

    Directory of Open Access Journals (Sweden)

    Offer Rozenstein

    2014-03-01

    Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

  16. A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor

    Directory of Open Access Journals (Sweden)

    Liang Zhang

    2015-08-01

    Full Text Available Internet of Things (IoT is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN k-Nearest Neighbor (KNN algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University’s datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy.

  17. A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor.

    Science.gov (United States)

    Zhang, Liang; Shen, Peiyi; Zhu, Guangming; Wei, Wei; Song, Houbing

    2015-08-14

    Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University's datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy.

  18. A Novel Algorithm for Feature Level Fusion Using SVM Classifier for Multibiometrics-Based Person Identification

    Directory of Open Access Journals (Sweden)

    Ujwalla Gawande

    2013-01-01

    Full Text Available Recent times witnessed many advancements in the field of biometric and ultimodal biometric fields. This is typically observed in the area, of security, privacy, and forensics. Even for the best of unimodal biometric systems, it is often not possible to achieve a higher recognition rate. Multimodal biometric systems overcome various limitations of unimodal biometric systems, such as nonuniversality, lower false acceptance, and higher genuine acceptance rates. More reliable recognition performance is achievable as multiple pieces of evidence of the same identity are available. The work presented in this paper is focused on multimodal biometric system using fingerprint and iris. Distinct textual features of the iris and fingerprint are extracted using the Haar wavelet-based technique. A novel feature level fusion algorithm is developed to combine these unimodal features using the Mahalanobis distance technique. A support-vector-machine-based learning algorithm is used to train the system using the feature extracted. The performance of the proposed algorithms is validated and compared with other algorithms using the CASIA iris database and real fingerprint database. From the simulation results, it is evident that our algorithm has higher recognition rate and very less false rejection rate compared to existing approaches.

  19. Application of the MOVE algorithm for the identification of reduced order models of a core of a BWR type reactor

    International Nuclear Information System (INIS)

    Victoria R, M.A.; Morales S, J.B.

    2005-01-01

    Presently work is applied the modified algorithm of the ellipsoid of optimal volume (MOVE) to a reduced order model of 5 differential equations of the core of a boiling water reactor (BWR) with the purpose of estimating the parameters that model the dynamics. The viability is analyzed of carrying out an analysis that calculates the global dynamic parameters that determine the stability of the system and the uncertainty of the estimate. The modified algorithm of the ellipsoid of optimal volume (MOVE), is a method applied to the parametric identification of systems, in particular to the estimate of groups of parameters (PSE for their initials in English). It is looked for to obtain the ellipsoid of smaller volume that guarantees to contain the real value of the parameters of the model. The PSE MOVE is a recursive identification method that can manage the sign of noise and to ponder it, the ellipsoid represents an advantage due to its easy mathematical handling in the computer, the results that surrender are very useful for the design of Robust Control since to smaller volume of the ellipsoid, better is in general the performance of the system to control. The comparison with other methods presented in the literature to estimate the reason of decline (DR) of a BWR is presented. (Author)

  20. Blind source identification from the multichannel surface electromyogram

    International Nuclear Information System (INIS)

    Holobar, A; Farina, D

    2014-01-01

    The spinal circuitries combine the information flow from the supraspinal centers with the afferent input to generate the neural codes that drive the human skeletal muscles. The muscles transform the neural drive they receive from alpha motor neurons into motor unit action potentials (electrical activity) and force. Thus, the output of the spinal cord circuitries can be examined noninvasively by measuring the electrical activity of skeletal muscles at the surface of the skin i.e. the surface electromyogram (EMG). The recorded multi-muscle EMG activity pattern is generated by mixing processes of neural sources that need to be identified from the recorded signals themselves, with minimal or no a priori information available. Recently, multichannel source separation techniques that rely minimally on a priori knowledge of the mixing process have been developed and successfully applied to surface EMG. They act at different scales of information extraction to identify: (a) the activation signals shared by synergistic skeletal muscles, (b) the specific neural activation of individual muscles, separating it from that of nearby muscles i.e. from crosstalk, and (c) the spike trains of the active motor neurons. This review discusses the assumptions made by these methods, the challenges and limitations, as well as examples of their current applications. (topical review)

  1. Identification of the Heat Transfer Coefficient in the Inverse Stefan Problem by Using the ABC Algorithm

    Directory of Open Access Journals (Sweden)

    E. Hetmaniok

    2012-12-01

    Full Text Available A procedure based on the Artificial Bee Colony algorithm for solving the two-phase axisymmetric one-dimensional inverse Stefanproblem with the third kind boundary condition is presented in this paper. Solving of the considered problem consists in reconstruction of the function describing the heat transfer coefficient appearing in boundary condition of the third kind in such a way that the reconstructed values of temperature would be as closed as possible to the measurements of temperature given in selected points of the solid. A crucial part of the solution method consists in minimizing some functional which will be executed with the aid of one of the swarm intelligence algorithms - the ABC algorithm.

  2. An Assessment of Surface Water Detection Algorithms for the Tahoua Region, Niger

    Science.gov (United States)

    Herndon, K. E.; Muench, R.; Cherrington, E. A.; Griffin, R.

    2017-12-01

    The recent release of several global surface water datasets derived from remotely sensed data has allowed for unprecedented analysis of the earth's hydrologic processes at a global scale. However, some of these datasets fail to identify important sources of surface water, especially small ponds, in the Sahel, an arid region of Africa that forms a border zone between the Sahara Desert to the north, and the savannah to the south. These ponds may seem insignificant in the context of wider, global-scale hydrologic processes, but smaller sources of water are important for local and regional assessments. Particularly, these smaller water bodies are significant sources of hydration and irrigation for nomadic pastoralists and smallholder farmers throughout the Sahel. For this study, several methods of identifying surface water from Landsat 8 OLI and Sentinel 1 SAR data were compared to determine the most effective means of delineating these features in the Tahoua Region of Niger. The Modified Normalized Difference Water Index (MNDWI) had the best performance when validated against very high resolution World View 3 imagery, with an overall accuracy of 99.48%. This study reiterates the importance of region-specific algorithms and suggests that the MNDWI method may be the best for delineating surface water in the Sahelian ecozone, likely due to the nature of the exposed geology and lack of dense green vegetation.

  3. Identification of aggregates for Tennessee bituminous surface courses

    Science.gov (United States)

    Sauter, Heather Jean

    Tennessee road construction is a major venue for federal and state spending. Tax dollars each year go to the maintenance and construction of roads. One aspect of highway construction that affects the public is the safety of its state roads. There are many factors that affect the safety of a given road. One factor that was focused on in this research was the polish resistance capabilities of aggregates. Several pre-evaluation methods have been used in the laboratory to predict what will happen in a field situation. A new pre-evaluation method was invented that utilized AASHTO T 304 procedure upscaled to accommodate surface bituminous aggregates. This new method, called the Tennessee Terminal Textural Condition Method (T3CM), was approved by Tennessee Department of Transportation to be used as a pre-evaluation method on bituminous surface courses. It was proven to be operator insensitive, repeatable, and an accurate indication of particle shape and texture. Further research was needed to correlate pre-evaluation methods to the current field method, ASTM E 274-85 Locked Wheel Skid Trailer. In this research, twenty-five in-place bituminous projects and eight source evaluations were investigated. The information gathered would further validate the T3CM and find the pre-evaluation method that best predicted the field method. In addition, new sources of aggregates for bituminous surface courses were revealed. The results of this research have shown T3CM to be highly repeatable with an overall coefficient of variation of 0.26% for an eight sample repeatability test. It was the best correlated pre-evaluation method with the locked wheel skid trailer method giving an R2 value of 0.3946 and a Pearson coefficient of 0.710. Being able to predict field performance of aggregates prior to construction is a powerful tool capable of saving time, money, labor, and possibly lives.

  4. Thoracic cavity segmentation algorithm using multiorgan extraction and surface fitting in volumetric CT

    Energy Technology Data Exchange (ETDEWEB)

    Bae, JangPyo [Interdisciplinary Program, Bioengineering Major, Graduate School, Seoul National University, Seoul 110-744, South Korea and Department of Radiology, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul 138-736 (Korea, Republic of); Kim, Namkug, E-mail: namkugkim@gmail.com; Lee, Sang Min; Seo, Joon Beom [Department of Radiology, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul 138-736 (Korea, Republic of); Kim, Hee Chan [Department of Biomedical Engineering, College of Medicine and Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 110-744 (Korea, Republic of)

    2014-04-15

    Purpose: To develop and validate a semiautomatic segmentation method for thoracic cavity volumetry and mediastinum fat quantification of patients with chronic obstructive pulmonary disease. Methods: The thoracic cavity region was separated by segmenting multiorgans, namely, the rib, lung, heart, and diaphragm. To encompass various lung disease-induced variations, the inner thoracic wall and diaphragm were modeled by using a three-dimensional surface-fitting method. To improve the accuracy of the diaphragm surface model, the heart and its surrounding tissue were segmented by a two-stage level set method using a shape prior. To assess the accuracy of the proposed algorithm, the algorithm results of 50 patients were compared to the manual segmentation results of two experts with more than 5 years of experience (these manual results were confirmed by an expert thoracic radiologist). The proposed method was also compared to three state-of-the-art segmentation methods. The metrics used to evaluate segmentation accuracy were volumetric overlap ratio (VOR), false positive ratio on VOR (FPRV), false negative ratio on VOR (FNRV), average symmetric absolute surface distance (ASASD), average symmetric squared surface distance (ASSSD), and maximum symmetric surface distance (MSSD). Results: In terms of thoracic cavity volumetry, the mean ± SD VOR, FPRV, and FNRV of the proposed method were (98.17 ± 0.84)%, (0.49 ± 0.23)%, and (1.34 ± 0.83)%, respectively. The ASASD, ASSSD, and MSSD for the thoracic wall were 0.28 ± 0.12, 1.28 ± 0.53, and 23.91 ± 7.64 mm, respectively. The ASASD, ASSSD, and MSSD for the diaphragm surface were 1.73 ± 0.91, 3.92 ± 1.68, and 27.80 ± 10.63 mm, respectively. The proposed method performed significantly better than the other three methods in terms of VOR, ASASD, and ASSSD. Conclusions: The proposed semiautomatic thoracic cavity segmentation method, which extracts multiple organs (namely, the rib, thoracic wall, diaphragm, and heart

  5. Identification of cultivated land using remote sensing images based on object-oriented artificial bee colony algorithm

    Science.gov (United States)

    Li, Nan; Zhu, Xiufang

    2017-04-01

    Cultivated land resources is the key to ensure food security. Timely and accurate access to cultivated land information is conducive to a scientific planning of food production and management policies. The GaoFen 1 (GF-1) images have high spatial resolution and abundant texture information and thus can be used to identify fragmentized cultivated land. In this paper, an object-oriented artificial bee colony algorithm was proposed for extracting cultivated land from GF-1 images. Firstly, the GF-1 image was segmented by eCognition software and some samples from the segments were manually identified into 2 types (cultivated land and non-cultivated land). Secondly, the artificial bee colony (ABC) algorithm was used to search for classification rules based on the spectral and texture information extracted from the image objects. Finally, the extracted classification rules were used to identify the cultivated land area on the image. The experiment was carried out in Hongze area, Jiangsu Province using wide field-of-view sensor on the GF-1 satellite image. The total precision of classification result was 94.95%, and the precision of cultivated land was 92.85%. The results show that the object-oriented ABC algorithm can overcome the defect of insufficient spectral information in GF-1 images and obtain high precision in cultivated identification.

  6. A possibilistic approach for transient identification with 'don't know' response capability optimized by genetic algorithm

    International Nuclear Information System (INIS)

    Almeida, Jose Carlos S. de; Schirru, Roberto; Pereira, Claudio M.N.A.; Universidade Federal, Rio de Janeiro, RJ

    2002-01-01

    This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work, optimized by genetic algorithm. The idea behind this method is to split the complex classification problem into small and simple ones, so that the performance in the classification can be increased. In order to accomplish that, a genetic algorithm is used to learn, from realistic simulated data, the optimized time partitions, which the robustness and correctness in the classification are maximized. The use of a possibilistic classification approach propitiates natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know 'response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical. Application of the proposed approach to a nuclear transient indentification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. Obtained results are shown and commented. (author)

  7. Identification of Arbitrary Zonation in Groundwater Parameters using the Level Set Method and a Parallel Genetic Algorithm

    Science.gov (United States)

    Lei, H.; Lu, Z.; Vesselinov, V. V.; Ye, M.

    2017-12-01

    Simultaneous identification of both the zonation structure of aquifer heterogeneity and the hydrogeological parameters associated with these zones is challenging, especially for complex subsurface heterogeneity fields. In this study, a new approach, based on the combination of the level set method and a parallel genetic algorithm is proposed. Starting with an initial guess for the zonation field (including both zonation structure and the hydraulic properties of each zone), the level set method ensures that material interfaces are evolved through the inverse process such that the total residual between the simulated and observed state variables (hydraulic head) always decreases, which means that the inversion result depends on the initial guess field and the minimization process might fail if it encounters a local minimum. To find the global minimum, the genetic algorithm (GA) is utilized to explore the parameters that define initial guess fields, and the minimal total residual corresponding to each initial guess field is considered as the fitness function value in the GA. Due to the expensive evaluation of the fitness function, a parallel GA is adapted in combination with a simulated annealing algorithm. The new approach has been applied to several synthetic cases in both steady-state and transient flow fields, including a case with real flow conditions at the chromium contaminant site at the Los Alamos National Laboratory. The results show that this approach is capable of identifying the arbitrary zonation structures of aquifer heterogeneity and the hydrogeological parameters associated with these zones effectively.

  8. Development of gastrointestinal surface. VIII. Lectin identification of carbohydrate differences

    International Nuclear Information System (INIS)

    Pang, K.Y.; Bresson, J.L.; Walker, W.A.

    1987-01-01

    Binding of microvillus membranes (MVM) from newborn and adult rats by concanavalin A (Con A), Ulex europaeus (UEA I), Dolichos bifluorus (DBA), and Triticum vulgaris (WGA) was examined to determine the availability of carbohydrate-containing sites for these lectins on the intestinal surface during development. Consistent patterns of differences in the reaction of MVM with these lectins were found. Con A and UEA had much higher reactivities to MVM of adult than newborn rats. 125 I-labeled-UEA gel overlay experiments revealed the abundance of UEA-binding sites in MVM of adult rat in contrast to the two binding sites in MVM of a newborn rat. DBA bound only to MVM of the adults, and very few binding sites were found in immature MVM. In contrast to these lectins, WGA binding was much higher in MVM of the newborns and decreased with maturation. Additional experiments on the age dependence of UEA and DBA reactivities revealed that the most striking changes occur in animals from 2 to 2 wk of age. In MVM from 2-wk-old rats, there were only 13.9% and < 0.2% of the adult binding capacities for UEA and DBA, respectively. By the time the animals were 4 wk old, the binding capacity for UEA had attained close to the level of the adults, whereas for DBA it reached 71.3% of the adult value. These results provide definite evidence of changes in the intestinal surface during perinatal development

  9. Development of gastrointestinal surface. VIII. Lectin identification of carbohydrate differences

    Energy Technology Data Exchange (ETDEWEB)

    Pang, K.Y.; Bresson, J.L.; Walker, W.A.

    1987-05-01

    Binding of microvillus membranes (MVM) from newborn and adult rats by concanavalin A (Con A), Ulex europaeus (UEA I), Dolichos bifluorus (DBA), and Triticum vulgaris (WGA) was examined to determine the availability of carbohydrate-containing sites for these lectins on the intestinal surface during development. Consistent patterns of differences in the reaction of MVM with these lectins were found. Con A and UEA had much higher reactivities to MVM of adult than newborn rats. /sup 125/I-labeled-UEA gel overlay experiments revealed the abundance of UEA-binding sites in MVM of adult rat in contrast to the two binding sites in MVM of a newborn rat. DBA bound only to MVM of the adults, and very few binding sites were found in immature MVM. In contrast to these lectins, WGA binding was much higher in MVM of the newborns and decreased with maturation. Additional experiments on the age dependence of UEA and DBA reactivities revealed that the most striking changes occur in animals from 2 to 2 wk of age. In MVM from 2-wk-old rats, there were only 13.9% and < 0.2% of the adult binding capacities for UEA and DBA, respectively. By the time the animals were 4 wk old, the binding capacity for UEA had attained close to the level of the adults, whereas for DBA it reached 71.3% of the adult value. These results provide definite evidence of changes in the intestinal surface during perinatal development.

  10. An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

    Science.gov (United States)

    Xia, Lang; Mao, Kebiao; Ma, Ying; Zhao, Fen; Jiang, Lipeng; Shen, Xinyi; Qin, Zhihao

    2014-01-01

    A practical algorithm was proposed to retrieve land surface temperature (LST) from Visible Infrared Imager Radiometer Suite (VIIRS) data in mid-latitude regions. The key parameter transmittance is generally computed from water vapor content, while water vapor channel is absent in VIIRS data. In order to overcome this shortcoming, the water vapor content was obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The analyses on the estimation errors of vapor content and emissivity indicate that when the water vapor errors are within the range of ±0.5 g/cm2, the mean retrieval error of the present algorithm is 0.634 K; while the land surface emissivity errors range from −0.005 to +0.005, the mean retrieval error is less than 1.0 K. Validation with the standard atmospheric simulation shows the average LST retrieval error for the twenty-three land types is 0.734 K, with a standard deviation value of 0.575 K. The comparison between the ground station LST data indicates the retrieval mean accuracy is −0.395 K, and the standard deviation value is 1.490 K in the regions with vegetation and water cover. Besides, the retrieval results of the test data have also been compared with the results measured by the National Oceanic and Atmospheric Administration (NOAA) VIIRS LST products, and the results indicate that 82.63% of the difference values are within the range of −1 to 1 K, and 17.37% of the difference values are within the range of ±2 to ±1 K. In a conclusion, with the advantages of multi-sensors taken fully exploited, more accurate results can be achieved in the retrieval of land surface temperature. PMID:25397919

  11. Therapeutic eyelids hygiene in the algorithms of prevention and treatment of ocular surface diseases

    Directory of Open Access Journals (Sweden)

    V. N. Trubilin

    2016-01-01

    Full Text Available When acute inflammation in anterior eye segment of a forward piece of an eye was stopped, ophthalmologists face a problem of absence of acute inflammation signs and at the same time complaints to the remain discomfort feelings. It causes dissatisfaction from the treatment. The complaints are typically caused by disturbance of tears productions. No accidental that the new group of diseases was allocated — the diseases of the ocular surface. Ocular surface is a difficult biologic system, including epithelium of the conjunctiva, cornea and limb, as well as the area costal margin eyelid and meibomian gland ducts. Pathological processes in conjunctiva, cornea and eyelids are linked with tears production. Ophthalmologists prescribes tears substitutions, providing short-term relief to patients. However, in respect that the lipid component of the tear film plays the key role in the preservation of its stability, eyelids hygiene is the basis for the treatment of dry eye associated with ocular surface diseases. Eyelids hygiene provides normal functioning of glands, restores the metabolic processes in skin and ensures the formation of a complete tear film. Protection of eyelids, especially the marginal edge from aggressive environmental agents, infections and parasites and is the basis for the prevention and treatment of blepharitis and dry eye syndrome. The most common clinical situations and algorithms of their treatment and prevention of dysfunction of the meibomian glands; demodectic blepharitis; seborrheic blepharitis; staphylococcal blepharitis; allergic blepharitis; barley and chalazion are discussed in the article. The prevention keratoconjunctival xerosis (before and postoperative period, caused by contact lenses, computer vision syndrome, remission after acute conjunctiva and cornea inflammation is also presented. The first part of the article presents the treatment and prevention algorithms for dysfunction of the meibomian glands, as well as

  12. Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure.

    Science.gov (United States)

    Peng, Wei; Wang, Jianxin; Zhao, Bihai; Wang, Lusheng

    2015-01-01

    Protein complexes play a significant role in understanding the underlying mechanism of most cellular functions. Recently, many researchers have explored computational methods to identify protein complexes from protein-protein interaction (PPI) networks. One group of researchers focus on detecting local dense subgraphs which correspond to protein complexes by considering local neighbors. The drawback of this kind of approach is that the global information of the networks is ignored. Some methods such as Markov Clustering algorithm (MCL), PageRank-Nibble are proposed to find protein complexes based on random walk technique which can exploit the global structure of networks. However, these methods ignore the inherent core-attachment structure of protein complexes and treat adjacent node equally. In this paper, we design a weighted PageRank-Nibble algorithm which assigns each adjacent node with different probability, and propose a novel method named WPNCA to detect protein complex from PPI networks by using weighted PageRank-Nibble algorithm and core-attachment structure. Firstly, WPNCA partitions the PPI networks into multiple dense clusters by using weighted PageRank-Nibble algorithm. Then the cores of these clusters are detected and the rest of proteins in the clusters will be selected as attachments to form the final predicted protein complexes. The experiments on yeast data show that WPNCA outperforms the existing methods in terms of both accuracy and p-value. The software for WPNCA is available at "http://netlab.csu.edu.cn/bioinfomatics/weipeng/WPNCA/download.html".

  13. A Level-2 trigger algorithm for the identification of muons in the ATLAS Muon Spectrometer

    CERN Document Server

    Di Mattia, A; Dos Anjos, A; Baines, J T M; Bee, C P; Biglietti, M; Bogaerts, J A C; Boisvert, V; Bosman, M; Caron, B; Casado, M P; Cataldi, G; Cavalli, D; Cervetto, M; Comune, G; Conde-Muíño, P; De Santo, A; Díaz-Gómez, M; Dosil, M; Ellis, Nick; Emeliyanov, D; Epp, B; Falciano, S; Farilla, A; George, S; Ghete, V M; González, S; Grothe, M; Kabana, S; Khomich, A; Kilvington, G; Konstantinidis, N P; Kootz, A; Lowe, A; Luminari, L; Maeno, T; Masik, J; Meessen, C; Mello, A G; Merino, G; Moore, R; Morettini, P; Negri, A; Nikitin, N V; Nisati, A; Padilla, C; Panikashvili, N; Parodi, F; Pasqualucci, E; Pérez-Réale, V; Pinfold, J L; Pinto, P; Qian, Z; Resconi, S; Rosati, S; Sánchez, C; Santamarina-Rios, C; Scannicchio, D A; Schiavi, C; Segura, E; De Seixas, J M; Sivoklokov, S Yu; Soluk, R A; Stefanidis, E; Sushkov, S S; Sutton, M; Tapprogge, Stefan; Thomas, E; Touchard, F; Venda-Pinto, B; Vercesi, V; Werner, P; Wheeler, S; Wickens, F J; Wiedenmann, W; Wielers, M; Zobernig, G; Computing In High Energy Physics

    2005-01-01

    The ATLAS Level-2 trigger provides a software-based event selection after the initial Level-1 hardware trigger. For the muon events, the selection is decomposed in a number of broad steps: first, the Muon Spectrometer data are processed to give physics quantities associated to the muon track (standalone feature extraction) then, other detector data are used to refine the extracted features. The “µFast” algorithm performs the standalone feature extraction, providing a first reduction of the muon event rate from Level-1. It confirms muon track candidates with a precise measurement of the muon momentum. The algorithm is designed to be both conceptually simple and fast so as to be readily implemented in the demanding online environment in which the Level-2 selection code will run. Never-the-less its physics performance approaches, in some cases, that of the offline reconstruction algorithms. This paper describes the implemented algorithm together with the software techniques employed to increase its timing p...

  14. Identification of Water Diffusivity of Inorganic Porous Materials Using Evolutionary Algorithms

    Czech Academy of Sciences Publication Activity Database

    Kočí, J.; Maděra, J.; Jerman, M.; Keppert, M.; Svora, Petr; Černý, R.

    2016-01-01

    Roč. 113, č. 1 (2016), s. 51-66 ISSN 0169-3913 Institutional support: RVO:61388980 Keywords : Evolutionary algorithms * Water transport * Inorganic porous materials * Inverse analysis Subject RIV: CA - Inorganic Chemistry Impact factor: 2.205, year: 2016

  15. Outcrop-scale fracture trace identification using surface roughness derived from a high-density point cloud

    Science.gov (United States)

    Okyay, U.; Glennie, C. L.; Khan, S.

    2017-12-01

    Owing to the advent of terrestrial laser scanners (TLS), high-density point cloud data has become increasingly available to the geoscience research community. Research groups have started producing their own point clouds for various applications, gradually shifting their emphasis from obtaining the data towards extracting more and meaningful information from the point clouds. Extracting fracture properties from three-dimensional data in a (semi-)automated manner has been an active area of research in geosciences. Several studies have developed various processing algorithms for extracting only planar surfaces. In comparison, (semi-)automated identification of fracture traces at the outcrop scale, which could be used for mapping fracture distribution have not been investigated frequently. Understanding the spatial distribution and configuration of natural fractures is of particular importance, as they directly influence fluid-flow through the host rock. Surface roughness, typically defined as the deviation of a natural surface from a reference datum, has become an important metric in geoscience research, especially with the increasing density and accuracy of point clouds. In the study presented herein, a surface roughness model was employed to identify fracture traces and their distribution on an ophiolite outcrop in Oman. Surface roughness calculations were performed using orthogonal distance regression over various grid intervals. The results demonstrated that surface roughness could identify outcrop-scale fracture traces from which fracture distribution and density maps can be generated. However, considering outcrop conditions and properties and the purpose of the application, the definition of an adequate grid interval for surface roughness model and selection of threshold values for distribution maps are not straightforward and require user intervention and interpretation.

  16. Acquisition and visualization of cross section surface characteristics for identification of archaeological ceramics

    NARCIS (Netherlands)

    Boon, Paul; Pont, Sylvia C.; van Oortmerssen, Gert J.M.

    2007-01-01

    This paper describes a new system for digitizing ceramic fabric reference collections and a preliminary evaluation of its applicability to archaeological ceramics identification. An important feature in the analysis of ceramic fabrics is the surface texture of the fresh cross section. Visibility of

  17. AATSR land surface temperature product algorithm verification over a WATERMED site

    Science.gov (United States)

    Noyes, E. J.; Sòria, G.; Sobrino, J. A.; Remedios, J. J.; Llewellyn-Jones, D. T.; Corlett, G. K.

    A new operational Land Surface Temperature (LST) product generated from data acquired by the Advanced Along-Track Scanning Radiometer (AATSR) provides the opportunity to measure LST on a global scale with a spatial resolution of 1 km2. The target accuracy of the product, which utilises nadir data from the AATSR thermal channels at 11 and 12 μm, is 2.5 K for daytime retrievals and 1.0 K at night. We present the results of an experiment where the performance of the algorithm has been assessed for one daytime and one night time overpass occurring over the WATERMED field site near Marrakech, Morocco, on 05 March 2003. Top of atmosphere (TOA) brightness temperatures (BTs) are simulated for 12 pixels from each overpass using a radiative transfer model, with the LST product and independent emissivity values and atmospheric data as inputs. We have estimated the error in the LST product over this biome for this set of conditions by applying the operational AATSR LST retrieval algorithm to the modelled BTs and comparing the results with the original AATSR LSTs input into the model. An average bias of -1.00 K (standard deviation 0.07 K) for the daytime data, and -1.74 K (standard deviation 0.02 K) for the night time data is obtained, which indicates that the algorithm is yielding an LST that is too cold under these conditions. While these results are within specification for daytime retrievals, this suggests that the target accuracy of 1.0 K at night is not being met within this biome.

  18. The Surface Extraction from TIN based Search-space Minimization (SETSM) algorithm

    Science.gov (United States)

    Noh, Myoung-Jong; Howat, Ian M.

    2017-07-01

    Digital Elevation Models (DEMs) provide critical information for a wide range of scientific, navigational and engineering activities. Submeter resolution, stereoscopic satellite imagery with high geometric and radiometric quality, and wide spatial coverage are becoming increasingly accessible for generating stereo-photogrammetric DEMs. However, low contrast and repeatedly-textured surfaces, such as snow and glacial ice at high latitudes, and mountainous terrains challenge existing stereo-photogrammetric DEM generation techniques, particularly without a-priori information such as existing seed DEMs or the manual setting of terrain-specific parameters. To utilize these data for fully-automatic DEM extraction at a large scale, we developed the Surface Extraction from TIN-based Search-space Minimization (SETSM) algorithm. SETSM is fully automatic (i.e. no search parameter settings are needed) and uses only the sensor model Rational Polynomial Coefficients (RPCs). SETSM adopts a hierarchical, combined image- and object-space matching strategy utilizing weighted normalized cross-correlation with both original distorted and geometrically corrected images for overcoming ambiguities caused by foreshortening and occlusions. In addition, SETSM optimally minimizes search-spaces to extract optimal matches over problematic terrains by iteratively updating object surfaces within a Triangulated Irregular Network, and utilizes a geometric-constrained blunder and outlier detection in object space. We prove the ability of SETSM to mitigate typical stereo-photogrammetric matching problems over a range of challenging terrains. SETSM is the primary DEM generation software for the US National Science Foundation's ArcticDEM project.

  19. Fault Identification Algorithm Based on Zone-Division Wide Area Protection System

    OpenAIRE

    Xiaojun Liu; Youcheng Wang; Hub Hu

    2014-01-01

    As the power grid becomes more magnified and complicated, wide-area protection system in the practical engineering application is more and more restricted by the communication level. Based on the concept of limitedness of wide-area protection system, the grid with complex structure is divided orderly in this paper, and fault identification and protection action are executed in each divided zone to reduce the pressure of the communication system. In protection zone, a new wide-area...

  20. Algorithms for the automatic identification of MARFEs and UFOs in JET database of visible camera videos

    International Nuclear Information System (INIS)

    Murari, A.; Camplani, M.; Cannas, B.; Usai, P.; Mazon, D.; Delaunay, F.

    2010-01-01

    MARFE instabilities and UFOs leave clear signatures in JET fast visible camera videos. Given the potential harmful consequences of these events, particularly as triggers of disruptions, it would be important to have the means of detecting them automatically. In this paper, the results of various algorithms to identify automatically the MARFEs and UFOs in JET visible videos are reported. The objective is to retrieve the videos, which have captured these events, exploring the whole JET database of images, as a preliminary step to the development of real-time identifiers in the future. For the detection of MARFEs, a complete identifier has been finalized, using morphological operators and Hu moments. The final algorithm manages to identify the videos with MARFEs with a success rate exceeding 80%. Due to the lack of a complete statistics of examples, the UFO identifier is less developed, but a preliminary code can detect UFOs quite reliably. (authors)

  1. Analysis of Surface Plasmon Resonance Curves with a Novel Sigmoid-Asymmetric Fitting Algorithm

    Directory of Open Access Journals (Sweden)

    Daeho Jang

    2015-09-01

    Full Text Available The present study introduces a novel curve-fitting algorithm for surface plasmon resonance (SPR curves using a self-constructed, wedge-shaped beam type angular interrogation SPR spectroscopy technique. Previous fitting approaches such as asymmetric and polynomial equations are still unsatisfactory for analyzing full SPR curves and their use is limited to determining the resonance angle. In the present study, we developed a sigmoid-asymmetric equation that provides excellent curve-fitting for the whole SPR curve over a range of incident angles, including regions of the critical angle and resonance angle. Regardless of the bulk fluid type (i.e., water and air, the present sigmoid-asymmetric fitting exhibited nearly perfect matching with a full SPR curve, whereas the asymmetric and polynomial curve fitting methods did not. Because the present curve-fitting sigmoid-asymmetric equation can determine the critical angle as well as the resonance angle, the undesired effect caused by the bulk fluid refractive index was excluded by subtracting the critical angle from the resonance angle in real time. In conclusion, the proposed sigmoid-asymmetric curve-fitting algorithm for SPR curves is widely applicable to various SPR measurements, while excluding the effect of bulk fluids on the sensing layer.

  2. Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms

    Science.gov (United States)

    Li, Shaoxin; Li, Linfang; Zeng, Qiuyao; Zhang, Yanjiao; Guo, Zhouyi; Liu, Zhiming; Jin, Mei; Su, Chengkang; Lin, Lin; Xu, Junfa; Liu, Songhao

    2015-05-01

    This study aims to characterize and classify serum surface-enhanced Raman spectroscopy (SERS) spectra between bladder cancer patients and normal volunteers by genetic algorithms (GAs) combined with linear discriminate analysis (LDA). Two group serum SERS spectra excited with nanoparticles are collected from healthy volunteers (n = 36) and bladder cancer patients (n = 55). Six diagnostic Raman bands in the regions of 481-486, 682-687, 1018-1034, 1313-1323, 1450-1459 and 1582-1587 cm-1 related to proteins, nucleic acids and lipids are picked out with the GAs and LDA. By the diagnostic models built with the identified six Raman bands, the improved diagnostic sensitivity of 90.9% and specificity of 100% were acquired for classifying bladder cancer patients from normal serum SERS spectra. The results are superior to the sensitivity of 74.6% and specificity of 97.2% obtained with principal component analysis by the same serum SERS spectra dataset. Receiver operating characteristic (ROC) curves further confirmed the efficiency of diagnostic algorithm based on GA-LDA technique. This exploratory work demonstrates that the serum SERS associated with GA-LDA technique has enormous potential to characterize and non-invasively detect bladder cancer through peripheral blood.

  3. Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping

    Directory of Open Access Journals (Sweden)

    Antero Kukko

    2008-09-01

    Full Text Available Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.

  4. Application of response surface methodology (RSM) and genetic algorithm in minimizing warpage on side arm

    Science.gov (United States)

    Raimee, N. A.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

    2017-09-01

    The plastic injection moulding process produces large numbers of parts of high quality with great accuracy and quickly. It has widely used for production of plastic part with various shapes and geometries. Side arm is one of the product using injection moulding to manufacture it. However, there are some difficulties in adjusting the parameter variables which are mould temperature, melt temperature, packing pressure, packing time and cooling time as there are warpage happen at the tip part of side arm. Therefore, the work reported herein is about minimizing warpage on side arm product by optimizing the process parameter using Response Surface Methodology (RSM) and with additional artificial intelligence (AI) method which is Genetic Algorithm (GA).

  5. Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

    Science.gov (United States)

    Diner, D.; Paradise, S.; Martonchik, J.

    1994-01-01

    In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

  6. Determination of Critical Conditions for Puncturing Almonds Using Coupled Response Surface Methodology and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Mahmood Mahmoodi-Eshkaftaki

    2013-01-01

    Full Text Available In this study, the effect of seed moisture content, probe diameter and loading velocity (puncture conditions on some mechanical properties of almond kernel and peeled almond kernel is considered to model a relationship between the puncture conditions and rupture energy. Furthermore, distribution of the mechanical properties is determined. The main objective is to determine the critical values of mechanical properties significant for peeling machines. The response surface methodology was used to find the relationship between the input parameters and the output responses, and the fitness function was applied to measure the optimal values using the genetic algorithm. Two-parameter Weibull function was used to describe the distribution of mechanical properties. Based on the Weibull parameter values, i.e. shape parameter (β and scale parameter (η calculated for each property, the mechanical distribution variations were completely described and it was confirmed that the mechanical properties are rule governed, which makes the Weibull function suitable for estimating their distributions. The energy model estimated using response surface methodology shows that the mechanical properties relate exponentially to the moisture, and polynomially to the loading velocity and probe diameter, which enabled successful estimation of the rupture energy (R²=0.94. The genetic algorithm calculated the critical values of seed moisture, probe diameter, and loading velocity to be 18.11 % on dry mass basis, 0.79 mm, and 0.15 mm/min, respectively, and optimum rupture energy of 1.97·10-³ J. These conditions were used for comparison with new samples, where the rupture energy was experimentally measured to be 2.68 and 2.21·10-³ J for kernel and peeled kernel, respectively, which was nearly in agreement with our model results.

  7. Soft tissue freezing process. Identification of the dual-phase lag model parameters using the evolutionary algorithm

    Science.gov (United States)

    Mochnacki, Bohdan; Majchrzak, Ewa; Paruch, Marek

    2018-01-01

    In the paper the soft tissue freezing process is considered. The tissue sub-domain is subjected to the action of cylindrical cryoprobe. Thermal processes proceeding in the domain considered are described using the dual-phase lag equation (DPLE) supplemented by the appropriate boundary and initial conditions. DPLE results from the generalization of the Fourier law in which two lag times are introduced (relaxation and thermalization times). The aim of research is the identification of these parameters on the basis of measured cooling curves at the set of points selected from the tissue domain. To solve the problem the evolutionary algorithms are used. The paper contains the mathematical model of the tissue freezing process, the very short information concerning the numerical solution of the basic problem, the description of the inverse problem solution and the results of computations.

  8. Identification of isomers and control of ionization and dissociation processes using dual-mass-spectrometer scheme and genetic algorithm optimization

    International Nuclear Information System (INIS)

    Chen Zhou; Qiu-Nan Tong; Zhang Cong-Cong; Hu Zhan

    2015-01-01

    Identification of acetone and its two isomers, and the control of their ionization and dissociation processes are performed using a dual-mass-spectrometer scheme. The scheme employs two sets of time of flight mass spectrometers to simultaneously acquire the mass spectra of two different molecules under the irradiation of identically shaped femtosecond laser pulses. The optimal laser pulses are found using closed-loop learning method based on a genetic algorithm. Compared with the mass spectra of the two isomers that are obtained with the transform limited pulse, those obtained under the irradiation of the optimal laser pulse show large differences and the various reaction pathways of the two molecules are selectively controlled. The experimental results demonstrate that the scheme is quite effective and useful in studies of two molecules having common mass peaks, which makes a traditional single mass spectrometer unfeasible. (paper)

  9. Particle identification at LHCb: new calibration techniques and machine learning classification algorithms

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Particle identification (PID) plays a crucial role in LHCb analyses. Combining information from LHCb subdetectors allows one to distinguish between various species of long-lived charged and neutral particles. PID performance directly affects the sensitivity of most LHCb measurements. Advanced multivariate approaches are used at LHCb to obtain the best PID performance and control systematic uncertainties. This talk highlights recent developments in PID that use innovative machine learning techniques, as well as novel data-driven approaches which ensure that PID performance is well reproduced in simulation.

  10. Validation of coding algorithms for the identification of patients hospitalized for alcoholic hepatitis using administrative data.

    Science.gov (United States)

    Pang, Jack X Q; Ross, Erin; Borman, Meredith A; Zimmer, Scott; Kaplan, Gilaad G; Heitman, Steven J; Swain, Mark G; Burak, Kelly W; Quan, Hude; Myers, Robert P

    2015-09-11

    Epidemiologic studies of alcoholic hepatitis (AH) have been hindered by the lack of a validated International Classification of Disease (ICD) coding algorithm for use with administrative data. Our objective was to validate coding algorithms for AH using a hospitalization database. The Hospital Discharge Abstract Database (DAD) was used to identify consecutive adults (≥18 years) hospitalized in the Calgary region with a diagnosis code for AH (ICD-10, K70.1) between 01/2008 and 08/2012. Medical records were reviewed to confirm the diagnosis of AH, defined as a history of heavy alcohol consumption, elevated AST and/or ALT (34 μmol/L, and elevated INR. Subgroup analyses were performed according to the diagnosis field in which the code was recorded (primary vs. secondary) and AH severity. Algorithms that incorporated ICD-10 codes for cirrhosis and its complications were also examined. Of 228 potential AH cases, 122 patients had confirmed AH, corresponding to a positive predictive value (PPV) of 54% (95% CI 47-60%). PPV improved when AH was the primary versus a secondary diagnosis (67% vs. 21%; P codes for ascites (PPV 75%; 95% CI 63-86%), cirrhosis (PPV 60%; 47-73%), and gastrointestinal hemorrhage (PPV 62%; 51-73%) had improved performance, however, the prevalence of these diagnoses in confirmed AH cases was low (29-39%). In conclusion the low PPV of the diagnosis code for AH suggests that caution is necessary if this hospitalization database is used in large-scale epidemiologic studies of this condition.

  11. A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data

    International Nuclear Information System (INIS)

    Wan, Z.; Li, Z.L.

    1997-01-01

    The authors have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NEΔT) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4--0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10--12.5 microm IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2--3 K

  12. Hybrid of Natural Element Method (NEM with Genetic Algorithm (GA to find critical slip surface

    Directory of Open Access Journals (Sweden)

    Shahriar Shahrokhabadi

    2014-06-01

    Full Text Available One of the most important issues in geotechnical engineering is the slope stability analysis for determination of the factor of safety and the probable slip surface. Finite Element Method (FEM is well suited for numerical study of advanced geotechnical problems. However, mesh requirements of FEM creates some difficulties for solution processing in certain problems. Recently, motivated by these limitations, several new Meshfree methods such as Natural Element Method (NEM have been used to analyze engineering problems. This paper presents advantages of using NEM in 2D slope stability analysis and Genetic Algorithm (GA optimization to determine the probable slip surface and the related factor of safety. The stress field is produced under plane strain condition using natural element formulation to simulate material behavior analysis utilized in conjunction with a conventional limit equilibrium method. In order to justify the preciseness and convergence of the proposed method, two kinds of examples, homogenous and non-homogenous, are conducted and results are compared with FEM and conventional limit equilibrium methods. The results show the robustness of the NEM in slope stability analysis.

  13. Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

    Energy Technology Data Exchange (ETDEWEB)

    Ulbrich, Uwe; Grieger, Jens [Freie Univ. Berlin (Germany). Inst. of Meteorology; Leckebusch, Gregor C. [Birmingham Univ. (United Kingdom). School of Geography, Earth and Environmental Sciences] [and others

    2013-02-15

    For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods. (orig.)

  14. Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

    Science.gov (United States)

    Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

    2017-07-01

    In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

  15. PERF: an exhaustive algorithm for ultra-fast and efficient identification of microsatellites from large DNA sequences.

    Science.gov (United States)

    Avvaru, Akshay Kumar; Sowpati, Divya Tej; Mishra, Rakesh Kumar

    2018-03-15

    Microsatellites or Simple Sequence Repeats (SSRs) are short tandem repeats of DNA motifs present in all genomes. They have long been used for a variety of purposes in the areas of population genetics, genotyping, marker-assisted selection and forensics. Numerous studies have highlighted their functional roles in genome organization and gene regulation. Though several tools are currently available to identify SSRs from genomic sequences, they have significant limitations. We present a novel algorithm called PERF for extremely fast and comprehensive identification of microsatellites from DNA sequences of any size. PERF is several fold faster than existing algorithms and uses up to 5-fold lesser memory. It provides a clean and flexible command-line interface to change the default settings, and produces output in an easily-parseable tab-separated format. In addition, PERF generates an interactive and stand-alone HTML report with charts and tables for easy downstream analysis. PERF is implemented in the Python programming language. It is freely available on PyPI under the package name perf_ssr, and can be installed directly using pip or easy_install. The documentation of PERF is available at https://github.com/rkmlab/perf. The source code of PERF is deposited in GitHub at https://github.com/rkmlab/perf under an MIT license. tej@ccmb.res.in. Supplementary data are available at Bioinformatics online.

  16. Multiple Convective Cell Identification and Tracking Algorithm for documenting time-height evolution of measured polarimetric radar and lightning properties

    Science.gov (United States)

    Rosenfeld, D.; Hu, J.; Zhang, P.; Snyder, J.; Orville, R. E.; Ryzhkov, A.; Zrnic, D.; Williams, E.; Zhang, R.

    2017-12-01

    A methodology to track the evolution of the hydrometeors and electrification of convective cells is presented and applied to various convective clouds from warm showers to super-cells. The input radar data are obtained from the polarimetric NEXRAD weather radars, The information on cloud electrification is obtained from Lightning Mapping Arrays (LMA). The development time and height of the hydrometeors and electrification requires tracking the evolution and lifecycle of convective cells. A new methodology for Multi-Cell Identification and Tracking (MCIT) is presented in this study. This new algorithm is applied to time series of radar volume scans. A cell is defined as a local maximum in the Vertical Integrated Liquid (VIL), and the echo area is divided between cells using a watershed algorithm. The tracking of the cells between radar volume scans is done by identifying the two cells in consecutive radar scans that have maximum common VIL. The vertical profile of the polarimetric radar properties are used for constructing the time-height cross section of the cell properties around the peak reflectivity as a function of height. The LMA sources that occur within the cell area are integrated as a function of height as well for each time step, as determined by the radar volume scans. The result of the tracking can provide insights to the evolution of storms, hydrometer types, precipitation initiation and cloud electrification under different thermodynamic, aerosol and geographic conditions. The details of the MCIT algorithm, its products and their performance for different types of storm are described in this poster.

  17. Parameter identification for continuous point emission source based on Tikhonov regularization method coupled with particle swarm optimization algorithm.

    Science.gov (United States)

    Ma, Denglong; Tan, Wei; Zhang, Zaoxiao; Hu, Jun

    2017-03-05

    In order to identify the parameters of hazardous gas emission source in atmosphere with less previous information and reliable probability estimation, a hybrid algorithm coupling Tikhonov regularization with particle swarm optimization (PSO) was proposed. When the source location is known, the source strength can be estimated successfully by common Tikhonov regularization method, but it is invalid when the information about both source strength and location is absent. Therefore, a hybrid method combining linear Tikhonov regularization and PSO algorithm was designed. With this method, the nonlinear inverse dispersion model was transformed to a linear form under some assumptions, and the source parameters including source strength and location were identified simultaneously by linear Tikhonov-PSO regularization method. The regularization parameters were selected by L-curve method. The estimation results with different regularization matrixes showed that the confidence interval with high-order regularization matrix is narrower than that with zero-order regularization matrix. But the estimation results of different source parameters are close to each other with different regularization matrixes. A nonlinear Tikhonov-PSO hybrid regularization was also designed with primary nonlinear dispersion model to estimate the source parameters. The comparison results of simulation and experiment case showed that the linear Tikhonov-PSO method with transformed linear inverse model has higher computation efficiency than nonlinear Tikhonov-PSO method. The confidence intervals from linear Tikhonov-PSO are more reasonable than that from nonlinear method. The estimation results from linear Tikhonov-PSO method are similar to that from single PSO algorithm, and a reasonable confidence interval with some probability levels can be additionally given by Tikhonov-PSO method. Therefore, the presented linear Tikhonov-PSO regularization method is a good potential method for hazardous emission

  18. Geostationary Communications Satellites as Sensors for the Space Weather Environment: Telemetry Event Identification Algorithms

    Science.gov (United States)

    Carlton, A.; Cahoy, K.

    2015-12-01

    Reliability of geostationary communication satellites (GEO ComSats) is critical to many industries worldwide. The space radiation environment poses a significant threat and manufacturers and operators expend considerable effort to maintain reliability for users. Knowledge of the space radiation environment at the orbital location of a satellite is of critical importance for diagnosing and resolving issues resulting from space weather, for optimizing cost and reliability, and for space situational awareness. For decades, operators and manufacturers have collected large amounts of telemetry from geostationary (GEO) communications satellites to monitor system health and performance, yet this data is rarely mined for scientific purposes. The goal of this work is to acquire and analyze archived data from commercial operators using new algorithms that can detect when a space weather (or non-space weather) event of interest has occurred or is in progress. We have developed algorithms, collectively called SEER (System Event Evaluation Routine), to statistically analyze power amplifier current and temperature telemetry by identifying deviations from nominal operations or other events and trends of interest. This paper focuses on our work in progress, which currently includes methods for detection of jumps ("spikes", outliers) and step changes (changes in the local mean) in the telemetry. We then examine available space weather data from the NOAA GOES and the NOAA-computed Kp index and sunspot numbers to see what role, if any, it might have played. By combining the results of the algorithm for many components, the spacecraft can be used as a "sensor" for the space radiation environment. Similar events occurring at one time across many component telemetry streams may be indicative of a space radiation event or system-wide health and safety concern. Using SEER on representative datasets of telemetry from Inmarsat and Intelsat, we find events that occur across all or many of

  19. Online Identification of Multivariable Discrete Time Delay Systems Using a Recursive Least Square Algorithm

    Directory of Open Access Journals (Sweden)

    Saïda Bedoui

    2013-01-01

    Full Text Available This paper addresses the problem of simultaneous identification of linear discrete time delay multivariable systems. This problem involves both the estimation of the time delays and the dynamic parameters matrices. In fact, we suggest a new formulation of this problem allowing defining the time delay and the dynamic parameters in the same estimated vector and building the corresponding observation vector. Then, we use this formulation to propose a new method to identify the time delays and the parameters of these systems using the least square approach. Convergence conditions and statistics properties of the proposed method are also developed. Simulation results are presented to illustrate the performance of the proposed method. An application of the developed approach to compact disc player arm is also suggested in order to validate simulation results.

  20. Fuel spill identification by gas chromatography -- genetic algorithms/pattern recognition techniques

    International Nuclear Information System (INIS)

    Lavine, B.K.; Moores, A.J.; Faruque, A.

    1998-01-01

    Gas chromatography and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of 256 gas chromatograms of neat jet fuels. 31 fuels that have undergone weathering in a subsurface environment were correctly identified by type using discriminants developed from the gas chromatograms of the neat jet fuels. Coalescing poorly resolved peaks, which occurred during preprocessing, diminished the resolution and hence information content of the GC profiles. Nevertheless a genetic algorithm was able to extract enough information from these profiles to correctly classify the chromatograms of weathered fuels. This suggests that cheaper and simpler GC instruments ca be used to type jet fuels

  1. Application of genetic algorithm for the simultaneous identification of atmospheric pollution sources

    Science.gov (United States)

    Cantelli, A.; D'Orta, F.; Cattini, A.; Sebastianelli, F.; Cedola, L.

    2015-08-01

    A computational model is developed for retrieving the positions and the emission rates of unknown pollution sources, under steady state conditions, starting from the measurements of the concentration of the pollutants. The approach is based on the minimization of a fitness function employing a genetic algorithm paradigm. The model is tested considering both pollutant concentrations generated through a Gaussian model in 25 points in a 3-D test case domain (1000m × 1000m × 50 m) and experimental data such as the Prairie Grass field experiments data in which about 600 receptors were located along five concentric semicircle arcs and the Fusion Field Trials 2007. The results show that the computational model is capable to efficiently retrieve up to three different unknown sources.

  2. Models for Evolutionary Algorithms and Their Applications in System Identification and Control Optimization

    DEFF Research Database (Denmark)

    Ursem, Rasmus Kjær

    population and many generations, which essentially turns the problem into a series of related static problems. To our surprise, the control problem could easily be solved when optimized like this. To further examine this, we compared the EA with a particle swarm and a local search approach, which we...... simulate an evolutionary process where the goal is to evolve solutions by means of crossover, mutation, and selection based on their quality (fitness) with respect to the optimization problem at hand. Evolutionary algorithms (EAs) are highly relevant for industrial applications, because they are capable...... of handling problems with non-linear constraints, multiple objectives, and dynamic components – properties that frequently appear in real-world problems. This thesis presents research in three fundamental areas of EC; fitness function design, methods for parameter control, and techniques for multimodal...

  3. Parameter identification of ZnO surge arrester models based on genetic algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bayadi, Abdelhafid [Laboratoire d' Automatique de Setif, Departement d' Electrotechnique, Faculte des Sciences de l' Ingenieur, Universite Ferhat ABBAS de Setif, Route de Bejaia Setif 19000 (Algeria)

    2008-07-15

    The correct and adequate modelling of ZnO surge arresters characteristics is very important for insulation coordination studies and systems reliability. In this context many researchers addressed considerable efforts to the development of surge arresters models to reproduce the dynamic characteristics observed in their behaviour when subjected to fast front impulse currents. The difficulties with these models reside essentially in the calculation and the adjustment of their parameters. This paper proposes a new technique based on genetic algorithm to obtain the best possible series of parameter values of ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the predicted results with the experimental results available in the literature. Using the ATP-EMTP package, an application of the arrester model on network system studies is presented and discussed. (author)

  4. THERAPEUTIC EYELIDS HYGIENE IN THE ALGORITHMS OF PREVENTION AND TREATMENT OF OCULAR SURFACE DISEASES. PART II

    Directory of Open Access Journals (Sweden)

    V. N. Trubilin

    2016-01-01

    problem of modern ophthalmology.Part 1 — Trubilin VN, Poluninа EG, Kurenkov VV, Kapkova SG, Markova EY, Therapeutic eyelids hygiene in the algorithms of prevention and treatment of ocular surface diseases. Ophthalmology in Russia. 2016;13(2:122–127 doi: 10.18008/1816–5095– 2016–2–122–127

  5. Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

    Science.gov (United States)

    Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

    2017-12-01

    The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance

  6. Surface protein composition of Aeromonas hydrophila strains virulent for fish: identification of a surface array protein

    International Nuclear Information System (INIS)

    Dooley, J.S.G.; Trust, T.J.

    1988-01-01

    The surface protein composition of members of a serogroup of Aeromonas hydrophila was examined. Immunoblotting with antiserum raised against formalinized whole cells of A. hydrophila TF7 showed a 52K S-layer protein to be the major surface protein antigen, and impermeant Sulfo-NHS-Biotin cell surface labeling showed that the 52K S-layer protein was the only protein accessible to the Sulfo-NHS-Biotin label and effectively masked underlying outer membrane (OM) proteins. In its native surface conformation the 52K S-layer protein was only weakly reactive with a lactoperoxidase 125 I surface iodination procedure. A UV-induced rough lipopolysaccharide (LPS) mutant of TF7 was found to produce an intact S layer, but a deep rough LPS mutant was unable to maintain an array on the cell surface and excreted the S-layer protein into the growth medium, indicating that a minimum LPS oligosaccharide size required for A. hydrophila S-layer anchoring. The native S layer was permeable to 125 I in the lactoperoxidase radiolabeling procedure, and two major OM proteins of molecular weights 30,000 and 48,000 were iodinated. The 48K species was a peptidoglycan-associated, transmembrane protein which exhibited heat-modifiable SDS solubilization behavior characteristic of a porin protein. A 50K major peptidoglycan-associated OM protein which was not radiolabeled exhibited similar SDS heat modification characteristics and possibly represents a second porin protein

  7. Identification of faint central stars in extended, low-surface-brightness planetary nebulae

    International Nuclear Information System (INIS)

    Kwitter, K.B.; Lydon, T.J.; Jacoby, G.H.

    1988-01-01

    As part of a larger program to study the properties of planetary nebula central stars, a search for faint central stars in extended, low-surface-brightness planetary nebulae using CCD imaging is performed. Of 25 target nebulae, central star candidates have been identified in 17, with certainties ranging from extremely probable to possible. Observed V values in the central star candidates extend to fainter than 23 mag. The identifications are presented along with the resulting photometric measurements. 24 references

  8. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Deling Wang

    2018-03-01

    Full Text Available Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS, random forest (RF, and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  9. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms.

    Science.gov (United States)

    Wang, Deling; Li, Jia-Rui; Zhang, Yu-Hang; Chen, Lei; Huang, Tao; Cai, Yu-Dong

    2018-03-12

    Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX) model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), random forest (RF), and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  10. Identification of candidate sites for a near surface repository for radioactive waste

    International Nuclear Information System (INIS)

    Motiejunas, S.

    2004-01-01

    This Report comprises results of the area survey stage, which involves regional screening to define the regions of interest and identification of potential sites within suitable regions. The main goal was to define a few sites potentially suitable for constructing of the near surface repository. It was concluded that a vicinity of Ignalina NPP is among the best suitable regions for the near surface repository. At the present investigation level a ridge in Galilauke village has the most favorable conditions. However, Apvardai site is potentially suitable for the repository too

  11. An integrated study of surface roughness in EDM process using regression analysis and GSO algorithm

    Science.gov (United States)

    Zainal, Nurezayana; Zain, Azlan Mohd; Sharif, Safian; Nuzly Abdull Hamed, Haza; Mohamad Yusuf, Suhaila

    2017-09-01

    The aim of this study is to develop an integrated study of surface roughness (Ra) in the die-sinking electrical discharge machining (EDM) process of Ti-6AL-4V titanium alloy with positive polarity of copper-tungsten (Cu-W) electrode. Regression analysis and glowworm swarm optimization (GSO) algorithm were considered for modelling and optimization process. Pulse on time (A), pulse off time (B), peak current (C) and servo voltage (D) were selected as the machining parameters with various levels. The experiments have been conducted based on the two levels of full factorial design with an added center point design of experiments (DOE). Moreover, mathematical models with linear and 2 factor interaction (2FI) effects of the parameters chosen were developed. The validity test of the fit and the adequacy of the developed mathematical models have been carried out by using analysis of variance (ANOVA) and F-test. The statistical analysis showed that the 2FI model outperformed with the most minimal value of Ra compared to the linear model and experimental result.

  12. A wavelet-based PWTD algorithm-accelerated time domain surface integral equation solver

    KAUST Repository

    Liu, Yang

    2015-10-26

    © 2015 IEEE. The multilevel plane-wave time-domain (PWTD) algorithm allows for fast and accurate analysis of transient scattering from, and radiation by, electrically large and complex structures. When used in tandem with marching-on-in-time (MOT)-based surface integral equation (SIE) solvers, it reduces the computational and memory costs of transient analysis from equation and equation to equation and equation, respectively, where Nt and Ns denote the number of temporal and spatial unknowns (Ergin et al., IEEE Trans. Antennas Mag., 41, 39-52, 1999). In the past, PWTD-accelerated MOT-SIE solvers have been applied to transient problems involving half million spatial unknowns (Shanker et al., IEEE Trans. Antennas Propag., 51, 628-641, 2003). Recently, a scalable parallel PWTD-accelerated MOT-SIE solver that leverages a hiearchical parallelization strategy has been developed and successfully applied to the transient problems involving ten million spatial unknowns (Liu et. al., in URSI Digest, 2013). We further enhanced the capabilities of this solver by implementing a compression scheme based on local cosine wavelet bases (LCBs) that exploits the sparsity in the temporal dimension (Liu et. al., in URSI Digest, 2014). Specifically, the LCB compression scheme was used to reduce the memory requirement of the PWTD ray data and computational cost of operations in the PWTD translation stage.

  13. Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

    Science.gov (United States)

    Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

    2012-09-01

    This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.

  14. Numerical thermal analysis and optimization of multi-chip LED module using response surface methodology and genetic algorithm

    NARCIS (Netherlands)

    Tang, Hong Yu; Ye, Huai Yu; Chen, Xian Ping; Qian, Cheng; Fan, Xue Jun; Zhang, G.Q.

    2017-01-01

    In this paper, the heat transfer performance of the multi-chip (MC) LED module is investigated numerically by using a general analytical solution. The configuration of the module is optimized with genetic algorithm (GA) combined with a response surface methodology. The space between chips, the

  15. Protein social behavior makes a stronger signal for partner identification than surface geometry

    Science.gov (United States)

    Laine, Elodie

    2016-01-01

    ABSTRACT Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico‐chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross‐docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S‐index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface‐based (ranking) score to discriminate partners from non‐interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137–154. © 2016 Wiley Periodicals, Inc. PMID:27802579

  16. Identification of spectrally similar materials using the USGS Tetracorder algorithm: The calcite-epidote-chlorite problem

    Science.gov (United States)

    Dalton, J.B.; Bove, D.J.; Mladinich, C.S.; Rockwell, B.W.

    2004-01-01

    A scheme to discriminate and identify materials having overlapping spectral absorption features has been developed and tested based on the U.S. Geological Survey (USGS) Tetracorder system. The scheme has been applied to remotely sensed imaging spectroscopy data acquired by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument. This approach was used to identify the minerals calcite, epidote, and chlorite in the upper Animas River watershed, Colorado. The study was motivated by the need to characterize the distribution of calcite in the watershed and assess its acid-neutralizing potential with regard to acidic mine drainage. Identification of these three minerals is difficult because their diagnostic spectral features are all centered at 2.3 ??m, and have similar shapes and widths. Previous studies overestimated calcite abundance as a result of these spectral overlaps. The use of a reference library containing synthetic mixtures of the three minerals in varying proportions was found to simplify the task of identifying these minerals when used in conjunction with a rule-based expert system. Some inaccuracies in the mineral distribution maps remain, however, due to the influence of a fourth spectral component, sericite, which exhibits spectral absorption features at 2.2 and 2.4 ??m that overlap the 2.3-??m absorption features of the other three minerals. Whereas the endmember minerals calcite, epidote, chlorite, and sericite can be identified by the method presented here, discrepancies occur in areas where all four occur together as intimate mixtures. It is expected that future work will be able to reduce these discrepancies by including reference mixtures containing sericite. ?? 2004 Elsevier Inc. All rights reserved.

  17. Identification and real time control of current profile in Tore-supra: algorithms and simulation; Identification et controle en temps reel du profil de courant dans Tore Supra: algorithmes et simulations

    Energy Technology Data Exchange (ETDEWEB)

    Houy, P

    1999-10-15

    The aim of this work is to propose a real-time control of the current profile in order to achieve reproducible operating modes with improved energetic confinement in tokamaks. The determination of the profile is based on measurements given by interferometry and polarimetry diagnostics. Different ways to evaluate and improve the accuracy of these measurements are exposed. The position and the shape of a plasma are controlled by the poloidal system that forces them to cope with standard values. Gas or neutral ions or ice pellet or extra power injection are technical means used to control other plasma parameters. These controls are performed by servo-controlled loops. The poloidal system of Tore-supra is presented. The main obstacle to a reliable determination of the current profile is the fact that slightly different Faraday angles lead to very different profiles. The direct identification method that is exposed in this work, gives the profile that minimizes the square of the margin between measured and computed values. The different algorithms proposed to control current profiles on Tore-supra have been validated by using a plasma simulation. The code Cronos that solves the resistive diffusion equation of current has been used. (A.C.)

  18. An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

    Science.gov (United States)

    Tan, Bin; Brown de Colstoun, Eric; Wolfe, Robert E.; Tilton, James C.; Huang, Chengquan; Smith, Sarah E.

    2012-01-01

    An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to

  19. Improving Limit Surface Search Algorithms in RAVEN Using Acceleration Schemes: Level II Milestone

    Energy Technology Data Exchange (ETDEWEB)

    Alfonsi, Andrea [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Cogliati, Joshua Joseph [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Sen, Ramazan Sonat [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Smith, Curtis Lee [Idaho National Laboratory (INL), Idaho Falls, ID (United States)

    2015-07-01

    The RAVEN code is becoming a comprehensive tool to perform Probabilistic Risk Assessment (PRA); Uncertainty Quantification (UQ) and Propagation; and Verification and Validation (V&V). The RAVEN code is being developed to support the Risk-Informed Safety Margin Characterization (RISMC) pathway by developing an advanced set of methodologies and algorithms for use in advanced risk analysis. The RISMC approach uses system simulator codes applied to stochastic analysis tools. The fundamental idea behind this coupling approach to perturb (by employing sampling strategies) timing and sequencing of events, internal parameters of the system codes (i.e., uncertain parameters of the physics model) and initial conditions to estimate values ranges and associated probabilities of figures of merit of interest for engineering and safety (e.g. core damage probability, etc.). This approach applied to complex systems such as nuclear power plants requires performing a series of computationally expensive simulation runs. The large computational burden is caused by the large set of (uncertain) parameters characterizing those systems. Consequently, exploring the uncertain/parametric domain, with a good level of confidence, is generally not affordable, considering the limited computational resources that are currently available. In addition, the recent tendency to develop newer tools, characterized by higher accuracy and larger computational resources (if compared with the presently used legacy codes, that have been developed decades ago), has made this issue even more compelling. In order to overcome to these limitations, the strategy for the exploration of the uncertain/parametric space needs to use at best the computational resources focusing the computational effort in those regions of the uncertain/parametric space that are “interesting” (e.g., risk-significant regions of the input space) with respect the targeted Figures Of Merit (FOM): for example, the failure of the system

  20. Genus- and species-level identification of dermatophyte fungi by surface-enhanced Raman spectroscopy

    Science.gov (United States)

    Witkowska, Evelin; Jagielski, Tomasz; Kamińska, Agnieszka

    2018-03-01

    This paper demonstrates that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) can serve as a fast and reliable technique for detection and identification of dermatophyte fungi at both genus and species level. Dermatophyte infections are the most common mycotic diseases worldwide, affecting a quarter of the human population. Currently, there is no optimal method for detection and identification of fungal diseases, as each has certain limitations. Here, for the first time, we have achieved with a high accuracy, differentiation of dermatophytes representing three major genera, i.e. Trichophyton, Microsporum, and Epidermophyton. Two first principal components (PC), namely PC-1 and PC-2, gave together 97% of total variance. Additionally, species-level identification within the Trichophyton genus has been performed. PC-1 and PC-2, which are the most diagnostically significant, explain 98% of the variance in the data obtained from spectra of: Trichophyton rubrum, Trichophyton menatgrophytes, Trichophyton interdigitale and Trichophyton tonsurans. This study offers a new diagnostic approach for the identification of dermatophytes. Being fast, reliable and cost-effective, it has the potential to be incorporated in the clinical practice to improve diagnostics of medically important fungi.

  1. Rapid and Direct VHH and Target Identification by Staphylococcal Surface Display Libraries

    Directory of Open Access Journals (Sweden)

    Marco Cavallari

    2017-07-01

    Full Text Available Unbiased and simultaneous identification of a specific antibody and its target antigen has been difficult without prior knowledge of at least one interaction partner. Immunization with complex mixtures of antigens such as whole organisms and tissue extracts including tumoral ones evokes a highly diverse immune response. During such a response, antibodies are generated against a variety of epitopes in the mixture. Here, we propose a surface display design that is suited to simultaneously identify camelid single domain antibodies and their targets. Immune libraries of single-domain antigen recognition fragments from camelid heavy chain-only antibodies (VHH were attached to the peptidoglycan of Gram-positive Staphylococcus aureus employing its endogenous housekeeping sortase enzyme. The sortase transpeptidation reaction covalently attached the VHH to the bacterial peptidoglycan. The reversible nature of the reaction allowed the recovery of the VHH from the bacterial surface and the use of the VHH in downstream applications. These staphylococcal surface display libraries were used to rapidly identify VHH as well as their targets by immunoprecipitation (IP. Our novel bacterial surface display platform was stable under harsh screening conditions, allowed fast target identification, and readily permitted the recovery of the displayed VHH for downstream analysis.

  2. An efficient and robust algorithm for parallel groupwise registration of bone surfaces

    NARCIS (Netherlands)

    van de Giessen, Martijn; Vos, Frans M.; Grimbergen, Cornelis A.; van Vliet, Lucas J.; Streekstra, Geert J.

    2012-01-01

    In this paper a novel groupwise registration algorithm is proposed for the unbiased registration of a large number of densely sampled point clouds. The method fits an evolving mean shape to each of the example point clouds thereby minimizing the total deformation. The registration algorithm

  3. Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID) of Penguins.

    Science.gov (United States)

    Afanasyev, Vsevolod; Buldyrev, Sergey V; Dunn, Michael J; Robst, Jeremy; Preston, Mark; Bremner, Steve F; Briggs, Dirk R; Brown, Ruth; Adlard, Stacey; Peat, Helen J

    2015-01-01

    A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus) at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

  4. Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

    Science.gov (United States)

    Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

    2016-01-01

    The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

  5. Effect of Load Model Using Ranking Identification Technique for Multi Type DG Incorporating Embedded Meta EP-Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    Abdul Rahim Siti Rafidah

    2018-01-01

    Full Text Available This paper presents the effect of load model prior to the distributed generation (DG planning in distribution system. In achieving optimal allocation and placement of DG, a ranking identification technique was proposed in order to study the DG planning using pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm. The aim of this study is to analyze the effect of different type of DG in order to reduce the total losses considering load factor. To realize the effectiveness of the proposed technique, the IEEE 33 bus test systems was utilized as the test specimen. In this study, the proposed techniques were used to determine the DG sizing and the suitable location for DG planning. The results produced are utilized for the optimization process of DG for the benefit of power system operators and planners in the utility. The power system planner can choose the suitable size and location from the result obtained in this study with the appropriate company’s budget. The modeling of voltage dependent loads has been presented and the results show the voltage dependent load models have a significant effect on total losses of a distribution system for different DG type.

  6. A Case Study on Maximizing Aqua Feed Pellet Properties Using Response Surface Methodology and Genetic Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Tumuluru, Jaya

    2013-01-10

    Aims: The present case study is on maximizing the aqua feed properties using response surface methodology and genetic algorithm. Study Design: Effect of extrusion process variables like screw speed, L/D ratio, barrel temperature, and feed moisture content were analyzed to maximize the aqua feed properties like water stability, true density, and expansion ratio. Place and Duration of Study: This study was carried out in the Department of Agricultural and Food Engineering, Indian Institute of Technology, Kharagpur, India. Methodology: A variable length single screw extruder was used in the study. The process variables selected were screw speed (rpm), length-to-diameter (L/D) ratio, barrel temperature (degrees C), and feed moisture content (%). The pelletized aqua feed was analyzed for physical properties like water stability (WS), true density (TD), and expansion ratio (ER). Extrusion experimental data was collected by based on central composite design. The experimental data was further analyzed using response surface methodology (RSM) and genetic algorithm (GA) for maximizing feed properties. Results: Regression equations developed for the experimental data has adequately described the effect of process variables on the physical properties with coefficient of determination values (R2) of > 0.95. RSM analysis indicated WS, ER, and TD were maximized at L/D ratio of 12-13, screw speed of 60-80 rpm, feed moisture content of 30-40%, and barrel temperature of = 80 degrees C for ER and TD and > 90 degrees C for WS. Based on GA analysis, a maxium WS of 98.10% was predicted at a screw speed of 96.71 rpm, L/D radio of 13.67, barrel temperature of 96.26 degrees C, and feed moisture content of 33.55%. Maximum ER and TD of 0.99 and 1346.9 kg/m3 was also predicted at screw speed of 60.37 and 90.24 rpm, L/D ratio of 12.18 and 13.52, barrel temperature of 68.50 and 64.88 degrees C, and medium feed moisture content of 33.61 and 38.36%. Conclusion: The present data analysis indicated

  7. Dynamic Water Surface Detection Algorithm Applied on PROBA-V Multispectral Data

    Directory of Open Access Journals (Sweden)

    Luc Bertels

    2016-12-01

    Full Text Available Water body detection worldwide using spaceborne remote sensing is a challenging task. A global scale multi-temporal and multi-spectral image analysis method for water body detection was developed. The PROBA-V microsatellite has been fully operational since December 2013 and delivers daily near-global synthesis with a spatial resolution of 1 km and 333 m. The Red, Near-InfRared (NIR and Short Wave InfRared (SWIR bands of the atmospherically corrected 10-day synthesis images are first Hue, Saturation and Value (HSV color transformed and subsequently used in a decision tree classification for water body detection. To minimize commission errors four additional data layers are used: the Normalized Difference Vegetation Index (NDVI, Water Body Potential Mask (WBPM, Permanent Glacier Mask (PGM and Volcanic Soil Mask (VSM. Threshold values on the hue and value bands, expressed by a parabolic function, are used to detect the water bodies. Beside the water bodies layer, a quality layer, based on the water bodies occurrences, is available in the output product. The performance of the Water Bodies Detection Algorithm (WBDA was assessed using Landsat 8 scenes over 15 regions selected worldwide. A mean Commission Error (CE of 1.5% was obtained while a mean Omission Error (OE of 15.4% was obtained for minimum Water Surface Ratio (WSR = 0.5 and drops to 9.8% for minimum WSR = 0.6. Here, WSR is defined as the fraction of the PROBA-V pixel covered by water as derived from high spatial resolution images, e.g., Landsat 8. Both the CE = 1.5% and OE = 9.8% (WSR = 0.6 fall within the user requirements of 15%. The WBDA is fully operational in the Copernicus Global Land Service and products are freely available.

  8. Real-time intelligent pattern recognition algorithm for surface EMG signals

    Directory of Open Access Journals (Sweden)

    Jahed Mehran

    2007-12-01

    Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

  9. Smell identification of spices using nanomechanical membrane-type surface stress sensors

    Science.gov (United States)

    Imamura, Gaku; Shiba, Kota; Yoshikawa, Genki

    2016-11-01

    Artificial olfaction, that is, a chemical sensor system that identifies samples by smell, has not been fully achieved because of the complex perceptional mechanism of olfaction. To realize an artificial olfactory system, not only an array of chemical sensors but also a valid feature extraction method is required. In this study, we achieved the identification of spices by smell using nanomechanical membrane-type surface stress sensors (MSS). Features were extracted from the sensing signals obtained from four MSS coated with different types of polymers, focusing on the chemical interactions between polymers and odor molecules. The principal component analysis (PCA) of the dataset consisting of the extracted parameters demonstrated the separation of each spice on the scatter plot. We discuss the strategy for improving odor identification based on the relationship between the results of PCA and the chemical species in the odors.

  10. Ear biometrics for patient identification in global health: a cross-sectional study to test the feasibility of a simplified algorithm.

    Science.gov (United States)

    Ragan, Elizabeth J; Johnson, Courtney; Milton, Jacqueline N; Gill, Christopher J

    2016-11-02

    One of the greatest public health challenges in low- and middle-income countries (LMICs) is identifying people over time and space. Recent years have seen an explosion of interest in developing electronic approaches to addressing this problem, with mobile technology at the forefront of these efforts. We investigate the possibility of biometrics as a simple, cost-efficient, and portable solution. Common biometrics approaches include fingerprinting, iris scanning and facial recognition, but all are less than ideal due to complexity, infringement on privacy, cost, or portability. Ear biometrics, however, proved to be a unique and viable solution. We developed an identification algorithm then conducted a cross sectional study in which we photographed left and right ears from 25 consenting adults. We then conducted re-identification and statistical analyses to identify the accuracy and replicability of our approach. Through principal component analysis, we found the curve of the ear helix to be the most reliable anatomical structure and the basis for re-identification. Although an individual ear allowed for high re-identification rate (88.3%), when both left and right ears were paired together, our rate of re-identification amidst the pool of potential matches was 100%. The results of this study have implications on future efforts towards building a biometrics solution for patient identification in LMICs. We provide a conceptual platform for further investigation into the development of an ear biometrics identification mobile application.

  11. An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2015-04-01

    Full Text Available The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST. However, calibration notices issued by the United States Geological Survey (USGS indicated that data from the Landsat 8 Thermal Infrared Sensor (TIRS Band 11 have large uncertainty and suggested using TIRS Band 10 data as a single spectral band for LST estimation. In this study, we presented an improved mono-window (IMW algorithm for LST retrieval from the Landsat 8 TIRS Band 10 data. Three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature were required for the IMW algorithm to retrieve LST. A new method was proposed to estimate the parameter of effective mean atmospheric temperature from local meteorological data. The other two essential parameters could be both estimated through the so-called land cover approach. Sensitivity analysis conducted for the IMW algorithm revealed that the possible error in estimating the required atmospheric water vapor content has the most significant impact on the probable LST estimation error. Under moderate errors in both water vapor content and ground emissivity, the algorithm had an accuracy of ~1.4 K for LST retrieval. Validation of the IMW algorithm using the simulated datasets for various situations indicated that the LST difference between the retrieved and the simulated ones was 0.67 K on average, with an RMSE of 0.43 K. Comparison of our IMW algorithm with the single-channel (SC algorithm for three main atmosphere profiles indicated that the average error and RMSE of the IMW algorithm were −0.05 K and 0.84 K, respectively, which were less than the −2.86 K and 1.05 K of the SC algorithm. Application of the IMW algorithm to Nanjing and its vicinity in east China resulted in a reasonable LST estimation for the region. Spatial

  12. Localization of accessory pathway in patients with wolff-parkinson-white syndrome from surface ecg using arruda algorithm

    International Nuclear Information System (INIS)

    Saidullah, S.; Shah, B.

    2016-01-01

    Background: To ablate accessory pathway successfully and conveniently, accurate localization of the pathway is needed. Electrophysiologists use different algorithms before taking the patients to the electrophysiology (EP) laboratory to plan the intervention accordingly. In this study, we used Arruda algorithm to locate the accessory pathway. The objective of the study was to determine the accuracy of the Arruda algorithm for locating the pathway on surface ECG. Methods: It was a cross-sectional observational study conducted from January 2014 to January 2016 in the electrophysiology department of Hayat Abad Medical Complex Peshawar Pakistan. A total of fifty nine (n=59) consecutive patients of both genders between age 14-60 years presented with WPW syndrome (Symptomatic tachycardia with delta wave on surface ECG) were included in the study. Patient's electrocardiogram (ECG) before taking patients to laboratory was analysed on Arruda algorithm. Standard four wires protocol was used for EP study before ablation. Once the findings were confirmed the pathway was ablated as per standard guidelines. Results: A total of fifty nine (n=59) patients between the age 14-60 years were included in the study. Cumulative mean age was 31.5 years ± 12.5 SD. There were 56.4% (n=31) males with mean age 28.2 years ± 10.2 SD and 43.6% (n=24) were females with mean age 35.9 years ± 14.0 SD. Arruda algorithm was found to be accurate in predicting the exact accessory pathway (AP) in 83.6% (n=46) cases. Among all inaccurate predictions (n=9), Arruda inaccurately predicted two third (n=6; 66.7%) pathways towards right side (right posteroseptal, right posterolateral and right antrolateral). Conclusion: Arruda algorithm was found highly accurate in predicting accessory pathway before ablation. (author)

  13. A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI

    Directory of Open Access Journals (Sweden)

    Giuseppe Loprencipe

    2017-04-01

    Full Text Available In this paper, a simplified procedure for the assessment of pavement structural integrity and the level of service for urban road surfaces is presented. A sample of 109 Asphalt Concrete (AC urban pavements of an Italian road network was considered to validate the methodology. As part of this research, the most recurrent defects, those never encountered and those not defined with respect to the list collected in the ASTM D6433 have been determined by statistical analysis. The goal of this research is the improvement of the ASTM D6433 Distress Identification Catalogue to be adapted to urban road surfaces. The presented methodology includes the implementation of a Visual Basic for Application (VBA language-based program for the computerization of Pavement Condition Index (PCI calculation with interpolation by the parametric cubic spline of all of the density/deduct value curves of ASTM D6433 distress types. Also, two new distress definitions (for manholes and for tree roots and new density/deduct curve values were proposed to achieve a new distress identification manual for urban road pavements. To validate the presented methodology, for the 109 urban pavements considered, the PCI was calculated using the new distress catalogue and using the ASTM D6433 implemented on PAVERTM. The results of the linear regression between them and their statistical parameters are presented in this paper. The comparison of the results shows that the proposed method is suitable for the identification and assessment of observed distress in urban pavement surfaces at the PCI-based scale.

  14. Wavelet based edge detection algorithm for web surface inspection of coated board web

    Energy Technology Data Exchange (ETDEWEB)

    Barjaktarovic, M; Petricevic, S, E-mail: slobodan@etf.bg.ac.r [School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11000 Belgrade (Serbia)

    2010-07-15

    This paper presents significant improvement of the already installed vision system. System was designed for real time coated board inspection. The improvement is achieved with development of a new algorithm for edge detection. The algorithm is based on the redundant (undecimated) wavelet transform. Compared to the existing algorithm better delineation of edges is achieved. This yields to better defect detection probability and more accurate geometrical classification, which will provide additional reduction of waste. Also, algorithm will provide detailed classification and more reliably tracking of defects. This improvement requires minimal changes in processing hardware, only a replacement of the graphic card would be needed, adding only negligibly to the system cost. Other changes are accomplished entirely in the image processing software.

  15. Implementation of Freeman-Wimley prediction algorithm in a web-based application for in silico identification of beta-barrel membrane proteins

    OpenAIRE

    José Antonio Agüero-Fernández; Lisandra Aguilar-Bultet; Yandy Abreu-Jorge; Agustín Lage-Castellanos; Yannier Estévez-Dieppa

    2015-01-01

    Beta-barrel type proteins play an important role in both, human and veterinary medicine. In particular, their localization on the bacterial surface, and their involvement in virulence mechanisms of pathogens, have turned them into an interesting target in studies to search for vaccine candidates. Recently, Freeman and Wimley developed a prediction algorithm based on the physicochemical properties of transmembrane beta-barrels proteins (TMBBs). Based on that algorithm, and using Grails, a web-...

  16. Crystal identification for a dual-layer-offset LYSO based PET system via Lu-176 background radiation and mean shift algorithm

    Science.gov (United States)

    Wei, Qingyang; Ma, Tianyu; Xu, Tianpeng; Zeng, Ming; Gu, Yu; Dai, Tiantian; Liu, Yaqiang

    2018-01-01

    Modern positron emission tomography (PET) detectors are made from pixelated scintillation crystal arrays and readout by Anger logic. The interaction position of the gamma-ray should be assigned to a crystal using a crystal position map or look-up table. Crystal identification is a critical procedure for pixelated PET systems. In this paper, we propose a novel crystal identification method for a dual-layer-offset LYSO based animal PET system via Lu-176 background radiation and mean shift algorithm. Single photon event data of the Lu-176 background radiation are acquired in list-mode for 3 h to generate a single photon flood map (SPFM). Coincidence events are obtained from the same data using time information to generate a coincidence flood map (CFM). The CFM is used to identify the peaks of the inner layer using the mean shift algorithm. The response of the inner layer is deducted from the SPFM by subtracting CFM. Then, the peaks of the outer layer are also identified using the mean shift algorithm. The automatically identified peaks are manually inspected by a graphical user interface program. Finally, a crystal position map is generated using a distance criterion based on these peaks. The proposed method is verified on the animal PET system with 48 detector blocks on a laptop with an Intel i7-5500U processor. The total runtime for whole system peak identification is 67.9 s. Results show that the automatic crystal identification has 99.98% and 99.09% accuracy for the peaks of the inner and outer layers of the whole system respectively. In conclusion, the proposed method is suitable for the dual-layer-offset lutetium based PET system to perform crystal identification instead of external radiation sources.

  17. Spectroscopic identification of binary and ternary surface complexes of Np(V) on gibbsite.

    Science.gov (United States)

    Gückel, Katharina; Rossberg, André; Müller, Katharina; Brendler, Vinzenz; Bernhard, Gert; Foerstendorf, Harald

    2013-12-17

    For the first time, detailed molecular information on the Np(V) sorption species on amorphous Al(OH)3 and crystalline gibbsite was obtained by in situ time-resolved Attenuated Total Reflection Fourier-Transform Infrared (ATR FT-IR) and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy. The results consistently demonstrate the formation of mononuclear inner sphere complexes of the NpO2(+) ion irrespective of the prevailing atmospheric condition. The impact of the presence of atmospheric equivalent added carbonate on the speciation in solution and on the surfaces becomes evident from vibrational data. While the 1:1 aqueous carbonato species (NpO2CO3(-)) was found to become predominant in the circumneutral pH range, it is most likely that this species is sorbed onto the gibbsite surface as a ternary inner sphere surface complex where the NpO2(+) moiety is directly coordinated to the functional groups of the gibbsite's surface. These findings are corroborated by results obtained from EXAFS spectroscopy providing further evidence for a bidentate coordination of the Np(V) ion on amorphous Al(OH)3. The identification of the Np(V) surface species on gibbsite constitutes a basic finding for a comprehensive description of the dissemination of neptunium in groundwater systems.

  18. Rapid Identification of Cortical Motor Areas in Rodents by High-Frequency Automatic Cortical Stimulation and Novel Motor Threshold Algorithm

    Directory of Open Access Journals (Sweden)

    Mitsuaki Takemi

    2017-10-01

    Full Text Available Cortical stimulation mapping is a valuable tool to test the functional organization of the motor cortex in both basic neurophysiology (e.g., elucidating the process of motor plasticity and clinical practice (e.g., before resecting brain tumors involving the motor cortex. However, compilation of motor maps based on the motor threshold (MT requires a large number of cortical stimulations and is therefore time consuming. Shortening the time for mapping may reduce stress on the subjects and unveil short-term plasticity mechanisms. In this study, we aimed to establish a cortical stimulation mapping procedure in which the time needed to identify a motor area is reduced to the order of minutes without compromising reliability. We developed an automatic motor mapping system that applies epidural cortical surface stimulations (CSSs through one-by-one of 32 micro-electrocorticographic electrodes while examining the muscles represented in a cortical region. The next stimulus intensity was selected according to previously evoked electromyographic responses in a closed-loop fashion. CSS was repeated at 4 Hz and electromyographic responses were submitted to a newly proposed algorithm estimating the MT with smaller number of stimuli with respect to traditional approaches. The results showed that in all tested rats (n = 12 the motor area maps identified by our novel mapping procedure (novel MT algorithm and 4-Hz CSS significantly correlated with the maps achieved by the conventional MT algorithm with 1-Hz CSS. The reliability of the both mapping methods was very high (intraclass correlation coefficients ≧0.8, while the time needed for the mapping was one-twelfth shorter with the novel method. Furthermore, the motor maps assessed by intracortical microstimulation and the novel CSS mapping procedure in two rats were compared and were also significantly correlated. Our novel mapping procedure that determined a cortical motor area within a few minutes could help

  19. Generation of synthetic surface electromyography signals under fatigue conditions for varying force inputs using feedback control algorithm.

    Science.gov (United States)

    Venugopal, G; Deepak, P; Ghosh, Diptasree M; Ramakrishnan, S

    2017-11-01

    Surface electromyography is a non-invasive technique used for recording the electrical activity of neuromuscular systems. These signals are random, complex and multi-component. There are several techniques to extract information about the force exerted by muscles during any activity. This work attempts to generate surface electromyography signals for various magnitudes of force under isometric non-fatigue and fatigue conditions using a feedback model. The model is based on existing current distribution, volume conductor relations, the feedback control algorithm for rate coding and generation of firing pattern. The result shows that synthetic surface electromyography signals are highly complex in both non-fatigue and fatigue conditions. Furthermore, surface electromyography signals have higher amplitude and lower frequency under fatigue condition. This model can be used to study the influence of various signal parameters under fatigue and non-fatigue conditions.

  20. Identification of Cell Surface Targets through Meta-analysis of Microarray Data

    Directory of Open Access Journals (Sweden)

    Henry Haeberle

    2012-07-01

    Full Text Available High-resolution image guidance for resection of residual tumor cells would enable more precise and complete excision for more effective treatment of cancers, such as medulloblastoma, the most common pediatric brain cancer. Numerous studies have shown that brain tumor patient outcomes correlate with the precision of resection. To enable guided resection with molecular specificity and cellular resolution, molecular probes that effectively delineate brain tumor boundaries are essential. Therefore, we developed a bioinformatics approach to analyze micro-array datasets for the identification of transcripts that encode candidate cell surface biomarkers that are highly enriched in medulloblastoma. The results identified 380 genes with greater than a two-fold increase in the expression in the medulloblastoma compared with that in the normal cerebellum. To enrich for targets with accessibility for extracellular molecular probes, we further refined this list by filtering it with gene ontology to identify genes with protein localization on, or within, the plasma membrane. To validate this meta-analysis, the top 10 candidates were evaluated with immunohistochemistry. We identified two targets, fibrillin 2 and EphA3, which specifically stain medulloblastoma. These results demonstrate a novel bioinformatics approach that successfully identified cell surface and extracellular candidate markers enriched in medulloblastoma versus adjacent cerebellum. These two proteins are high-value targets for the development of tumor-specific probes in medulloblastoma. This bioinformatics method has broad utility for the identification of accessible molecular targets in a variety of cancers and will enable probe development for guided resection.

  1. Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

    Directory of Open Access Journals (Sweden)

    Byung Eun Lee

    2014-09-01

    Full Text Available This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

  2. Surface quality monitoring for process control by on-line vibration analysis using an adaptive spline wavelet algorithm

    Science.gov (United States)

    Luo, G. Y.; Osypiw, D.; Irle, M.

    2003-05-01

    The dynamic behaviour of wood machining processes affects the surface finish quality of machined workpieces. In order to meet the requirements of increased production efficiency and improved product quality, surface quality information is needed for enhanced process control. However, current methods using high price devices or sophisticated designs, may not be suitable for industrial real-time application. This paper presents a novel approach of surface quality evaluation by on-line vibration analysis using an adaptive spline wavelet algorithm, which is based on the excellent time-frequency localization of B-spline wavelets. A series of experiments have been performed to extract the feature, which is the correlation between the relevant frequency band(s) of vibration with the change of the amplitude and the surface quality. The graphs of the experimental results demonstrate that the change of the amplitude in the selective frequency bands with variable resolution (linear and non-linear) reflects the quality of surface finish, and the root sum square of wavelet power spectrum is a good indication of surface quality. Thus, surface quality can be estimated and quantified at an average level in real time. The results can be used to regulate and optimize the machine's feed speed, maintaining a constant spindle motor speed during cutting. This will lead to higher level control and machining rates while keeping dimensional integrity and surface finish within specification.

  3. Effect of reconstruction algorithm on image quality and identification of ground-glass opacities and partly solid nodules on low-dose thin-section CT: Experimental study using chest phantom

    International Nuclear Information System (INIS)

    Koyama, Hisanobu; Ohno, Yoshiharu; Kono, Atsushi A.; Kusaka, Akiko; Konishi, Minoru; Yoshii, Masaru; Sugimura, Kazuro

    2010-01-01

    Purpose: The purpose of this study was to assess the influence of reconstruction algorithm on identification and image quality of ground-glass opacities (GGOs) and partly solid nodules on low-dose thin-section CT. Materials and methods: A chest CT phantom including simulated GGOs and partly solid nodules was scanned with five different tube currents and reconstructed by using standard (A) and newly developed (B) high-resolution reconstruction algorithms, followed by visually assessment of identification and image quality of GGOs and partly solid nodules by two chest radiologists. Inter-observer agreement, ROC analysis and ANOVA were performed to compare identification and image quality of each data set with those of the standard reference. The standard reference used 120 mA s in conjunction with reconstruction algorithm A. Results: Kappa values (κ) of overall identification and image qualities were substantial or almost perfect (0.60 < κ). Assessment of identification showed that area under the curve of 25 mA reconstructed with reconstruction algorithm A was significantly lower than that of standard reference (p < 0.05), while assessment of image quality indicated that 50 mA s reconstructed with reconstruction algorithm A and 25 mA s reconstructed with both reconstruction algorithms were significantly lower than standard reference (p < 0.05). Conclusion: Reconstruction algorithm may be an important factor for identification and image quality of ground-glass opacities and partly solid nodules on low-dose CT examination.

  4. Identification of surface species by vibrational normal mode analysis. A DFT study

    Science.gov (United States)

    Zhao, Zhi-Jian; Genest, Alexander; Rösch, Notker

    2017-10-01

    Infrared spectroscopy is an important experimental tool for identifying molecular species adsorbed on a metal surface that can be used in situ. Often vibrational modes in such IR spectra of surface species are assigned and identified by comparison with vibrational spectra of related (molecular) compounds of known structure, e. g., an organometallic cluster analogue. To check the validity of this strategy, we carried out a computational study where we compared the normal modes of three C2Hx species (x = 3, 4) in two types of systems, as adsorbates on the Pt(111) surface and as ligands in an organometallic cluster compound. The results of our DFT calculations reproduce the experimental observed frequencies with deviations of at most 50 cm-1. However, the frequencies of the C2Hx species in both types of systems have to be interpreted with due caution if the coordination mode is unknown. The comparative identification strategy works satisfactorily when the coordination mode of the molecular species (ethylidyne) is similar on the surface and in the metal cluster. However, large shifts are encountered when the molecular species (vinyl) exhibits different coordination modes on both types of substrates.

  5. A wavelet-based PWTD algorithm-accelerated time domain surface integral equation solver

    KAUST Repository

    Liu, Yang; Yucel, Abdulkadir C.; Gilbert, Anna C.; Bagci, Hakan; Michielssen, Eric

    2015-01-01

    © 2015 IEEE. The multilevel plane-wave time-domain (PWTD) algorithm allows for fast and accurate analysis of transient scattering from, and radiation by, electrically large and complex structures. When used in tandem with marching-on-in-time (MOT

  6. Identification of novel adhesins of M. tuberculosis H37Rv using integrated approach of multiple computational algorithms and experimental analysis.

    Directory of Open Access Journals (Sweden)

    Sanjiv Kumar

    Full Text Available Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA, Apa, Malate Synthase of M. tuberculosis have been identified using specific experimental interaction models based on the biological knowledge of the pathogen. In the present work, we carried out computational screening for adhesins of M. tuberculosis. We used an integrated computational approach using SPAAN for predicting adhesins, PSORTb, SubLoc and LocTree for extracellular localization, and BLAST for verifying non-similarity to human proteins. These steps are among the first of reverse vaccinology. Multiple claims and attacks from different algorithms were processed through argumentative approach. Additional filtration criteria included selection for proteins with low molecular weights and absence of literature reports. We examined binding potential of the selected proteins using an image based ELISA. The protein Rv2599 (membrane protein binds to human fibronectin, laminin and collagen. Rv3717 (N-acetylmuramoyl-L-alanine amidase and Rv0309 (L,D-transpeptidase bind to fibronectin and laminin. We report Rv2599 (membrane protein, Rv0309 and Rv3717 as novel adhesins of M. tuberculosis H37Rv. Our results expand the number of known adhesins of M. tuberculosis and suggest their regulated expression in different stages.

  7. A highly accurate dynamic contact angle algorithm for drops on inclined surface based on ellipse-fitting.

    Science.gov (United States)

    Xu, Z N; Wang, S Y

    2015-02-01

    To improve the accuracy in the calculation of dynamic contact angle for drops on the inclined surface, a significant number of numerical drop profiles on the inclined surface with different inclination angles, drop volumes, and contact angles are generated based on the finite difference method, a least-squares ellipse-fitting algorithm is used to calculate the dynamic contact angle. The influences of the above three factors are systematically investigated. The results reveal that the dynamic contact angle errors, including the errors of the left and right contact angles, evaluated by the ellipse-fitting algorithm tend to increase with inclination angle/drop volume/contact angle. If the drop volume and the solid substrate are fixed, the errors of the left and right contact angles increase with inclination angle. After performing a tremendous amount of computation, the critical dimensionless drop volumes corresponding to the critical contact angle error are obtained. Based on the values of the critical volumes, a highly accurate dynamic contact angle algorithm is proposed and fully validated. Within nearly the whole hydrophobicity range, it can decrease the dynamic contact angle error in the inclined plane method to less than a certain value even for different types of liquids.

  8. A Torque Error Compensation Algorithm for Surface Mounted Permanent Magnet Synchronous Machines with Respect to Magnet Temperature Variations

    Directory of Open Access Journals (Sweden)

    Chang-Seok Park

    2017-09-01

    Full Text Available This paper presents a torque error compensation algorithm for a surface mounted permanent magnet synchronous machine (SPMSM through real time permanent magnet (PM flux linkage estimation at various temperature conditions from medium to rated speed. As known, the PM flux linkage in SPMSMs varies with the thermal conditions. Since a maximum torque per ampere look up table, a control method used for copper loss minimization, is developed based on estimated PM flux linkage, variation of PM flux linkage results in undesired torque development of SPMSM drives. In this paper, PM flux linkage is estimated through a stator flux linkage observer and the torque error is compensated in real time using the estimated PM flux linkage. In this paper, the proposed torque error compensation algorithm is verified in simulation and experiment.

  9. A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

    2018-01-19

    The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the

  10. Floor Covering and Surface Identification for Assistive Mobile Robotic Real-Time Room Localization Application

    Directory of Open Access Journals (Sweden)

    Michael Gillham

    2013-12-01

    Full Text Available Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms’ flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification.

  11. Evaluation of Bending Strength of Carburized Gears Based on Inferential Identification of Principal Surface Layer Defects

    Science.gov (United States)

    Masuyama, Tomoya; Inoue, Katsumi; Yamanaka, Masashi; Kitamura, Kenichi; Saito, Tomoyuki

    High load capacity of carburized gears originates mainly from the hardened layer and induced residual stress. On the other hand, surface decarburization, which causes a nonmartensitic layer, and inclusions such as oxides and segregation act as latent defects which considerably reduce fatigue strength. In this connection, the authors have proposed a formula of strength evaluation by separately quantifying defect influence. However, the principal defect which limits strength of gears with several different defects remains unclarified. This study presents a method of inferential identification of principal defects based on test results of carburized gears made of SCM420 clean steel, gears with both an artificial notch and nonmartensitic layer at the tooth fillet, and so forth. It clarifies practical uses of presented methods, and strength of carburized gears can be evaluated by focusing on principal defect size.

  12. An algorithm for detecting trophic status (chlorophyll-a), cyanobacterial-dominance, surface scums and floating vegetation in inland and coastal waters

    CSIR Research Space (South Africa)

    Matthews, MW

    2012-09-01

    Full Text Available A novel algorithm is presented for detecting trophic status (chlorophyll-a), cyanobacterial blooms (cyano-blooms), surface scum and floating vegetation in coastal and inland waters using top-ofatmosphere data from the Medium Resolution Imaging...

  13. Interferometry with flexible point source array for measuring complex freeform surface and its design algorithm

    Science.gov (United States)

    Li, Jia; Shen, Hua; Zhu, Rihong; Gao, Jinming; Sun, Yue; Wang, Jinsong; Li, Bo

    2018-06-01

    The precision of the measurements of aspheric and freeform surfaces remains the primary factor restrict their manufacture and application. One effective means of measuring such surfaces involves using reference or probe beams with angle modulation, such as tilted-wave-interferometer (TWI). It is necessary to improve the measurement efficiency by obtaining the optimum point source array for different pieces before TWI measurements. For purpose of forming a point source array based on the gradients of different surfaces under test, we established a mathematical model describing the relationship between the point source array and the test surface. However, the optimal point sources are irregularly distributed. In order to achieve a flexible point source array according to the gradient of test surface, a novel interference setup using fiber array is proposed in which every point source can be independently controlled on and off. Simulations and the actual measurement examples of two different surfaces are given in this paper to verify the mathematical model. Finally, we performed an experiment of testing an off-axis ellipsoidal surface that proved the validity of the proposed interference system.

  14. Technical assessment of forest road network using Backmund and surface distribution algorithm in a hardwood forest of Hyrcanian zone

    Energy Technology Data Exchange (ETDEWEB)

    Parsakhoo, P.

    2016-07-01

    Aim of study: Corrected Backmund and Surface Distribution Algorithms (SDA) for analysis of forest road network are introduced and presented in this study. Research was carried out to compare road network performance between two districts in a hardwood forest. Area of study: Shast Kalateh forests, Iran. Materials and methods: In uncorrected Backmund algorithm, skidding distance was determined by calculating road density and spacing and then it was designed as Potential Area for Skidding Operations (PASO) in ArcGIS software. To correct this procedure, the skidding constraint areas were taken using GPS and then removed from PASO. In SDA, shortest perpendicular distance from geometrical center of timber compartments to road was measured at both districts. Main results: In corrected Backmund, forest openness in district I and II were 70.3% and 69.5%, respectively. Therefore, there was little difference in forest openness in the districts based on the uncorrected Backmund. In SDA, the mean distance from geometrical center of timber compartments to the roads of districts I and II were 199.45 and 149.31 meters, respectively. Forest road network distribution in district II was better than that of district I relating to SDA. Research highlights: It was concluded that uncorrected Backmund was not precise enough to assess forest road network, while corrected Backmund could exhibit a real PASO by removing skidding constraints. According to presented algorithms, forest road network performance in district II was better than district I. (Author)

  15. An algorithm to locate optimal bond breaking points on a potential energy surface for applications in mechanochemistry and catalysis.

    Science.gov (United States)

    Bofill, Josep Maria; Ribas-Ariño, Jordi; García, Sergio Pablo; Quapp, Wolfgang

    2017-10-21

    The reaction path of a mechanically induced chemical transformation changes under stress. It is well established that the force-induced structural changes of minima and saddle points, i.e., the movement of the stationary points on the original or stress-free potential energy surface, can be described by a Newton Trajectory (NT). Given a reactive molecular system, a well-fitted pulling direction, and a sufficiently large value of the force, the minimum configuration of the reactant and the saddle point configuration of a transition state collapse at a point on the corresponding NT trajectory. This point is called barrier breakdown point or bond breaking point (BBP). The Hessian matrix at the BBP has a zero eigenvector which coincides with the gradient. It indicates which force (both in magnitude and direction) should be applied to the system to induce the reaction in a barrierless process. Within the manifold of BBPs, there exist optimal BBPs which indicate what is the optimal pulling direction and what is the minimal magnitude of the force to be applied for a given mechanochemical transformation. Since these special points are very important in the context of mechanochemistry and catalysis, it is crucial to develop efficient algorithms for their location. Here, we propose a Gauss-Newton algorithm that is based on the minimization of a positively defined function (the so-called σ-function). The behavior and efficiency of the new algorithm are shown for 2D test functions and for a real chemical example.

  16. Land Surface Temperature and Emissivity Separation from Cross-Track Infrared Sounder Data with Atmospheric Reanalysis Data and ISSTES Algorithm

    Directory of Open Access Journals (Sweden)

    Yu-Ze Zhang

    2017-01-01

    Full Text Available The Cross-track Infrared Sounder (CrIS is one of the most advanced hyperspectral instruments and has been used for various atmospheric applications such as atmospheric retrievals and weather forecast modeling. However, because of the specific design purpose of CrIS, little attention has been paid to retrieving land surface parameters from CrIS data. To take full advantage of the rich spectral information in CrIS data to improve the land surface retrievals, particularly the acquisition of a continuous Land Surface Emissivity (LSE spectrum, this paper attempts to simultaneously retrieve a continuous LSE spectrum and the Land Surface Temperature (LST from CrIS data with the atmospheric reanalysis data and the Iterative Spectrally Smooth Temperature and Emissivity Separation (ISSTES algorithm. The results show that the accuracy of the retrieved LSEs and LST is comparable with the current land products. The overall differences of the LST and LSE retrievals are approximately 1.3 K and 1.48%, respectively. However, the LSEs in our study can be provided as a continuum spectrum instead of the single-channel values in traditional products. The retrieved LST and LSEs now can be better used to further analyze the surface properties or improve the retrieval of atmospheric parameters.

  17. A DOUBLE-RING ALGORITHM FOR MODELING SOLAR ACTIVE REGIONS: UNIFYING KINEMATIC DYNAMO MODELS AND SURFACE FLUX-TRANSPORT SIMULATIONS

    International Nuclear Information System (INIS)

    Munoz-Jaramillo, Andres; Martens, Petrus C. H.; Nandy, Dibyendu; Yeates, Anthony R.

    2010-01-01

    The emergence of tilted bipolar active regions (ARs) and the dispersal of their flux, mediated via processes such as diffusion, differential rotation, and meridional circulation, is believed to be responsible for the reversal of the Sun's polar field. This process (commonly known as the Babcock-Leighton mechanism) is usually modeled as a near-surface, spatially distributed α-effect in kinematic mean-field dynamo models. However, this formulation leads to a relationship between polar field strength and meridional flow speed which is opposite to that suggested by physical insight and predicted by surface flux-transport simulations. With this in mind, we present an improved double-ring algorithm for modeling the Babcock-Leighton mechanism based on AR eruption, within the framework of an axisymmetric dynamo model. Using surface flux-transport simulations, we first show that an axisymmetric formulation-which is usually invoked in kinematic dynamo models-can reasonably approximate the surface flux dynamics. Finally, we demonstrate that our treatment of the Babcock-Leighton mechanism through double-ring eruption leads to an inverse relationship between polar field strength and meridional flow speed as expected, reconciling the discrepancy between surface flux-transport simulations and kinematic dynamo models.

  18. Assessment of Polarization Effect on Efficiency of Levenberg-Marquardt Algorithm in Case of Thin Atmosphere over Black Surface

    Science.gov (United States)

    Korkin, S.; Lyapustin, A.

    2012-12-01

    The Levenberg-Marquardt algorithm [1, 2] provides a numerical iterative solution to the problem of minimization of a function over a space of its parameters. In our work, the Levenberg-Marquardt algorithm retrieves optical parameters of a thin (single scattering) plane parallel atmosphere irradiated by collimated infinitely wide monochromatic beam of light. Black ground surface is assumed. Computational accuracy, sensitivity to the initial guess and the presence of noise in the signal, and other properties of the algorithm are investigated in scalar (using intensity only) and vector (including polarization) modes. We consider an atmosphere that contains a mixture of coarse and fine fractions. Following [3], the fractions are simulated using Henyey-Greenstein model. Though not realistic, this assumption is very convenient for tests [4, p.354]. In our case it yields analytical evaluation of Jacobian matrix. Assuming the MISR geometry of observation [5] as an example, the average scattering cosines and the ratio of coarse and fine fractions, the atmosphere optical depth, and the single scattering albedo, are the five parameters to be determined numerically. In our implementation of the algorithm, the system of five linear equations is solved using the fast Cramer's rule [6]. A simple subroutine developed by the authors, makes the algorithm independent from external libraries. All Fortran 90/95 codes discussed in the presentation will be available immediately after the meeting from sergey.v.korkin@nasa.gov by request. [1]. Levenberg K, A method for the solution of certain non-linear problems in least squares, Quarterly of Applied Mathematics, 1944, V.2, P.164-168. [2]. Marquardt D, An algorithm for least-squares estimation of nonlinear parameters, Journal on Applied Mathematics, 1963, V.11, N.2, P.431-441. [3]. Hovenier JW, Multiple scattering of polarized light in planetary atmospheres. Astronomy and Astrophysics, 1971, V.13, P.7 - 29. [4]. Mishchenko MI, Travis LD

  19. Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

    Science.gov (United States)

    Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

    2017-12-01

    Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

  20. Spatial assessment and source identification of heavy metals pollution in surface water using several chemometric techniques.

    Science.gov (United States)

    Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Zain, Sharifuddin Md; Habir, Nur Liyana Abdul; Retnam, Ananthy; Kamaruddin, Mohd Khairul Amri; Umar, Roslan; Azid, Azman

    2016-05-15

    This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time. The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Identification of distant drug off-targets by direct superposition of binding pocket surfaces.

    Science.gov (United States)

    Schumann, Marcel; Armen, Roger S

    2013-01-01

    Correctly predicting off-targets for a given molecular structure, which would have the ability to bind a large range of ligands, is both particularly difficult and important if they share no significant sequence or fold similarity with the respective molecular target ("distant off-targets"). A novel approach for identification of off-targets by direct superposition of protein binding pocket surfaces is presented and applied to a set of well-studied and highly relevant drug targets, including representative kinases and nuclear hormone receptors. The entire Protein Data Bank is searched for similar binding pockets and convincing distant off-target candidates were identified that share no significant sequence or fold similarity with the respective target structure. These putative target off-target pairs are further supported by the existence of compounds that bind strongly to both with high topological similarity, and in some cases, literature examples of individual compounds that bind to both. Also, our results clearly show that it is possible for binding pockets to exhibit a striking surface similarity, while the respective off-target shares neither significant sequence nor significant fold similarity with the respective molecular target ("distant off-target").

  2. Evaluation of sea-surface photosynthetically available radiation algorithms under various sky conditions and solar elevations.

    Science.gov (United States)

    Somayajula, Srikanth Ayyala; Devred, Emmanuel; Bélanger, Simon; Antoine, David; Vellucci, V; Babin, Marcel

    2018-04-20

    In this study, we report on the performance of satellite-based photosynthetically available radiation (PAR) algorithms used in published oceanic primary production models. The performance of these algorithms was evaluated using buoy observations under clear and cloudy skies, and for the particular case of low sun angles typically encountered at high latitudes or at moderate latitudes in winter. The PAR models consisted of (i) the standard one from the NASA-Ocean Biology Processing Group (OBPG), (ii) the Gregg and Carder (GC) semi-analytical clear-sky model, and (iii) look-up-tables based on the Santa Barbara DISORT atmospheric radiative transfer (SBDART) model. Various combinations of atmospheric inputs, empirical cloud corrections, and semi-analytical irradiance models yielded a total of 13 (11 + 2 developed in this study) different PAR products, which were compared with in situ measurements collected at high frequency (15 min) at a buoy site in the Mediterranean Sea (the "BOUée pour l'acquiSition d'une Série Optique à Long termE," or, "BOUSSOLE" site). An objective ranking method applied to the algorithm results indicated that seven PAR products out of 13 were well in agreement with the in situ measurements. Specifically, the OBPG method showed the best overall performance with a root mean square difference (RMSD) (bias) of 19.7% (6.6%) and 10% (6.3%) followed by the look-up-table method with a RMSD (bias) of 25.5% (6.8%) and 9.6% (2.6%) at daily and monthly scales, respectively. Among the four methods based on clear-sky PAR empirically corrected for cloud cover, the Dobson and Smith method consistently underestimated daily PAR while the Budyko formulation overestimated daily PAR. Empirically cloud-corrected methods using cloud fraction (CF) performed better under quasi-clear skies (CF0.7), however, all methods showed larger RMSD differences (biases) ranging between 32% and 80.6% (-54.5%-8.7%). Finally, three methods tested for low sun elevations revealed

  3. An Algorithm for Surface Current Retrieval from X-band Marine Radar Images

    Directory of Open Access Journals (Sweden)

    Chengxi Shen

    2015-06-01

    Full Text Available In this paper, a novel current inversion algorithm from X-band marine radar images is proposed. The routine, for which deep water is assumed, begins with 3-D FFT of the radar image sequence, followed by the extraction of the dispersion shell from the 3-D image spectrum. Next, the dispersion shell is converted to a polar current shell (PCS using a polar coordinate transformation. After removing outliers along each radial direction of the PCS, a robust sinusoidal curve fitting is applied to the data points along each circumferential direction of the PCS. The angle corresponding to the maximum of the estimated sinusoid function is determined to be the current direction, and the amplitude of this sinusoidal function is the current speed. For validation, the algorithm is tested against both simulated radar images and field data collected by a vertically-polarized X-band system and ground-truthed with measurements from an acoustic Doppler current profiler (ADCP. From the field data, it is observed that when the current speed is less than 0.5 m/s, the root mean square differences between the radar-derived and the ADCP-measured current speed and direction are 7.3 cm/s and 32.7°, respectively. The results indicate that the proposed procedure, unlike most existing current inversion schemes, is not susceptible to high current speeds and circumvents the need to consider aliasing. Meanwhile, the relatively low computational cost makes it an excellent choice in practical marine applications.

  4. Comparing experts and novices in Martian surface feature change detection and identification

    Science.gov (United States)

    Wardlaw, Jessica; Sprinks, James; Houghton, Robert; Muller, Jan-Peter; Sidiropoulos, Panagiotis; Bamford, Steven; Marsh, Stuart

    2018-02-01

    Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided ;expert; data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who

  5. Two-sheet surface rebinning algorithm for real time cone beam tomography

    Energy Technology Data Exchange (ETDEWEB)

    Betcke, Marta M. [University College London (United Kingdom). Dept. of Computer Science; Lionheart, William R.B. [Manchester Univ. (United Kingdom). School of Mathematics

    2011-07-01

    The Rapiscan RTT80 is an example of a fast cone beam CT scanner in which the X-ray sources are fixed on a circle while the detector rows are offset axially on one side of the sources. Reconstruction for this offset truncation presents a new challenge and we propose a method using rebinning to an optimal two-sheet surface. (orig.)

  6. Identification of near surface events using athermal phonon signals in low temperature Ge bolometers for the EDELWEISS experiment

    International Nuclear Information System (INIS)

    Marnieros, S.; Juillard, A.; Berge, L.; Collin, S.; Dumoulin, L.

    2004-01-01

    We present a study of a 100 g low temperature Ge detector, allowing identification of surface events down to the energy threshold. The bolometer is fitted with segmented electrodes and two NbSi Anderson insulator thermometric layers. Analysis of the athermal signals amplitudes allows us to identify and reject all events occurring in the first millimeter under the electrodes

  7. Identification of near surface events using athermal phonon signals in low temperature Ge bolometers for the EDELWEISS experiment

    Energy Technology Data Exchange (ETDEWEB)

    Marnieros, S. E-mail: marniero@csnsm.in2p3.fr; Juillard, A.; Berge, L.; Collin, S.; Dumoulin, L

    2004-03-11

    We present a study of a 100 g low temperature Ge detector, allowing identification of surface events down to the energy threshold. The bolometer is fitted with segmented electrodes and two NbSi Anderson insulator thermometric layers. Analysis of the athermal signals amplitudes allows us to identify and reject all events occurring in the first millimeter under the electrodes.

  8. Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

    Directory of Open Access Journals (Sweden)

    Z. Q. Peng

    2016-11-01

    Full Text Available Evapotranspiration (ET plays an important role in surface–atmosphere interactions and can be monitored using remote sensing data. However, surface heterogeneity, including the inhomogeneity of landscapes and surface variables, significantly affects the accuracy of ET estimated from satellite data. The objective of this study is to assess and reduce the uncertainties resulting from surface heterogeneity in remotely sensed ET using Chinese HJ-1B satellite data, which is of 30 m spatial resolution in VIS/NIR bands and 300 m spatial resolution in the thermal-infrared (TIR band. A temperature-sharpening and flux aggregation scheme (TSFA was developed to obtain accurate heat fluxes from the HJ-1B satellite data. The IPUS (input parameter upscaling and TRFA (temperature resampling and flux aggregation methods were used to compare with the TSFA in this study. The three methods represent three typical schemes used to handle mixed pixels from the simplest to the most complex. IPUS handles all surface variables at coarse resolution of 300 m in this study, TSFA handles them at 30 m resolution, and TRFA handles them at 30 and 300 m resolution, which depends on the actual spatial resolution. Analyzing and comparing the three methods can help us to get a better understanding of spatial-scale errors in remote sensing of surface heat fluxes. In situ data collected during HiWATER-MUSOEXE (Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces of the Heihe Watershed Allied Telemetry Experimental Research were used to validate and analyze the methods. ET estimated by TSFA exhibited the best agreement with in situ observations, and the footprint validation results showed that the R2, MBE, and RMSE values of the sensible heat flux (H were 0.61, 0.90, and 50.99 W m−2, respectively, and those for the latent heat flux (LE were 0.82, −20.54, and 71.24 W m−2, respectively. IPUS yielded the largest errors

  9. Land Surface Temperature Retrieval from MODIS Data by Integrating Regression Models and the Genetic Algorithm in an Arid Region

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2014-06-01

    Full Text Available The land surface temperature (LST is one of the most important parameters of surface-atmosphere interactions. Methods for retrieving LSTs from satellite remote sensing data are beneficial for modeling hydrological, ecological, agricultural and meteorological processes on Earth’s surface. Many split-window (SW algorithms, which can be applied to satellite sensors with two adjacent thermal channels located in the atmospheric window between 10 μm and 12 μm, require auxiliary atmospheric parameters (e.g., water vapor content. In this research, the Heihe River basin, which is one of the most arid regions in China, is selected as the study area. The Moderate-resolution Imaging Spectroradiometer (MODIS is selected as a test case. The Global Data Assimilation System (GDAS atmospheric profiles of the study area are used to generate the training dataset through radiative transfer simulation. Significant correlations between the atmospheric upwelling radiance in MODIS channel 31 and the other three atmospheric parameters, including the transmittance in channel 31 and the transmittance and upwelling radiance in channel 32, are trained based on the simulation dataset and formulated with three regression models. Next, the genetic algorithm is used to estimate the LST. Validations of the RM-GA method are based on the simulation dataset generated from in situ measured radiosonde profiles and GDAS atmospheric profiles, the in situ measured LSTs, and a pair of daytime and nighttime MOD11A1 products in the study area. The results demonstrate that RM-GA has a good ability to estimate the LSTs directly from the MODIS data without any auxiliary atmospheric parameters. Although this research is for local application in the Heihe River basin, the findings and proposed method can easily be extended to other satellite sensors and regions with arid climates and high elevations.

  10. Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

    Science.gov (United States)

    Fisz, Jacek J

    2006-12-07

    The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi

  11. The Novel Artificial Intelligence Based Sub-Surface Inclusion Detection Device and Algorithm

    Directory of Open Access Journals (Sweden)

    Jong-Ha LEE

    2017-05-01

    Full Text Available We design, implement, and test a novel tactile elasticity imaging sensor to detect the elastic modulus of a contacted object. Emulating a human finger, a multi-layer polydimethylsiloxane waveguide has been fabricated as the sensing probe. The light is illuminated under the critical angle to totally reflect within the flexible and transparent waveguide. When a waveguide is compressed by an object, the contact area of the waveguide deforms and causes the light to scatter. The scattered light is captured by a high resolution camera. Multiple images are taken from slightly different loading values. The distributed forces have been estimated using the integrated pixel values of diffused lights. The displacements of the contacted object deformation have been estimated by matching the series of tactile images. For this purpose, a novel pattern matching algorithm is developed. The salient feature of this sensor is that it is capable of measuring the absolute elastic modulus value of soft materials without additional measurement units. The measurements were validated by comparing the measured elasticity of the commercial rubber samples with the known elasticity. The evaluation results showed that this type of sensor can measure elasticity within ±5.38 %.

  12. Self-Assembled Nanocube-Based Plasmene Nanosheets as Soft Surface-Enhanced Raman Scattering Substrates toward Direct Quantitative Drug Identification on Surfaces.

    Science.gov (United States)

    Si, Kae Jye; Guo, Pengzhen; Shi, Qianqian; Cheng, Wenlong

    2015-05-19

    We report on self-assembled nanocube-based plasmene nanosheets as new surface-enhanced Raman scattering (SERS) substrates toward direct identification of a trace amount of drugs sitting on topologically complex real-world surfaces. The uniform nanocube arrays (superlattices) led to low spatial SERS signal variances (∼2%). Unlike conventional SERS substrates which are based on rigid nanostructured metals, our plasmene nanosheets are mechanically soft and optically semitransparent, enabling conformal attachment to real-world solid surfaces such as banknotes for direct SERS identification of drugs. Our plasmene nanosheets were able to detect benzocaine overdose down to a parts-per-billion (ppb) level with an excellent linear relationship (R(2) > 0.99) between characteristic peak intensity and concentration. On banknote surfaces, a detection limit of ∼0.9 × 10(-6) g/cm(2) benzocaine could be achieved. Furthermore, a few other drugs could also be identified, even in their binary mixtures with our plasmene nanosheets. Our experimental results clearly show that our plasmene sheets represent a new class of unique SERS substrates, potentially serving as a versatile platform for real-world forensic drug identification.

  13. An Improved Global Harmony Search Algorithm for the Identification of Nonlinear Discrete-Time Systems Based on Volterra Filter Modeling

    Directory of Open Access Journals (Sweden)

    Zongyan Li

    2016-01-01

    Full Text Available This paper describes an improved global harmony search (IGHS algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.

  14. Neuro-diffuse algorithm for neutronic power identification of TRIGA Mark III reactor; Algoritmo neuro-difuso para la identificacion de la potencia neutronica del reactor Triga Mark III

    Energy Technology Data Exchange (ETDEWEB)

    Rojas R, E.; Benitez R, J. S. [Instituto Tecnologico de Toluca, Division de Estudios de Posgrado e Investigacion, Av. Tecnologico s/n, Ex-Rancho La Virgen, 50140 Metepec, Estado de Mexico (Mexico); Segovia de los Rios, J. A.; Rivero G, T. [ININ, Gerencia de Ciencias Aplicadas, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)], e-mail: jorge.benitez@inin.gob.mx

    2009-10-15

    In this work are presented the results of design and implementation of an algorithm based on diffuse logic systems and neural networks like method of neutronic power identification of TRIGA Mark III reactor. This algorithm uses the punctual kinetics equation as data generator of training, a cost function and a learning stage based on the descending gradient algorithm allow to optimize the parameters of membership functions of a diffuse system. Also, a series of criteria like part of the initial conditions of training algorithm are established. These criteria according to the carried out simulations show a quick convergence of neutronic power estimated from the first iterations. (Author)

  15. Remote sensing algorithm for sea surface CO2 in the Baltic Sea

    Science.gov (United States)

    Parard, G.; Charantonis, A. A.; Rutgerson, A.

    2014-08-01

    Studies of coastal seas in Europe have brought forth the high variability in the CO2 system. This high variability, generated by the complex mechanisms driving the CO2 fluxes makes their accurate estimation an arduous task. This is more pronounced in the Baltic Sea, where the mechanisms driving the fluxes have not been as highly detailed as in the open oceans. In adition, the joint availability of in-situ measurements of CO2 and of sea-surface satellite data is limited in the area. In this paper, a combination of two existing methods (Self-Organizing-Maps and Multiple Linear regression) is used to estimate ocean surface pCO2 in the Baltic Sea from remotely sensed surface temperature, chlorophyll, coloured dissolved organic matter, net primary production and mixed layer depth. The outputs of this research have an horizontal resolution of 4 km, and cover the period from 1998 to 2011. The reconstructed pCO2 values over the validation data set have a correlation of 0.93 with the in-situ measurements, and a root mean square error is of 38 μatm. The removal of any of the satellite parameters degraded this reconstruction of the CO2 flux, and we chose therefore to complete any missing data through statistical imputation. The CO2 maps produced by this method also provide a confidence level of the reconstruction at each grid point. The results obtained are encouraging given the sparsity of available data and we expect to be able to produce even more accurate reconstructions in the coming years, in view of the predicted acquisitions of new data.

  16. Iterative algorithm for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution

    Science.gov (United States)

    Quan, Haiyang; Wu, Fan; Hou, Xi

    2015-10-01

    New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.

  17. Solvent-assisted multistage nonequilibrium electron transfer in rigid supramolecular systems: Diabatic free energy surfaces and algorithms for numerical simulations

    Science.gov (United States)

    Feskov, Serguei V.; Ivanov, Anatoly I.

    2018-03-01

    An approach to the construction of diabatic free energy surfaces (FESs) for ultrafast electron transfer (ET) in a supramolecule with an arbitrary number of electron localization centers (redox sites) is developed, supposing that the reorganization energies for the charge transfers and shifts between all these centers are known. Dimensionality of the coordinate space required for the description of multistage ET in this supramolecular system is shown to be equal to N - 1, where N is the number of the molecular centers involved in the reaction. The proposed algorithm of FES construction employs metric properties of the coordinate space, namely, relation between the solvent reorganization energy and the distance between the two FES minima. In this space, the ET reaction coordinate zn n' associated with electron transfer between the nth and n'th centers is calculated through the projection to the direction, connecting the FES minima. The energy-gap reaction coordinates zn n' corresponding to different ET processes are not in general orthogonal so that ET between two molecular centers can create nonequilibrium distribution, not only along its own reaction coordinate but along other reaction coordinates too. This results in the influence of the preceding ET steps on the kinetics of the ensuing ET. It is important for the ensuing reaction to be ultrafast to proceed in parallel with relaxation along the ET reaction coordinates. Efficient algorithms for numerical simulation of multistage ET within the stochastic point-transition model are developed. The algorithms are based on the Brownian simulation technique with the recrossing-event detection procedure. The main advantages of the numerical method are (i) its computational complexity is linear with respect to the number of electronic states involved and (ii) calculations can be naturally parallelized up to the level of individual trajectories. The efficiency of the proposed approach is demonstrated for a model

  18. Identification of hip surface arthroplasty failures with TcSC/TcmDP radionuclide imaging

    International Nuclear Information System (INIS)

    Thomas, B.J.; Amstutz, H.C.; Mai, L.L.; Webber, M.M.

    1982-01-01

    The roentgenographic identification of femoral component loosening after hip surface arthroplasty is often impossible because the metallic femoral component obscures the bone-cement interface. The use of combined technetium sulfur colloid and technetium methylene diphosphonate radionuclide imaging has been especially useful in the diagnosis of loosening. In 40 patients, follow-up combined TcSC and TcmDP scans at an average of three, nine, and 27 months postoperation revealed significant differences in the isotope uptakes in patients who had loose prostheses compared with those without complications. Scans were evaluated by first dividing them into eight anatomical regions and then rating the uptake in each region or 'zone' on a five-point scale. Results were compared using the Student's t-test and differences were noted between normal controls and patients who had femoral component loosening. Combining both TcSC and TcmDP studies increased the statistical significance obtained when comparing patients who had complications to those in the control group

  19. Identification and Quantification of Celery Allergens Using Fiber Optic Surface Plasmon Resonance PCR.

    Science.gov (United States)

    Daems, Devin; Peeters, Bernd; Delport, Filip; Remans, Tony; Lammertyn, Jeroen; Spasic, Dragana

    2017-07-31

    Abstract : Accurate identification and quantification of allergens is key in healthcare, biotechnology and food quality and safety. Celery ( Apium graveolens ) is one of the most important elicitors of food allergic reactions in Europe. Currently, the golden standards to identify, quantify and discriminate celery in a biological sample are immunoassays and two-step molecular detection assays in which quantitative PCR (qPCR) is followed by a high-resolution melting analysis (HRM). In order to provide a DNA-based, rapid and simple detection method suitable for one-step quantification, a fiber optic PCR melting assay (FO-PCR-MA) was developed to determine different concentrations of celery DNA (1 pM-0.1 fM). The presented method is based on the hybridization and melting of DNA-coated gold nanoparticles to the FO sensor surface in the presence of the target gene (mannitol dehydrogenase, Mtd ). The concept was not only able to reveal the presence of celery DNA, but also allowed for the cycle-to-cycle quantification of the target sequence through melting analysis. Furthermore, the developed bioassay was benchmarked against qPCR followed by HRM, showing excellent agreement ( R ² = 0.96). In conclusion, this innovative and sensitive diagnostic test could further improve food quality control and thus have a large impact on allergen induced healthcare problems.

  20. Identification and Quantification of Celery Allergens Using Fiber Optic Surface Plasmon Resonance PCR

    Directory of Open Access Journals (Sweden)

    Devin Daems

    2017-07-01

    Full Text Available Abstract: Accurate identification and quantification of allergens is key in healthcare, biotechnology and food quality and safety. Celery (Apium graveolens is one of the most important elicitors of food allergic reactions in Europe. Currently, the golden standards to identify, quantify and discriminate celery in a biological sample are immunoassays and two-step molecular detection assays in which quantitative PCR (qPCR is followed by a high-resolution melting analysis (HRM. In order to provide a DNA-based, rapid and simple detection method suitable for one-step quantification, a fiber optic PCR melting assay (FO-PCR-MA was developed to determine different concentrations of celery DNA (1 pM–0.1 fM. The presented method is based on the hybridization and melting of DNA-coated gold nanoparticles to the FO sensor surface in the presence of the target gene (mannitol dehydrogenase, Mtd. The concept was not only able to reveal the presence of celery DNA, but also allowed for the cycle-to-cycle quantification of the target sequence through melting analysis. Furthermore, the developed bioassay was benchmarked against qPCR followed by HRM, showing excellent agreement (R2 = 0.96. In conclusion, this innovative and sensitive diagnostic test could further improve food quality control and thus have a large impact on allergen induced healthcare problems.

  1. Identification of Patients with Statin Intolerance in a Managed Care Plan: A Comparison of 2 Claims-Based Algorithms.

    Science.gov (United States)

    Bellows, Brandon K; Sainski-Nguyen, Amy M; Olsen, Cody J; Boklage, Susan H; Charland, Scott; Mitchell, Matthew P; Brixner, Diana I

    2017-09-01

    While statins are safe and efficacious, some patients may experience statin intolerance or treatment-limiting adverse events. Identifying patients with statin intolerance may allow optimal management of cardiovascular event risk through other strategies. Recently, an administrative claims data (ACD) algorithm was developed to identify patients with statin intolerance and validated against electronic medical records. However, how this algorithm compared with perceptions of statin intolerance by integrated delivery networks remains largely unknown. To determine the concurrent validity of an algorithm developed by a regional integrated delivery network multidisciplinary panel (MP) and a published ACD algorithm in identifying patients with statin intolerance. The MP consisted of 3 physicians and 2 pharmacists with expertise in cardiology, internal medicine, and formulary management. The MP algorithm used pharmacy and medical claims to identify patients with statin intolerance, classifying them as having statin intolerance if they met any of the following criteria: (a) medical claim for rhabdomyolysis, (b) medical claim for muscle weakness, (c) an outpatient medical claim for creatinine kinase assay, (d) fills for ≥ 2 different statins excluding dose increases, (e) decrease in statin dose, or (f) discontinuation of a statin with a subsequent fill for a nonstatin lipid-lowering therapy. The validated ACD algorithm identified statin intolerance as absolute intolerance with rhabdomyolysis; absolute intolerance without rhabdomyolysis (i.e., other adverse events); or as dose titration intolerance. Adult patients (aged ≥ 18 years) from the integrated delivery network with at least 1 prescription fill for a statin between January 1, 2011, and December 31, 2012 (first fill defined the index date) were identified. Patients with ≥ 1 year pre- and ≥ 2 years post-index continuous enrollment and no statin prescription fills in the pre-index period were included. The MP and

  2. Online Surface Defect Identification of Cold Rolled Strips Based on Local Binary Pattern and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2018-03-01

    Full Text Available In the production of cold-rolled strip, the strip surface may suffer from various defects which need to be detected and identified using an online inspection system. The system is equipped with high-speed and high-resolution cameras to acquire images from the moving strip surface. Features are then extracted from the images and are used as inputs of a pre-trained classifier to identify the type of defect. New types of defect often appear in production. At this point the pre-trained classifier needs to be quickly retrained and deployed in seconds to meet the requirement of the online identification of all defects in the environment of a continuous production line. Therefore, the method for extracting the image features and the training for the classification model should be automated and fast enough, normally within seconds. This paper presents our findings in investigating the computational and classification performance of various feature extraction methods and classification models for the strip surface defect identification. The methods include Scale Invariant Feature Transform (SIFT, Speeded Up Robust Features (SURF and Local Binary Patterns (LBP. The classifiers we have assessed include Back Propagation (BP neural network, Support Vector Machine (SVM and Extreme Learning Machine (ELM. By comparing various combinations of different feature extraction and classification methods, our experiments show that the hybrid method of LBP for feature extraction and ELM for defect classification results in less training and identification time with higher classification accuracy, which satisfied online real-time identification.

  3. A Semiautomated Multilayer Picking Algorithm for Ice-sheet Radar Echograms Applied to Ground-Based Near-Surface Data

    Science.gov (United States)

    Onana, Vincent De Paul; Koenig, Lora Suzanne; Ruth, Julia; Studinger, Michael; Harbeck, Jeremy P.

    2014-01-01

    Snow accumulation over an ice sheet is the sole mass input, making it a primary measurement for understanding the past, present, and future mass balance. Near-surface frequency-modulated continuous-wave (FMCW) radars image isochronous firn layers recording accumulation histories. The Semiautomated Multilayer Picking Algorithm (SAMPA) was designed and developed to trace annual accumulation layers in polar firn from both airborne and ground-based radars. The SAMPA algorithm is based on the Radon transform (RT) computed by blocks and angular orientations over a radar echogram. For each echogram's block, the RT maps firn segmented-layer features into peaks, which are picked using amplitude and width threshold parameters of peaks. A backward RT is then computed for each corresponding block, mapping the peaks back into picked segmented-layers. The segmented layers are then connected and smoothed to achieve a final layer pick across the echogram. Once input parameters are trained, SAMPA operates autonomously and can process hundreds of kilometers of radar data picking more than 40 layers. SAMPA final pick results and layer numbering still require a cursory manual adjustment to correct noncontinuous picks, which are likely not annual, and to correct for inconsistency in layer numbering. Despite the manual effort to train and check SAMPA results, it is an efficient tool for picking multiple accumulation layers in polar firn, reducing time over manual digitizing efforts. The trackability of good detected layers is greater than 90%.

  4. Optimisation of process parameters on thin shell part using response surface methodology (RSM) and genetic algorithm (GA)

    Science.gov (United States)

    Faiz, J. M.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

    2017-09-01

    This study conducts the simulation on optimisation of injection moulding process parameters using Autodesk Moldflow Insight (AMI) software. This study has applied some process parameters which are melt temperature, mould temperature, packing pressure, and cooling time in order to analyse the warpage value of the part. Besides, a part has been selected to be studied which made of Polypropylene (PP). The combination of the process parameters is analysed using Analysis of Variance (ANOVA) and the optimised value is obtained using Response Surface Methodology (RSM). The RSM as well as Genetic Algorithm are applied in Design Expert software in order to minimise the warpage value. The outcome of this study shows that the warpage value improved by using RSM and GA.

  5. Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2015-04-01

    Full Text Available As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST retrieved from Thermal Infra-Red (TIR images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD and absolute average difference (AAD are smaller than 1.7 K, where the correlation coefficient (CC and root-mean-square error (RMSE are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

  6. Detecting wood surface defects with fusion algorithm of visual saliency and local threshold segmentation

    Science.gov (United States)

    Wang, Xuejuan; Wu, Shuhang; Liu, Yunpeng

    2018-04-01

    This paper presents a new method for wood defect detection. It can solve the over-segmentation problem existing in local threshold segmentation methods. This method effectively takes advantages of visual saliency and local threshold segmentation. Firstly, defect areas are coarsely located by using spectral residual method to calculate global visual saliency of them. Then, the threshold segmentation of maximum inter-class variance method is adopted for positioning and segmenting the wood surface defects precisely around the coarse located areas. Lastly, we use mathematical morphology to process the binary images after segmentation, which reduces the noise and small false objects. Experiments on test images of insect hole, dead knot and sound knot show that the method we proposed obtains ideal segmentation results and is superior to the existing segmentation methods based on edge detection, OSTU and threshold segmentation.

  7. An algorithm for analytical solution of basic problems featuring elastostatic bodies with cavities and surface flaws

    Science.gov (United States)

    Penkov, V. B.; Levina, L. V.; Novikova, O. S.; Shulmin, A. S.

    2018-03-01

    Herein we propose a methodology for structuring a full parametric analytical solution to problems featuring elastostatic media based on state-of-the-art computing facilities that support computerized algebra. The methodology includes: direct and reverse application of P-Theorem; methods of accounting for physical properties of media; accounting for variable geometrical parameters of bodies, parameters of boundary states, independent parameters of volume forces, and remote stress factors. An efficient tool to address the task is the sustainable method of boundary states originally designed for the purposes of computerized algebra and based on the isomorphism of Hilbertian spaces of internal states and boundary states of bodies. We performed full parametric solutions of basic problems featuring a ball with a nonconcentric spherical cavity, a ball with a near-surface flaw, and an unlimited medium with two spherical cavities.

  8. Cuckoo Search Algorithm with Lévy Flights for Global-Support Parametric Surface Approximation in Reverse Engineering

    Directory of Open Access Journals (Sweden)

    Andrés Iglesias

    2018-03-01

    Full Text Available This paper concerns several important topics of the Symmetry journal, namely, computer-aided design, computational geometry, computer graphics, visualization, and pattern recognition. We also take advantage of the symmetric structure of the tensor-product surfaces, where the parametric variables u and v play a symmetric role in shape reconstruction. In this paper we address the general problem of global-support parametric surface approximation from clouds of data points for reverse engineering applications. Given a set of measured data points, the approximation is formulated as a nonlinear continuous least-squares optimization problem. Then, a recent metaheuristics called Cuckoo Search Algorithm (CSA is applied to compute all relevant free variables of this minimization problem (namely, the data parameters and the surface poles. The method includes the iterative generation of new solutions by using the Lévy flights to promote the diversity of solutions and prevent stagnation. A critical advantage of this method is its simplicity: the CSA requires only two parameters, many fewer than any other metaheuristic approach, so the parameter tuning becomes a very easy task. The method is also simple to understand and easy to implement. Our approach has been applied to a benchmark of three illustrative sets of noisy data points corresponding to surfaces exhibiting several challenging features. Our experimental results show that the method performs very well even for the cases of noisy and unorganized data points. Therefore, the method can be directly used for real-world applications for reverse engineering without further pre/post-processing. Comparative work with the most classical mathematical techniques for this problem as well as a recent modification of the CSA called Improved CSA (ICSA is also reported. Two nonparametric statistical tests show that our method outperforms the classical mathematical techniques and provides equivalent results to ICSA

  9. The Parallel SBAS-DInSAR algorithm: an effective and scalable tool for Earth's surface displacement retrieval

    Science.gov (United States)

    Zinno, Ivana; De Luca, Claudio; Elefante, Stefano; Imperatore, Pasquale; Manunta, Michele; Casu, Francesco

    2014-05-01

    been carried out on real data acquired by ENVISAT and COSMO-SkyMed sensors. Moreover, the P-SBAS performances with respect to the size of the input dataset will also be investigated. This kind of analysis is essential for assessing the goodness of the P-SBAS algorithm and gaining insight into its applicability to different scenarios. Besides, such results will also become crucial to identify and evaluate how to appropriately exploit P-SBAS to process the forthcoming large Sentinel-1 data stream. References [1] Massonnet, D., Briole, P., Arnaud, A., "Deflation of Mount Etna monitored by Spaceborne Radar Interferometry", Nature, vol. 375, pp. 567-570, 1995. [2] Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti, "A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms", IEEE Trans. Geosci. Remote Sens., vol. 40, no. 11, pp. 2375-2383, Nov. 2002. [3] Elefante, S., Imperatore, P. , Zinno, I., M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, F. Casu, "SBAS-DINSAR Time series generation on cloud computing platforms", IEEE IGARSS 2013, July 2013, Melbourne (AU). [4] Zinno, P. Imperatore, S. Elefante, F. Casu, M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, "A Novel Parallel Computational Framework for Processing Large INSAR Data Sets", Living Planet Symposium 2013, Sept. 9-13, 2013.

  10. Deployment Algorithms of Wireless Sensor Networks for Near-surface Underground Oil and Gas Pipeline Monitoring

    Directory of Open Access Journals (Sweden)

    Hua-Ping YU

    2014-07-01

    Full Text Available Oil and gas pipelines are the infrastructure of national economic development. Deployment problem of wireless underground sensor networks (WUSN for oil and gas pipeline systems is a fundamental problem. This paper firstly analyzed the wireless channel characteristics and energy consumption model in near-surface underground soil, and then studied the spatial structure of oil and gas pipelines and introduced the three-layer system structure of WUSN for oil and gas pipelines monitoring. Secondly, the optimal deployment strategy in XY plane and XZ plane which were projected from three-dimensional oil and gas pipeline structure was analyzed. Thirdly, the technical framework of using kinetic energy of the fluid in pipelines to recharge sensor nodes and partition strategy for energy consumption balance based on the wireless communication technology of magnetic induction waveguide were proposed, which can effectively improve the energy performance and connectivity of the network, and provide theoretical guidance and practical basis for the monitoring of long oil and gas pipeline network, the city tap water pipe network and sewage pipe network.

  11. Performance and Complexity Analysis of Blind FIR Channel Identification Algorithms Based on Deterministic Maximum Likelihood in SIMO Systems

    DEFF Research Database (Denmark)

    De Carvalho, Elisabeth; Omar, Samir; Slock, Dirk

    2013-01-01

    We analyze two algorithms that have been introduced previously for Deterministic Maximum Likelihood (DML) blind estimation of multiple FIR channels. The first one is a modification of the Iterative Quadratic ML (IQML) algorithm. IQML gives biased estimates of the channel and performs poorly at low...... to the initialization. Its asymptotic performance does not reach the DML performance though. The second strategy, called Pseudo-Quadratic ML (PQML), is naturally denoised. The denoising in PQML is furthermore more efficient than in DIQML: PQML yields the same asymptotic performance as DML, as opposed to DIQML......, but requires a consistent initialization. We furthermore compare DIQML and PQML to the strategy of alternating minimization w.r.t. symbols and channel for solving DML (AQML). An asymptotic performance analysis, a complexity evaluation and simulation results are also presented. The proposed DIQML and PQML...

  12. Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

    Science.gov (United States)

    González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

    2015-03-01

    A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

  13. A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

    Science.gov (United States)

    Siddeq, M. M.; Rodrigues, M. A.

    2015-09-01

    Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

  14. Detection and Identification of Salmonella spp. in Surface Water by Molecular Technology in Taiwan

    Science.gov (United States)

    Tseng, S. F.; Hsu, B. M.; Huang, K. H.; Hsiao, H. Y.; Kao, P. M.; Shen, S. M.; Tsai, H. F.; Chen, J. S.

    2012-04-01

    Salmonella spp. is classified to gram-negative bacterium and is one of the most important causal agents of waterborne diseases. The genus of Salmonella comprises more than 2,500 serotypes and its taxonomy is also very complicated. In tradition, the detection of Salmonella in environmental water samples by routines culture methods using selective media and characterization of suspicious colonies based on biochemical tests and serological assay are generally time and labor consuming. To overcome this disadvantage, it is desirable to use effective method which provides a higher discrimination and more rapid identification about Salmonella in environmental water. The aim of this study is to investigate the occurrence of Salmonella using novel procedures of detection method and to identify the serovars of Salmonella isolates from 157 surface water samples in Taiwan. The procedures include membrane filtration, non-selective pre-enrichment, selective enrichment of Salmonella, and then isolation of Salmonella strains by selective culture plates. The selective enrichment and culture plates were both detected by PCR. Finally, we used biochemical tests and serological assay to confirm the serovars of Salmonella and also used Pulsed-field gel electrophoresis (PFGE) to identify their sarovar catagories by the genetic pattern. In this study, 44 water samples (28%) were indentified as Salmonella. The 44 positive water samples by culture method were further identified as S. Agona(1/44), S. Albany (10/44), S. Bareilly (13/44),S. Choleraesuis (2/44),S. Derby (4/44),S. Isangi (3/44),S.Kedougou(3/44),S. Mbandaka(1/44),S.Newport (3/44), S. Oranienburg(1/44), S. Potsdam (1/44),S. Typhimurium (1/44), andS. Weltevreden(1/44) by PFGE. The presence of Salmonella in surface water indicates the possibility of waterborne transmission in drinking watershed if water is not adequately treated. Therefore, the authorities need to have operating systems that currently provide adequate source

  15. A coupled remote sensing and the Surface Energy Balance with Topography Algorithm (SEBTA to estimate actual evapotranspiration over heterogeneous terrain

    Directory of Open Access Journals (Sweden)

    Z. Q. Gao

    2011-01-01

    Full Text Available Evapotranspiration (ET may be used as an ecological indicator to address the ecosystem complexity. The accurate measurement of ET is of great significance for studying environmental sustainability, global climate changes, and biodiversity. Remote sensing technologies are capable of monitoring both energy and water fluxes on the surface of the Earth. With this advancement, existing models, such as SEBAL, S_SEBI and SEBS, enable us to estimate the regional ET with limited temporal and spatial coverage in the study areas. This paper extends the existing modeling efforts with the inclusion of new components for ET estimation at different temporal and spatial scales under heterogeneous terrain with varying elevations, slopes and aspects. Following a coupled remote sensing and surface energy balance approach, this study emphasizes the structure and function of the Surface Energy Balance with Topography Algorithm (SEBTA. With the aid of the elevation and landscape information, such as slope and aspect parameters derived from the digital elevation model (DEM, and the vegetation cover derived from satellite images, the SEBTA can account for the dynamic impacts of heterogeneous terrain and changing land cover with some varying kinetic parameters (i.e., roughness and zero-plane displacement. Besides, the dry and wet pixels can be recognized automatically and dynamically in image processing thereby making the SEBTA more sensitive to derive the sensible heat flux for ET estimation. To prove the application potential, the SEBTA was carried out to present the robust estimates of 24 h solar radiation over time, which leads to the smooth simulation of the ET over seasons in northern China where the regional climate and vegetation cover in different seasons compound the ET calculations. The SEBTA was validated by the measured data at the ground level. During validation, it shows that the consistency index reached 0.92 and the correlation coefficient was 0.87.

  16. An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

    Science.gov (United States)

    Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

    2015-12-01

    Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

  17. Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

    Science.gov (United States)

    Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

    2018-02-01

    Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

  18. Use of two predictive algorithms of the world wide web for the identification of tumor-reactive T-cell epitopes.

    Science.gov (United States)

    Lu, J; Celis, E

    2000-09-15

    Tumor cells can be effectively recognized and eliminated by CTLs. One approach for the development of CTL-based cancer immunotherapy for solid tumors requires the use of the appropriate immunogenic peptide epitopes that are derived from defined tumor-associated antigens. Because CTL peptide epitopes are restricted to specific MHC alleles, to design immune therapies for the general population it is necessary to identify epitopes for the most commonly found human MHC alleles. The identification of such epitopes has been based on MHC-peptide-binding assays that are costly and labor-intensive. We report here the use of two computer-based prediction algorithms, which are readily available in the public domain (Internet), to identify HL4-B7-restricted CTL epitopes for carcinoembryonic antigen (CEA). These algorithms identified three candidate peptides that we studied for their capacity to induce CTL responses in vitro using lymphocytes from HLA-B7+ normal blood donors. The results show that one of these peptides, CEA9(632) (IPQQHTQVL) was efficient in the induction of primary CTL responses when dendritic cells were used as antigen-presenting cells. These CTLs were efficient in killing tumor cells that express HLA-B7 and produce CEA. The identification of this HLA-B7-restricted CTL epitope will be useful for the design of ethnically unbiased, widely applicable immunotherapies for common solid epithelial tumors expressing CEA. Moreover, our strategy of identifying MHC class I-restricted CTL epitopes without the need of peptide/HLA-binding assays provides a convenient and cost-saving alternative approach to previous methods.

  19. Vertical Jump Height Estimation Algorithm Based on Takeoff and Landing Identification Via Foot-Worn Inertial Sensing.

    Science.gov (United States)

    Wang, Jianren; Xu, Junkai; Shull, Peter B

    2018-03-01

    Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were -2.2±2.1 cm and -0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=-10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.

  20. Data and software tools for gamma radiation spectral threat detection and nuclide identification algorithm development and evaluation

    International Nuclear Information System (INIS)

    Portnoy, David; Fisher, Brian; Phifer, Daniel

    2015-01-01

    The detection of radiological and nuclear threats is extremely important to national security. The federal government is spending significant resources developing new detection systems and attempting to increase the performance of existing ones. The detection of illicit radionuclides that may pose a radiological or nuclear threat is a challenging problem complicated by benign radiation sources (e.g., cat litter and medical treatments), shielding, and large variations in background radiation. Although there is a growing acceptance within the community that concentrating efforts on algorithm development (independent of the specifics of fully assembled systems) has the potential for significant overall system performance gains, there are two major hindrances to advancements in gamma spectral analysis algorithms under the current paradigm: access to data and common performance metrics along with baseline performance measures. Because many of the signatures collected during performance measurement campaigns are classified, dissemination to algorithm developers is extremely limited. This leaves developers no choice but to collect their own data if they are lucky enough to have access to material and sensors. This is often combined with their own definition of metrics for measuring performance. These two conditions make it all but impossible for developers and external reviewers to make meaningful comparisons between algorithms. Without meaningful comparisons, performance advancements become very hard to achieve and (more importantly) recognize. The objective of this work is to overcome these obstacles by developing and freely distributing real and synthetically generated gamma-spectra data sets as well as software tools for performance evaluation with associated performance baselines to national labs, academic institutions, government agencies, and industry. At present, datasets for two tracks, or application domains, have been developed: one that includes temporal

  1. Data and software tools for gamma radiation spectral threat detection and nuclide identification algorithm development and evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Portnoy, David; Fisher, Brian; Phifer, Daniel

    2015-06-01

    The detection of radiological and nuclear threats is extremely important to national security. The federal government is spending significant resources developing new detection systems and attempting to increase the performance of existing ones. The detection of illicit radionuclides that may pose a radiological or nuclear threat is a challenging problem complicated by benign radiation sources (e.g., cat litter and medical treatments), shielding, and large variations in background radiation. Although there is a growing acceptance within the community that concentrating efforts on algorithm development (independent of the specifics of fully assembled systems) has the potential for significant overall system performance gains, there are two major hindrances to advancements in gamma spectral analysis algorithms under the current paradigm: access to data and common performance metrics along with baseline performance measures. Because many of the signatures collected during performance measurement campaigns are classified, dissemination to algorithm developers is extremely limited. This leaves developers no choice but to collect their own data if they are lucky enough to have access to material and sensors. This is often combined with their own definition of metrics for measuring performance. These two conditions make it all but impossible for developers and external reviewers to make meaningful comparisons between algorithms. Without meaningful comparisons, performance advancements become very hard to achieve and (more importantly) recognize. The objective of this work is to overcome these obstacles by developing and freely distributing real and synthetically generated gamma-spectra data sets as well as software tools for performance evaluation with associated performance baselines to national labs, academic institutions, government agencies, and industry. At present, datasets for two tracks, or application domains, have been developed: one that includes temporal

  2. Identification of PV solar cells and modules parameters using the genetic algorithms: Application to maximum power extraction

    Energy Technology Data Exchange (ETDEWEB)

    Zagrouba, M.; Sellami, A.; Bouaicha, M. [Laboratoire de Photovoltaique, des Semi-conducteurs et des Nanostructures, Centre de Recherches et des Technologies de l' Energie, Technopole de Borj-Cedria, Tunis, B.P. 95, 2050 Hammam-Lif (Tunisia); Ksouri, M. [Unite de Recherche RME-Groupe AIA, Institut National des Sciences Appliquees et de Technologie (Tunisia)

    2010-05-15

    In this paper, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (I{sub s}, I{sub ph}, R{sub s}, R{sub sh}, and n) of photovoltaic (PV) solar cells and modules. These parameters were used to determine the corresponding maximum power point (MPP) from the illuminated current-voltage (I-V) characteristic. The one diode type approach is used to model the AM1.5 I-V characteristic of the solar cell. To extract electrical parameters, the approach is formulated as a non convex optimization problem. The GAs approach was used as a numerical technique in order to overcome problems involved in the local minima in the case of non convex optimization criteria. Compared to other methods, we find that the GAs is a very efficient technique to estimate the electrical parameters of PV solar cells and modules. Indeed, the race of the algorithm stopped after five generations in the case of PV solar cells and seven generations in the case of PV modules. The identified parameters are then used to extract the maximum power working points for both cell and module. (author)

  3. Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm.

    Science.gov (United States)

    Chuang, Li-Yeh; Lane, Hsien-Yuan; Lin, Yu-Da; Lin, Ming-Teng; Yang, Cheng-Hong; Chang, Hsueh-Wei

    2014-01-01

    Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear. This study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups). The analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance. This study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion.

  4. A Two-Step Strategy for System Identification of Civil Structures for Structural Health Monitoring Using Wavelet Transform and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Carlos Andres Perez-Ramirez

    2017-01-01

    Full Text Available Nowadays, the accurate identification of natural frequencies and damping ratios play an important role in smart civil engineering, since they can be used for seismic design, vibration control, and condition assessment, among others. To achieve it in practical way, it is required to instrument the structure and apply techniques which are able to deal with noise-corrupted and non-linear signals, as they are common features in real-life civil structures. In this article, a two-step strategy is proposed for performing accurate modal parameters identification in an automated manner. In the first step, it is obtained and decomposed the measured signals using the natural excitation technique and the synchrosqueezed wavelet transform, respectively. Then, the second step estimates the modal parameters by solving an optimization problem employing a genetic algorithm-based approach, where the micropopulation concept is used to improve the speed convergence as well as the accuracy of the estimated values. The accuracy and effectiveness of the proposal are tested using both the simulated response of a benchmark structure and the measurements of a real eight-story building. The obtained results show that the proposed strategy can estimate the modal parameters accurately, indicating than the proposal can be considered as an alternative to perform the abovementioned task.

  5. Identification of Subtype-Specific Prognostic Genes for Early-Stage Lung Adenocarcinoma and Squamous Cell Carcinoma Patients Using an Embedded Feature Selection Algorithm.

    Directory of Open Access Journals (Sweden)

    Suyan Tian

    Full Text Available The existence of fundamental differences between lung adenocarcinoma (AC and squamous cell carcinoma (SCC in their underlying mechanisms motivated us to postulate that specific genes might exist relevant to prognosis of each histology subtype. To test on this research hypothesis, we previously proposed a simple Cox-regression model based feature selection algorithm and identified successfully some subtype-specific prognostic genes when applying this method to real-world data. In this article, we continue our effort on identification of subtype-specific prognostic genes for AC and SCC, and propose a novel embedded feature selection method by extending Threshold Gradient Descent Regularization (TGDR algorithm and minimizing on a corresponding negative partial likelihood function. Using real-world datasets and simulated ones, we show these two proposed methods have comparable performance whereas the new proposal is superior in terms of model parsimony. Our analysis provides some evidence on the existence of such subtype-specific prognostic genes, more investigation is warranted.

  6. Combining Fragment-Ion and Neutral-Loss Matching during Mass Spectral Library Searching: A New General Purpose Algorithm Applicable to Illicit Drug Identification.

    Science.gov (United States)

    Moorthy, Arun S; Wallace, William E; Kearsley, Anthony J; Tchekhovskoi, Dmitrii V; Stein, Stephen E

    2017-12-19

    A mass spectral library search algorithm that identifies compounds that differ from library compounds by a single "inert" structural component is described. This algorithm, the Hybrid Similarity Search, generates a similarity score based on matching both fragment ions and neutral losses. It employs the parameter DeltaMass, defined as the mass difference between query and library compounds, to shift neutral loss peaks in the library spectrum to match corresponding neutral loss peaks in the query spectrum. When the spectra being compared differ by a single structural feature, these matching neutral loss peaks should contain that structural feature. This method extends the scope of the library to include spectra of "nearest-neighbor" compounds that differ from library compounds by a single chemical moiety. Additionally, determination of the structural origin of the shifted peaks can aid in the determination of the chemical structure and fragmentation mechanism of the query compound. A variety of examples are presented, including the identification of designer drugs and chemical derivatives not present in the library.

  7. Cardiac MRI in mice at 9.4 Tesla with a transmit-receive surface coil and a cardiac-tailored intensity-correction algorithm.

    Science.gov (United States)

    Sosnovik, David E; Dai, Guangping; Nahrendorf, Matthias; Rosen, Bruce R; Seethamraju, Ravi

    2007-08-01

    To evaluate the use of a transmit-receive surface (TRS) coil and a cardiac-tailored intensity-correction algorithm for cardiac MRI in mice at 9.4 Tesla (9.4T). Fast low-angle shot (FLASH) cines, with and without delays alternating with nutations for tailored excitation (DANTE) tagging, were acquired in 13 mice. An intensity-correction algorithm was developed to compensate for the sensitivity profile of the surface coil, and was tailored to account for the unique distribution of noise and flow artifacts in cardiac MR images. Image quality was extremely high and allowed fine structures such as trabeculations, valve cusps, and coronary arteries to be clearly visualized. The tag lines created with the surface coil were also sharp and clearly visible. Application of the intensity-correction algorithm improved signal intensity, tissue contrast, and image quality even further. Importantly, the cardiac-tailored properties of the correction algorithm prevented noise and flow artifacts from being significantly amplified. The feasibility and value of cardiac MRI in mice with a TRS coil has been demonstrated. In addition, a cardiac-tailored intensity-correction algorithm has been developed and shown to improve image quality even further. The use of these techniques could produce significant potential benefits over a broad range of scanners, coil configurations, and field strengths. (c) 2007 Wiley-Liss, Inc.

  8. Inverse problem studies of biochemical systems with structure identification of S-systems by embedding training functions in a genetic algorithm.

    Science.gov (United States)

    Sarode, Ketan Dinkar; Kumar, V Ravi; Kulkarni, B D

    2016-05-01

    An efficient inverse problem approach for parameter estimation, state and structure identification from dynamic data by embedding training functions in a genetic algorithm methodology (ETFGA) is proposed for nonlinear dynamical biosystems using S-system canonical models. Use of multiple shooting and decomposition approach as training functions has been shown for handling of noisy datasets and computational efficiency in studying the inverse problem. The advantages of the methodology are brought out systematically by studying it for three biochemical model systems of interest. By studying a small-scale gene regulatory system described by a S-system model, the first example demonstrates the use of ETFGA for the multifold aims of the inverse problem. The estimation of a large number of parameters with simultaneous state and network identification is shown by training a generalized S-system canonical model with noisy datasets. The results of this study bring out the superior performance of ETFGA on comparison with other metaheuristic approaches. The second example studies the regulation of cAMP oscillations in Dictyostelium cells now assuming limited availability of noisy data. Here, flexibility of the approach to incorporate partial system information in the identification process is shown and its effect on accuracy and predictive ability of the estimated model are studied. The third example studies the phenomenological toy model of the regulation of circadian oscillations in Drosophila that follows rate laws different from S-system power-law. For the limited noisy data, using a priori information about properties of the system, we could estimate an alternate S-system model that showed robust oscillatory behavior with predictive abilities. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Accuracy and Consistency of Grass Pollen Identification by Human Analysts Using Electron Micrographs of Surface Ornamentation

    Directory of Open Access Journals (Sweden)

    Luke Mander

    2014-08-01

    Full Text Available Premise of the study: Humans frequently identify pollen grains at a taxonomic rank above species. Grass pollen is a classic case of this situation, which has led to the development of computational methods for identifying grass pollen species. This paper aims to provide context for these computational methods by quantifying the accuracy and consistency of human identification. Methods: We measured the ability of nine human analysts to identify 12 species of grass pollen using scanning electron microscopy images. These are the same images that were used in computational identifications. We have measured the coverage, accuracy, and consistency of each analyst, and investigated their ability to recognize duplicate images. Results: Coverage ranged from 87.5% to 100%. Mean identification accuracy ranged from 46.67% to 87.5%. The identification consistency of each analyst ranged from 32.5% to 87.5%, and each of the nine analysts produced considerably different identification schemes. The proportion of duplicate image pairs that were missed ranged from 6.25% to 58.33%. Discussion: The identification errors made by each analyst, which result in a decline in accuracy and consistency, are likely related to psychological factors such as the limited capacity of human memory, fatigue and boredom, recency effects, and positivity bias.

  10. Identification of slip surface location by TLS-GPS datafor landslide mitigation case study: Ciloto-Puncak, West Java

    International Nuclear Information System (INIS)

    Sadarviana, Vera; Hasanuddin, A. Z.; Joenil, G. K.; Irwan; Wijaya, Dudy; Ilman, H.; Agung, N.; Achmad, R. T.; Pangeran, C.; Martin, S.; Gamal, M.; Santoso, Djoko

    2015-01-01

    Landslide can prevented by understanding the direction of movement to the safety evacuation track or slip surface location to hold avalanches. Slip surface is separating between stable soil and unstable soil in the slope. The slip surface location gives information about stable material depth. The information can be utilize to mitigate technical step, such as pile installation to keep construction or settlement safe from avalanches.There are two kinds landslide indicators which are visualization and calculation. By visualization, landslide identified from soil crack or scarp. Scarp is a scar of exposed soil on the landslide. That identification can be done by Terrestrial Laser Scanner (TLS) Image. Shape of scarp shows type of slip surface, translation or rotational. By calculation, kinematic and dynamic mathematic model will give vector, velocity and acceleration of material movement. In this calculation need velocity trend line at GPS point from five GPS data campaign. From intersection of trend lines it will create curves or lines of slip surface location. The number of slip surface can be known from material movement direction in landslide zone.Ciloto landslide zone have complicated phenomenon because that zone have influence from many direction of ground water level pressure. The pressure is causes generating several slip surface in Ciloto zone. Types of Ciloto slip surface have mix between translational and rotational type

  11. Identification of slip surface location by TLS-GPS datafor landslide mitigation case study: Ciloto-Puncak, West Java

    Energy Technology Data Exchange (ETDEWEB)

    Sadarviana, Vera, E-mail: vsadarviana@gmail.com; Hasanuddin, A. Z.; Joenil, G. K.; Irwan; Wijaya, Dudy; Ilman, H.; Agung, N.; Achmad, R. T.; Pangeran, C.; Martin, S.; Gamal, M. [Geodesy Research Group, Faculty of Earth Sciences and Technology, Bandung Institute of Technology, Jl. Ganesha 10, Bandung 40132, West Java (Indonesia); Santoso, Djoko [Geophysics Engineering Research Group, Faculty of Geoscience and Mineral Engineering, Bandung Institute of Technology, Jl. Ganesha 10, Bandung 40132, West Java (Indonesia)

    2015-04-24

    Landslide can prevented by understanding the direction of movement to the safety evacuation track or slip surface location to hold avalanches. Slip surface is separating between stable soil and unstable soil in the slope. The slip surface location gives information about stable material depth. The information can be utilize to mitigate technical step, such as pile installation to keep construction or settlement safe from avalanches.There are two kinds landslide indicators which are visualization and calculation. By visualization, landslide identified from soil crack or scarp. Scarp is a scar of exposed soil on the landslide. That identification can be done by Terrestrial Laser Scanner (TLS) Image. Shape of scarp shows type of slip surface, translation or rotational. By calculation, kinematic and dynamic mathematic model will give vector, velocity and acceleration of material movement. In this calculation need velocity trend line at GPS point from five GPS data campaign. From intersection of trend lines it will create curves or lines of slip surface location. The number of slip surface can be known from material movement direction in landslide zone.Ciloto landslide zone have complicated phenomenon because that zone have influence from many direction of ground water level pressure. The pressure is causes generating several slip surface in Ciloto zone. Types of Ciloto slip surface have mix between translational and rotational type.

  12. An algorithm for automatic crystal identification in pixelated scintillation detectors using thin plate splines and Gaussian mixture models.

    Science.gov (United States)

    Schellenberg, Graham; Stortz, Greg; Goertzen, Andrew L

    2016-02-07

    A typical positron emission tomography detector is comprised of a scintillator crystal array coupled to a photodetector array or other position sensitive detector. Such detectors using light sharing to read out crystal elements require the creation of a crystal lookup table (CLUT) that maps the detector response to the crystal of interaction based on the x-y position of the event calculated through Anger-type logic. It is vital for system performance that these CLUTs be accurate so that the location of events can be accurately identified and so that crystal-specific corrections, such as energy windowing or time alignment, can be applied. While using manual segmentation of the flood image to create the CLUT is a simple and reliable approach, it is both tedious and time consuming for systems with large numbers of crystal elements. In this work we describe the development of an automated algorithm for CLUT generation that uses a Gaussian mixture model paired with thin plate splines (TPS) to iteratively fit a crystal layout template that includes the crystal numbering pattern. Starting from a region of stability, Gaussians are individually fit to data corresponding to crystal locations while simultaneously updating a TPS for predicting future Gaussian locations at the edge of a region of interest that grows as individual Gaussians converge to crystal locations. The algorithm was tested with flood image data collected from 16 detector modules, each consisting of a 409 crystal dual-layer offset LYSO crystal array readout by a 32 pixel SiPM array. For these detector flood images, depending on user defined input parameters, the algorithm runtime ranged between 17.5-82.5 s per detector on a single core of an Intel i7 processor. The method maintained an accuracy above 99.8% across all tests, with the majority of errors being localized to error prone corner regions. This method can be easily extended for use with other detector types through adjustment of the initial

  13. An algorithm for automatic crystal identification in pixelated scintillation detectors using thin plate splines and Gaussian mixture models

    International Nuclear Information System (INIS)

    Schellenberg, Graham; Goertzen, Andrew L; Stortz, Greg

    2016-01-01

    A typical positron emission tomography detector is comprised of a scintillator crystal array coupled to a photodetector array or other position sensitive detector. Such detectors using light sharing to read out crystal elements require the creation of a crystal lookup table (CLUT) that maps the detector response to the crystal of interaction based on the x–y position of the event calculated through Anger-type logic. It is vital for system performance that these CLUTs be accurate so that the location of events can be accurately identified and so that crystal-specific corrections, such as energy windowing or time alignment, can be applied. While using manual segmentation of the flood image to create the CLUT is a simple and reliable approach, it is both tedious and time consuming for systems with large numbers of crystal elements. In this work we describe the development of an automated algorithm for CLUT generation that uses a Gaussian mixture model paired with thin plate splines (TPS) to iteratively fit a crystal layout template that includes the crystal numbering pattern. Starting from a region of stability, Gaussians are individually fit to data corresponding to crystal locations while simultaneously updating a TPS for predicting future Gaussian locations at the edge of a region of interest that grows as individual Gaussians converge to crystal locations. The algorithm was tested with flood image data collected from 16 detector modules, each consisting of a 409 crystal dual-layer offset LYSO crystal array readout by a 32 pixel SiPM array. For these detector flood images, depending on user defined input parameters, the algorithm runtime ranged between 17.5–82.5 s per detector on a single core of an Intel i7 processor. The method maintained an accuracy above 99.8% across all tests, with the majority of errors being localized to error prone corner regions. This method can be easily extended for use with other detector types through adjustment of the initial

  14. An algorithm for automatic crystal identification in pixelated scintillation detectors using thin plate splines and Gaussian mixture models

    Science.gov (United States)

    Schellenberg, Graham; Stortz, Greg; Goertzen, Andrew L.

    2016-02-01

    A typical positron emission tomography detector is comprised of a scintillator crystal array coupled to a photodetector array or other position sensitive detector. Such detectors using light sharing to read out crystal elements require the creation of a crystal lookup table (CLUT) that maps the detector response to the crystal of interaction based on the x-y position of the event calculated through Anger-type logic. It is vital for system performance that these CLUTs be accurate so that the location of events can be accurately identified and so that crystal-specific corrections, such as energy windowing or time alignment, can be applied. While using manual segmentation of the flood image to create the CLUT is a simple and reliable approach, it is both tedious and time consuming for systems with large numbers of crystal elements. In this work we describe the development of an automated algorithm for CLUT generation that uses a Gaussian mixture model paired with thin plate splines (TPS) to iteratively fit a crystal layout template that includes the crystal numbering pattern. Starting from a region of stability, Gaussians are individually fit to data corresponding to crystal locations while simultaneously updating a TPS for predicting future Gaussian locations at the edge of a region of interest that grows as individual Gaussians converge to crystal locations. The algorithm was tested with flood image data collected from 16 detector modules, each consisting of a 409 crystal dual-layer offset LYSO crystal array readout by a 32 pixel SiPM array. For these detector flood images, depending on user defined input parameters, the algorithm runtime ranged between 17.5-82.5 s per detector on a single core of an Intel i7 processor. The method maintained an accuracy above 99.8% across all tests, with the majority of errors being localized to error prone corner regions. This method can be easily extended for use with other detector types through adjustment of the initial

  15. Identification of immiscible NAPL contaminant sources in aquifers by a modified two-level saturation based imperialist competitive algorithm

    Science.gov (United States)

    Ghafouri, H. R.; Mosharaf-Dehkordi, M.; Afzalan, B.

    2017-07-01

    A simulation-optimization model is proposed for identifying the characteristics of local immiscible NAPL contaminant sources inside aquifers. This model employs the UTCHEM 9.0 software as its simulator for solving the governing equations associated with the multi-phase flow in porous media. As the optimization model, a novel two-level saturation based Imperialist Competitive Algorithm (ICA) is proposed to estimate the parameters of contaminant sources. The first level consists of three parallel independent ICAs and plays as a pre-conditioner for the second level which is a single modified ICA. The ICA in the second level is modified by dividing each country into a number of provinces (smaller parts). Similar to countries in the classical ICA, these provinces are optimized by the assimilation, competition, and revolution steps in the ICA. To increase the diversity of populations, a new approach named knock the base method is proposed. The performance and accuracy of the simulation-optimization model is assessed by solving a set of two and three-dimensional problems considering the effects of different parameters such as the grid size, rock heterogeneity and designated monitoring networks. The obtained numerical results indicate that using this simulation-optimization model provides accurate results at a less number of iterations when compared with the model employing the classical one-level ICA. A model is proposed to identify characteristics of immiscible NAPL contaminant sources. The contaminant is immiscible in water and multi-phase flow is simulated. The model is a multi-level saturation-based optimization algorithm based on ICA. Each answer string in second level is divided into a set of provinces. Each ICA is modified by incorporating a new knock the base model.

  16. An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

    Science.gov (United States)

    Huang, Chengjun; Chen, Xiang; Cao, Shuai; Qiu, Bensheng; Zhang, Xu

    2017-08-01

    Objective. To realize accurate muscle force estimation, a novel framework is proposed in this paper which can extract the input of the prediction model from the appropriate activation area of the skeletal muscle. Approach. Surface electromyographic (sEMG) signals from the biceps brachii muscle during isometric elbow flexion were collected with a high-density (HD) electrode grid (128 channels) and the external force at three contraction levels was measured at the wrist synchronously. The sEMG envelope matrix was factorized into a matrix of basis vectors with each column representing an activation pattern and a matrix of time-varying coefficients by a nonnegative matrix factorization (NMF) algorithm. The activation pattern with the highest activation intensity, which was defined as the sum of the absolute values of the time-varying coefficient curve, was considered as the major activation pattern, and its channels with high weighting factors were selected to extract the input activation signal of a force estimation model based on the polynomial fitting technique. Main results. Compared with conventional methods using the whole channels of the grid, the proposed method could significantly improve the quality of force estimation and reduce the electrode number. Significance. The proposed method provides a way to find proper electrode placement for force estimation, which can be further employed in muscle heterogeneity analysis, myoelectric prostheses and the control of exoskeleton devices.

  17. Optimization of microwave-assisted drying of Jerusalem artichokes (Helianthus tuberosus L. by response surface methodology and genetic algorithm

    Directory of Open Access Journals (Sweden)

    E. KARACABEY

    2016-03-01

    Full Text Available The objective of the present study was to investigate microwave-assisted drying of Jerusalem artichoke tubers to determine the effects of the processing conditions. Drying time (DT and effectivemoisture diffusivity (EMD were determined to evaluate the drying process in terms of dehydration performance, whereas the rehydration ratio (RhR was considered as a significant quality index. A pretreatment of soaking in a NaCl solution was applied before all trials. The output power of the microwave oven, slice thickness and NaCl concentration of the pretreatment solution werethe three investigated parameters. The drying process was accelerated by altering the conditions while obtaining a higher quality product. For optimization of the drying process, response surface methodology (RSM and genetic algorithms (GA were used. Model adequacy was evaluated for each corresponding mathematical expression developed for interested responses by RSM. The residual of the model obtained by GA was compared to that of the RSM model. The GA was successful in high-performance prediction and produced results similar to those of RSM. The analysis and results of the present study show that both RSM and GA models can be used in cohesion to gain insight into the bioprocessing system.

  18. An intelligent algorithm for identification of optimum mix of demographic features for trust in medical centers in Iran.

    Science.gov (United States)

    Yazdanparast, R; Zadeh, S Abdolhossein; Dadras, D; Azadeh, A

    2018-06-01

    Healthcare quality is affected by various factors including trust. Patients' trust to healthcare providers is one of the most important factors for treatment outcomes. The presented study identifies optimum mixture of patient demographic features with respect to trust in three large and busy medical centers in Tehran, Iran. The presented algorithm is composed of adaptive neuro-fuzzy inference system and statistical methods. It is used to deal with data and environmental uncertainty. The required data are collected from three large hospitals using standard questionnaires. The reliability and validity of the collected data is evaluated using Cronbach's Alpha, factor analysis and statistical tests. The results of this study indicate that middle age patients with low level of education and moderate illness severity and young patients with high level of education, moderate illness severity and moderate to weak financial status have the highest trust to the considered medical centers. To the best of our knowledge this the first study that investigates patient demographic features using adaptive neuro-fuzzy inference system in healthcare sector. Second, it is a practical approach for continuous improvement of trust features in medical centers. Third, it deals with the existing uncertainty through the unique neuro-fuzzy approach. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. Identification of a Threshold Value for the DEMATEL Method: Using the Maximum Mean De-Entropy Algorithm

    Science.gov (United States)

    Chung-Wei, Li; Gwo-Hshiung, Tzeng

    To deal with complex problems, structuring them through graphical representations and analyzing causal influences can aid in illuminating complex issues, systems, or concepts. The DEMATEL method is a methodology which can be used for researching and solving complicated and intertwined problem groups. The end product of the DEMATEL process is a visual representation—the impact-relations map—by which respondents organize their own actions in the world. The applicability of the DEMATEL method is widespread, ranging from analyzing world problematique decision making to industrial planning. The most important property of the DEMATEL method used in the multi-criteria decision making (MCDM) field is to construct interrelations between criteria. In order to obtain a suitable impact-relations map, an appropriate threshold value is needed to obtain adequate information for further analysis and decision-making. In this paper, we propose a method based on the entropy approach, the maximum mean de-entropy algorithm, to achieve this purpose. Using real cases to find the interrelationships between the criteria for evaluating effects in E-learning programs as an examples, we will compare the results obtained from the respondents and from our method, and discuss that the different impact-relations maps from these two methods.

  20. Application of the nonlinear time series prediction method of genetic algorithm for forecasting surface wind of point station in the South China Sea with scatterometer observations

    International Nuclear Information System (INIS)

    Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin

    2016-01-01

    The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)

  1. 6 CFR 37.17 - Requirements for the surface of the driver's license or identification card.

    Science.gov (United States)

    2010-01-01

    ... Driver's license or identification card number. This cannot be the individual's SSN, and must be unique... University Street, Montreal, Quebec, Canada H3C 5H7, e-mail: [email protected] You may inspect a copy of the...

  2. Source identification of underground fuel spills by solid-phase microextraction/high-resolution gas chromatography/genetic algorithms.

    Science.gov (United States)

    Lavine, B K; Ritter, J; Moores, A J; Wilson, M; Faruque, A; Mayfield, H T

    2000-01-15

    Solid-phase microextraction (SPME), capillary column gas chromatography, and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of gas chromatograms from 180 neat jet fuel samples representing common aviation turbine fuels found in the United States (JP-4, Jet-A, JP-7, JPTS, JP-5, JP-8). SPME sampling of the fuel's headspace afforded well-resolved reproducible profiles, which were standardized using special peak-matching software. The peak-matching procedure yielded 84 standardized retention time windows, though not all peaks were present in all gas chromatograms. A genetic algorithm (GA) was employed to identify features (in the standardized chromatograms of the neat jet fuels) suitable for pattern recognition analysis. The GA selected peaks, whose two largest principal components showed clustering of the chromatograms on the basis of fuel type. The principal component analysis routine in the fitness function of the GA acted as an information filter, significantly reducing the size of the search space, since it restricted the search to feature subsets whose variance is primarily about differences between the various fuel types in the training set. In addition, the GA focused on those classes and/or samples that were difficult to classify as it trained using a form of boosting. Samples that consistently classify correctly were not as heavily weighted as samples that were difficult to classify. Over time, the GA learned its optimal parameters in a manner similar to a perceptron. The pattern recognition GA integrated aspects of strong and weak learning to yield a "smart" one-pass procedure for feature selection.

  3. A MATLAB-based graphical user interface for the identification of muscular activations from surface electromyography signals.

    Science.gov (United States)

    Mengarelli, Alessandro; Cardarelli, Stefano; Verdini, Federica; Burattini, Laura; Fioretti, Sandro; Di Nardo, Francesco

    2016-08-01

    In this paper a graphical user interface (GUI) built in MATLAB® environment is presented. This interactive tool has been developed for the analysis of superficial electromyography (sEMG) signals and in particular for the assessment of the muscle activation time intervals. After the signal import, the tool performs a first analysis in a totally user independent way, providing a reliable computation of the muscular activation sequences. Furthermore, the user has the opportunity to modify each parameter of the on/off identification algorithm implemented in the presented tool. The presence of an user-friendly GUI allows the immediate evaluation of the effects that the modification of every single parameter has on the activation intervals recognition, through the real-time updating and visualization of the muscular activation/deactivation sequences. The possibility to accept the initial signal analysis or to modify the on/off identification with respect to each considered signal, with a real-time visual feedback, makes this GUI-based tool a valuable instrument in clinical, research applications and also in an educational perspective.

  4. ChromAlign: A two-step algorithmic procedure for time alignment of three-dimensional LC-MS chromatographic surfaces.

    Science.gov (United States)

    Sadygov, Rovshan G; Maroto, Fernando Martin; Hühmer, Andreas F R

    2006-12-15

    We present an algorithmic approach to align three-dimensional chromatographic surfaces of LC-MS data of complex mixture samples. The approach consists of two steps. In the first step, we prealign chromatographic profiles: two-dimensional projections of chromatographic surfaces. This is accomplished by correlation analysis using fast Fourier transforms. In this step, a temporal offset that maximizes the overlap and dot product between two chromatographic profiles is determined. In the second step, the algorithm generates correlation matrix elements between full mass scans of the reference and sample chromatographic surfaces. The temporal offset from the first step indicates a range of the mass scans that are possibly correlated, then the correlation matrix is calculated only for these mass scans. The correlation matrix carries information on highly correlated scans, but it does not itself determine the scan or time alignment. Alignment is determined as a path in the correlation matrix that maximizes the sum of the correlation matrix elements. The computational complexity of the optimal path generation problem is reduced by the use of dynamic programming. The program produces time-aligned surfaces. The use of the temporal offset from the first step in the second step reduces the computation time for generating the correlation matrix and speeds up the process. The algorithm has been implemented in a program, ChromAlign, developed in C++ language for the .NET2 environment in WINDOWS XP. In this work, we demonstrate the applications of ChromAlign to alignment of LC-MS surfaces of several datasets: a mixture of known proteins, samples from digests of surface proteins of T-cells, and samples prepared from digests of cerebrospinal fluid. ChromAlign accurately aligns the LC-MS surfaces we studied. In these examples, we discuss various aspects of the alignment by ChromAlign, such as constant time axis shifts and warping of chromatographic surfaces.

  5. Real breakthrough in detection of radioactive sources by portal monitors with plastic detectors and New Advanced Source Identification Algorithm (ASIA-New)

    Energy Technology Data Exchange (ETDEWEB)

    Stavrov, Andrei; Yamamoto, Eugene [Rapiscan Systems, Inc., 14000 Mead Street, Longmont, CO, 80504 (United States)

    2015-07-01

    Radiation Portal Monitors (RPM) with plastic detectors represent the main instruments used for primary border (customs) radiation control. RPM are widely used because they are simple, reliable, relatively inexpensive and have a high sensitivity. However, experience using the RPM in various countries has revealed the systems have some grave shortcomings. There is a dramatic decrease of the probability of detection of radioactive sources under high suppression of the natural gamma background (radiation control of heavy cargoes, containers and, especially, trains). NORM (Naturally Occurring Radioactive Material) existing in objects under control trigger the so-called 'nuisance alarms', requiring a secondary inspection for source verification. At a number of sites, the rate of such alarms is so high it significantly complicates the work of customs and border officers. This paper presents a brief description of new variant of algorithm ASIA-New (New Advanced Source Identification Algorithm), which was developed by the Rapiscan company. It also demonstrates results of different tests and the capability of a new system to overcome the shortcomings stated above. New electronics and ASIA-New enables RPM to detect radioactive sources under a high background suppression (tested at 15-30%) and to verify the detected NORM (KCl) and the artificial isotopes (Co- 57, Ba-133 and other). New variant of ASIA is based on physical principles, a phenomenological approach and analysis of some important parameter changes during the vehicle passage through the monitor control area. Thanks to this capability main advantage of new system is that this system can be easily installed into any RPM with plastic detectors. Taking into account that more than 4000 RPM has been installed worldwide their upgrading by ASIA-New may significantly increase probability of detection and verification of radioactive sources even masked by NORM. This algorithm was tested for 1,395 passages of

  6. Identification of unknown contaminants in surface water : combination of analytical and computer-based approaches

    OpenAIRE

    Hu, Meng

    2017-01-01

    Thousands of different chemicals are used in our daily life for household, industry, agriculture and medical purpose, and many of them are discharged into water bodies by direct or indirect ways. Thus, monitoring and identification of organic pollutants in aquatic ecosystem is one of the most essential concerns with respects to human health and aquatic life. Althrough liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) has made huge advancements in recent years, allow...

  7. Identification of the Heat Transfer Coefficient at the Charge Surface Heated on the Chamber Furnace

    Directory of Open Access Journals (Sweden)

    Gołdasz A.

    2017-06-01

    Full Text Available The inverse method was applied to determine the heat flux reaching the charge surface. The inverse solution was based upon finding the minimum of the error norm between the measured and calculated temperatures. The charge temperature field was calculated with the finite element method by solving the heat transfer equation for a square charge made of 15HM steel heated on all its surfaces. On the basis of the mean value of heat flux, the value of the heat transfer coefficient at each surface was determined depending on the surface temperature of the material heated.

  8. Interrogating the Plasmodium Sporozoite Surface: Identification of Surface-Exposed Proteins and Demonstration of Glycosylation on CSP and TRAP by Mass Spectrometry-Based Proteomics.

    Directory of Open Access Journals (Sweden)

    Kristian E Swearingen

    2016-04-01

    Full Text Available Malaria parasite infection is initiated by the mosquito-transmitted sporozoite stage, a highly motile invasive cell that targets hepatocytes in the liver for infection. A promising approach to developing a malaria vaccine is the use of proteins located on the sporozoite surface as antigens to elicit humoral immune responses that prevent the establishment of infection. Very little of the P. falciparum genome has been considered as potential vaccine targets, and candidate vaccines have been almost exclusively based on single antigens, generating the need for novel target identification. The most advanced malaria vaccine to date, RTS,S, a subunit vaccine consisting of a portion of the major surface protein circumsporozoite protein (CSP, conferred limited protection in Phase III trials, falling short of community-established vaccine efficacy goals. In striking contrast to the limited protection seen in current vaccine trials, sterilizing immunity can be achieved by immunization with radiation-attenuated sporozoites, suggesting that more potent protection may be achievable with a multivalent protein vaccine. Here, we provide the most comprehensive analysis to date of proteins located on the surface of or secreted by Plasmodium falciparum salivary gland sporozoites. We used chemical labeling to isolate surface-exposed proteins on sporozoites and identified these proteins by mass spectrometry. We validated several of these targets and also provide evidence that components of the inner membrane complex are in fact surface-exposed and accessible to antibodies in live sporozoites. Finally, our mass spectrometry data provide the first direct evidence that the Plasmodium surface proteins CSP and TRAP are glycosylated in sporozoites, a finding that could impact the selection of vaccine antigens.

  9. Scanning the cell surface proteome of cancer cells and identification of metastasis-associated proteins using a subtractive immunization strategy

    DEFF Research Database (Denmark)

    Rasmussen, Nicolaj; Ditzel, Henrik J

    2009-01-01

    and technologically challenging, and no ideal method is currently available. Here, we describe a strategy that allows scanning of the entire cell surface and identification of molecules that exhibit altered expression between two cell types. Concurrently, this method gives rise to valuable reagents for further...... characterization of the identified proteins. The strategy is based on subtractive immunization of mice, and we used the two isogenic cell lines, NM-2C5 and M-4A4, derived from the MDA-MB-435 cancer cell line, as a model system. Although the two cell lines are equally tumorigenic, only M-4A4 has metastatic...... capabilities. Our results yielded a large panel of monoclonal antibodies (mAbs) that recognized cell surface markers preferentially or exclusively expressed on metastatic vs nonmetastatic cancer cells. Four mAbs and their corresponding antigens were further characterized. Importantly, analysis on an extended...

  10. An algorithm for hyperspectral remote sensing of aerosols: 2. Information content analysis for aerosol parameters and principal components of surface spectra

    Science.gov (United States)

    Hou, Weizhen; Wang, Jun; Xu, Xiaoguang; Reid, Jeffrey S.

    2017-05-01

    This paper describes the second part of a series of investigation to develop algorithms for simultaneous retrieval of aerosol parameters and surface reflectance from the future hyperspectral and geostationary satellite sensors such as Tropospheric Emissions: Monitoring of POllution (TEMPO). The information content in these hyperspectral measurements is analyzed for 6 principal components (PCs) of surface spectra and a total of 14 aerosol parameters that describe the columnar aerosol volume Vtotal, fine-mode aerosol volume fraction, and the size distribution and wavelength-dependent index of refraction in both coarse and fine mode aerosols. Forward simulations of atmospheric radiative transfer are conducted for 5 surface types (green vegetation, bare soil, rangeland, concrete and mixed surface case) and a wide range of aerosol mixtures. It is shown that the PCs of surface spectra in the atmospheric window channel could be derived from the top-of-the-atmosphere reflectance in the conditions of low aerosol optical depth (AOD ≤ 0.2 at 550 nm), with a relative error of 1%. With degree freedom for signal analysis and the sequential forward selection method, the common bands for different aerosol mixture types and surface types can be selected for aerosol retrieval. The first 20% of our selected bands accounts for more than 90% of information content for aerosols, and only 4 PCs are needed to reconstruct surface reflectance. However, the information content in these common bands from each TEMPO individual observation is insufficient for the simultaneous retrieval of surface's PC weight coefficients and multiple aerosol parameters (other than Vtotal). In contrast, with multiple observations for the same location from TEMPO in multiple consecutive days, 1-3 additional aerosol parameters could be retrieved. Consequently, a self-adjustable aerosol retrieval algorithm to account for surface types, AOD conditions, and multiple-consecutive observations is recommended to derive

  11. Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

    Science.gov (United States)

    Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

    2016-01-01

    Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

  12. Identification of variant-specific surface proteins in Giardia muris trophozoites.

    Science.gov (United States)

    Ropolo, Andrea S; Saura, Alicia; Carranza, Pedro G; Lujan, Hugo D

    2005-08-01

    Giardia lamblia undergoes antigenic variation, a process that might allow the parasite to evade the host's immune response and adapt to different environments. Here we show that Giardia muris, a related species that naturally infects rodents, possesses multiple variant-specific surface proteins (VSPs) and expresses VSPs on its surface, suggesting that it undergoes antigenic variation similar to that of G. lamblia.

  13. Identification of Variant-Specific Surface Proteins in Giardia muris Trophozoites

    OpenAIRE

    Ropolo, Andrea S.; Saura, Alicia; Carranza, Pedro G.; Lujan, Hugo D.

    2005-01-01

    Giardia lamblia undergoes antigenic variation, a process that might allow the parasite to evade the host's immune response and adapt to different environments. Here we show that Giardia muris, a related species that naturally infects rodents, possesses multiple variant-specific surface proteins (VSPs) and expresses VSPs on its surface, suggesting that it undergoes antigenic variation similar to that of G. lamblia.

  14. Comparison of Performance between Genetic Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation

    OpenAIRE

    Jeon, Ji-Hong; Park, Chan-Gi; Engel, Bernard

    2014-01-01

    Global optimization methods linked with simulation models are widely used for automated calibration and serve as useful tools for searching for cost-effective alternatives for environmental management. A genetic algorithm (GA) and shuffled complex evolution (SCE-UA) algorithm were linked with the Long-Term Hydrologic Impact Assessment (L-THIA) model, which employs the curve number (SCS-CN) method. The performance of the two optimization methods was compared by automatically calibrating L-THI...

  15. Process Parameter Identification in Thin Film Flows Driven by a Stretching Surface

    Directory of Open Access Journals (Sweden)

    Satyananda Panda

    2014-01-01

    Full Text Available The flow of a thin liquid film over a heated stretching surface is considered in this study. Due to a potential nonuniform temperature distribution on the stretching sheet, a temperature gradient occurs in the fluid which produces surface tension gradient at the free surface of the thin film. As a result, the free surface deforms and these deformations are advected by the flow in the stretching direction. This work focuses on the inverse problem of reconstructing the sheet temperature distribution and the sheet stretch rate from observed free surface variations. This work builds on the analysis of Santra and Dandapat (2009 who, based on the long-wave expansion of the Navier-Stokes equations, formulate a partial differential equation which describes the evolution of the thickness of a film over a nonisothermal stretched surface. In this work, we show that after algebraic manipulation of a discrete form of the governing equations, it is possible to reconstruct either the unknown temperature field on the sheet and hence the resulting heat transfer or the stretching rate of the underlying surface. We illustrate the proposed methodology and test its applicability on a range of test problems.

  16. Identification of sporozoite surface proteins and antigens of Eimeria nieschulzi (Apicomplexa)

    International Nuclear Information System (INIS)

    Tilley, M.; Upton, S.J.

    1990-01-01

    Sodium dodecyl sulfate polyacrylamide gel electrophoresis, immunoblotting, lectin binding, and 125 I surface labeling of sporozoites were used to probe sporozoites of the rat coccidian, Eimeria nieschulzi. Analysis of silver stained gels revealed greater than 50 bands. Surface iodination revealed about 14 well labeled, and about 10 weakly labeled but potential, surface proteins. The most heavily labeled surface proteins had molecular masses of 60, 53-54, 45, 28, 23-24, 17, 15, 14, 13, and 12 kD. Following electrophoresis and Western blotting, 2 of the 12 125I labeled lectin probes bound to two bands on the blots, which collectively indicated that two bands were glycosylated. Concanavalin A (ConA) specifically recognized a band at 53 kD, which may represent a surface glycoprotein, and a lectin derived from Osage orange (MPA) bound to a single band at 82-88 kD, that may also be a surface molecule. Immunoblotting using sera collected from rats inoculated orally with oocysts, as well as sera from mice hyperimmunized with sporozoites, revealed that many surface molecules appear to be immunogenic

  17. Non-invasive identification of metal-oxalate complexes on polychrome artwork surfaces by reflection mid-infrared spectroscopy.

    Science.gov (United States)

    Monico, Letizia; Rosi, Francesca; Miliani, Costanza; Daveri, Alessia; Brunetti, Brunetto G

    2013-12-01

    In this work a reflection mid-infrared spectroscopy study of twelve metal-oxalate complexes, of interest in art conservation science as alteration compounds, was performed. Spectra of the reference materials highlighted the presence of derivative-like and/or inverted features for the fundamental vibrational modes as result of the main contribution from the surface component of the reflected light. In order to provide insights in the interpretation of theses spectral distortions, reflection spectra were compared with conventional transmission ones. The Kramers-Kronig (KK) algorithm, employed to correct for the surface reflection distortions, worked properly only for the derivative-like bands. Therefore, to pay attention to the use of this algorithm when interpreting the reflection spectra is recommended. The outcome of this investigation was exploited to discriminate among different oxalates on thirteen polychrome artworks analyzed in situ by reflection mid-infrared spectroscopy. The visualization of the νs(CO) modes (1400-1200 cm(-1)) and low wavenumber bands (below 900 cm(-1)) in the raw reflection profiles allowed Ca, Cu and Zn oxalates to be identified. Further information about the speciation of different hydration forms of calcium oxalates were obtained by using the KK transform. The work proves reflection mid-infrared spectroscopy to be a reliable and sensitive spectro-analytical method for identifying and mapping different metal-oxalate alteration compounds on the surface of artworks, thus providing conservation scientists with a non-invasive tool to obtain information on the state of conservation and causes of alteration of artworks. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. High colored dissolved organic matter (CDOM) absorption in surface waters of the central-eastern Arctic Ocean: Implications for biogeochemistry and ocean color algorithms.

    Science.gov (United States)

    Gonçalves-Araujo, Rafael; Rabe, Benjamin; Peeken, Ilka; Bracher, Astrid

    2018-01-01

    As consequences of global warming sea-ice shrinking, permafrost thawing and changes in fresh water and terrestrial material export have already been reported in the Arctic environment. These processes impact light penetration and primary production. To reach a better understanding of the current status and to provide accurate forecasts Arctic biogeochemical and physical parameters need to be extensively monitored. In this sense, bio-optical properties are useful to be measured due to the applicability of optical instrumentation to autonomous platforms, including satellites. This study characterizes the non-water absorbers and their coupling to hydrographic conditions in the poorly sampled surface waters of the central and eastern Arctic Ocean. Over the entire sampled area colored dissolved organic matter (CDOM) dominates the light absorption in surface waters. The distribution of CDOM, phytoplankton and non-algal particles absorption reproduces the hydrographic variability in this region of the Arctic Ocean which suggests a subdivision into five major bio-optical provinces: Laptev Sea Shelf, Laptev Sea, Central Arctic/Transpolar Drift, Beaufort Gyre and Eurasian/Nansen Basin. Evaluating ocean color algorithms commonly applied in the Arctic Ocean shows that global and regionally tuned empirical algorithms provide poor chlorophyll-a (Chl-a) estimates. The semi-analytical algorithms Generalized Inherent Optical Property model (GIOP) and Garver-Siegel-Maritorena (GSM), on the other hand, provide robust estimates of Chl-a and absorption of colored matter. Applying GSM with modifications proposed for the western Arctic Ocean produced reliable information on the absorption by colored matter, and specifically by CDOM. These findings highlight that only semi-analytical ocean color algorithms are able to identify with low uncertainty the distribution of the different optical water constituents in these high CDOM absorbing waters. In addition, a clustering of the Arctic Ocean

  19. Identification and characterization of surface antigens in parasites, using radiolabelling techniques

    International Nuclear Information System (INIS)

    Ramasamy, R.

    1982-04-01

    Surface proteins of Schistosoma sp and Leishmania sp were studied using 125-Iodine as tracer. The surface proteins were labelled by the Lactoperoxidase method and the proteins then separated using SDS PAG electrophoresis and autoradiography. The possible immunogens were then separated using immunoprecipitation and Fluorescent Antibody techniques using sera from patients or from artificially immunized rabbits. Four common antigens were identified from the surfaces of male and female adult worms, cercariae and schistosomulae of S.mansoni. These antigens, which had molecular weights of 150,000, 78,000, 45,000, and 22,000 were also isolated from the surfaces of S.haematobium adults. The surface antigens on promastigotes of a Kenyan strain of Leishmania donovani were separated into three protein antigens with molecular weights of 66,000, 59,000 and 43,000 respectively. The 59,000 molecular weight antigen was a glycoprotein and was common to promastigotes of an American and Indian strain of L.donovani and to L.braziliensis mexicana. None of the isolated antigens have been shown to have a protective effect when vaccinated into mice, but the study illustrates the value of radionuclide tracers in the unravelling of the mosaic of antigens which parasites possess

  20. Identification of soil erosion land surfaces by Landsat data analysis and processing

    International Nuclear Information System (INIS)

    Lo Curzio, S.

    2009-01-01

    In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

  1. In situ identification of paper chromatogram spots by surface enhanced Raman scattering

    Energy Technology Data Exchange (ETDEWEB)

    Tran, C D

    1984-01-01

    The use of silver hydrosols to enhance the Raman scattering of paper chromatogram spots has been used successfully. This enhancement technique, which is dependent on the interaction between the substrate, silver particles, and paper fibers, has been applied to detection and identification of ng amounts of crystal violet, malachite green, and basic fuchsin with an argon laser of only 4 mW. This technique enhances the resonance of the Raman scattering so that the Raman cross sections of the spots are approximately 9 to 10 orders of magnitude higher than those observed for non-enhanced systems. The limit of detection of the techniques is defined as the amount of dye spot that yields a signal to noise ratio of 2 when excited with the 4MeV.

  2. Bulk and surface event identification in p-type germanium detectors

    Science.gov (United States)

    Yang, L. T.; Li, H. B.; Wong, H. T.; Agartioglu, M.; Chen, J. H.; Jia, L. P.; Jiang, H.; Li, J.; Lin, F. K.; Lin, S. T.; Liu, S. K.; Ma, J. L.; Sevda, B.; Sharma, V.; Singh, L.; Singh, M. K.; Singh, M. K.; Soma, A. K.; Sonay, A.; Yang, S. W.; Wang, L.; Wang, Q.; Yue, Q.; Zhao, W.

    2018-04-01

    The p-type point-contact germanium detectors have been adopted for light dark matter WIMP searches and the studies of low energy neutrino physics. These detectors exhibit anomalous behavior to events located at the surface layer. The previous spectral shape method to identify these surface events from the bulk signals relies on spectral shape assumptions and the use of external calibration sources. We report an improved method in separating them by taking the ratios among different categories of in situ event samples as calibration sources. Data from CDEX-1 and TEXONO experiments are re-examined using the ratio method. Results are shown to be consistent with the spectral shape method.

  3. A novel algorithm for delineating wetland depressions and mapping surface hydrologic flow pathways using LiDAR data

    Science.gov (United States)

    In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In re...

  4. Identification and quantification of point sources of surface water contamination in fruit culture in the Netherlands

    NARCIS (Netherlands)

    Wenneker, M.; Beltman, W.H.J.; Werd, de H.A.E.; Zande, van de J.C.

    2008-01-01

    Measurements of pesticide concentrations in surface water by the water boards show that they have decreased less than was expected from model calculations. Possibly, the implementation of spray drift reducing techniques is overestimated in the model calculation. The impact of point sources is

  5. Identification of Uranyl Surface Complexes an Ferrihydrite: Advanced EXAFS Data Analysis and CD-MUSIC Modeling

    NARCIS (Netherlands)

    Rossberg, A.; Ulrich, K.U.; Weiss, S.; Tsushima, S.; Hiemstra, T.; Scheinost, A.C.

    2009-01-01

    Previous spectroscopic research suggested that uranium(VI) adsorption to iron oxides is dominated by ternary uranyl-carbonato surface complexes across an unexpectedly wide pH range. Formation of such complexes would have a significant impact on the sorption behavior and mobility of uranium in

  6. Curve identification for high friction surface treatment (HFST) installation recommendation : final report.

    Science.gov (United States)

    2016-09-01

    The objectives of this study are to develop and deploy a means for cost-effectively extracting curve information using the widely available GPS and GIS data to support high friction surface treatment (HFST) installation recommendations (i.e., start a...

  7. Identification and Characterization of Ixodes scapularis Antigens That Elicit Tick Immunity Using Yeast Surface Display

    NARCIS (Netherlands)

    Schuijt, T.J.; Narasimhan, S.; Daffre, S.; Deponte, K.; Hovius, J.W.R.; van 't Veer, C.; van der Poll, T.; Bakhtiari, K.; Meijers, J.C.M.; Boder, E.T.; van Dam, A.P.; Fikrig, E.

    2011-01-01

    Repeated exposure of rabbits and other animals to ticks results in acquired resistance or immunity to subsequent tick bites and is partially elicited by antibodies directed against tick antigens. In this study we demonstrate the utility of a yeast surface display approach to identify tick salivary

  8. A new technique for the identification of surface contamination in low temperature bolometric experiments

    International Nuclear Information System (INIS)

    Sangiorgio, S.; Arnaboldi, C.; Brofferio, C.; Bucci, C.; Capelli, S.; Carbone, L.; Clemenza, M.; Cremonesi, O.; Fiorini, E.; Foggetta, L.; Giuliani, A.; Gorla, P.; Nones, C.; Nucciotti, A.; Pavan, M.; Pedretti, M.; Pessina, G.; Pirro, S.; Previtali, E.; Salvioni, C.

    2011-01-01

    In the framework of the bolometric experiment CUORE, a new and promising technique has been developed in order to control the dangerous contamination coming from the surfaces close to the detector. In fact, by means of a composite bolometer, it is possible to partially overcome the loss of spatial resolution of the bolometer itself and to clearly identify events coming from outside.

  9. Implementation of Freeman-Wimley prediction algorithm in a web-based application for in silico identification of beta-barrel membrane proteins

    Directory of Open Access Journals (Sweden)

    José Antonio Agüero-Fernández

    2015-11-01

    Full Text Available Beta-barrel type proteins play an important role in both, human and veterinary medicine. In particular, their localization on the bacterial surface, and their involvement in virulence mechanisms of pathogens, have turned them into an interesting target in studies to search for vaccine candidates. Recently, Freeman and Wimley developed a prediction algorithm based on the physicochemical properties of transmembrane beta-barrels proteins (TMBBs. Based on that algorithm, and using Grails, a web-based application was implemented. This system, named Beta Predictor, is capable of processing from one protein sequence to complete predicted proteomes up to 10000 proteins with a runtime of about 0.019 seconds per 500-residue protein, and it allows graphical analyses for each protein. The application was evaluated with a validation set of 535 non-redundant proteins, 102 TMBBs and 433 non-TMBBs. The sensitivity, specificity, Matthews correlation coefficient, positive predictive value and accuracy were calculated, being 85.29%, 95.15%, 78.72%, 80.56% and 93.27%, respectively. The performance of this system was compared with TMBBs predictors, BOMP and TMBHunt, using the same validation set. Taking into account the order mentioned above, the following results were obtained: 76.47%, 99.31%, 83.05%, 96.30% and 94.95% for BOMP, and 78.43%, 92.38%, 67.90%, 70.17% and 89.78% for TMBHunt. Beta Predictor was outperformed by BOMP but the latter showed better behavior than TMBHunt

  10. A new algorithm for three-dimensional joint inversion of body wave and surface wave data and its application to the Southern California plate boundary region

    Science.gov (United States)

    Fang, Hongjian; Zhang, Haijiang; Yao, Huajian; Allam, Amir; Zigone, Dimitri; Ben-Zion, Yehuda; Thurber, Clifford; van der Hilst, Robert D.

    2016-05-01

    We introduce a new algorithm for joint inversion of body wave and surface wave data to get better 3-D P wave (Vp) and S wave (Vs) velocity models by taking advantage of the complementary strengths of each data set. Our joint inversion algorithm uses a one-step inversion of surface wave traveltime measurements at different periods for 3-D Vs and Vp models without constructing the intermediate phase or group velocity maps. This allows a more straightforward modeling of surface wave traveltime data with the body wave arrival times. We take into consideration the sensitivity of surface wave data with respect to Vp in addition to its large sensitivity to Vs, which means both models are constrained by two different data types. The method is applied to determine 3-D crustal Vp and Vs models using body wave and Rayleigh wave data in the Southern California plate boundary region, which has previously been studied with both double-difference tomography method using body wave arrival times and ambient noise tomography method with Rayleigh and Love wave group velocity dispersion measurements. Our approach creates self-consistent and unique models with no prominent gaps, with Rayleigh wave data resolving shallow and large-scale features and body wave data constraining relatively deeper structures where their ray coverage is good. The velocity model from the joint inversion is consistent with local geological structures and produces better fits to observed seismic waveforms than the current Southern California Earthquake Center (SCEC) model.

  11. The use of algorithms to predict surface seawater dimethyl sulphide concentrations in the SE Pacific, a region of steep gradients in primary productivity, biomass and mixed layer depth

    Directory of Open Access Journals (Sweden)

    A. J. Hind

    2011-01-01

    Full Text Available Dimethyl sulphide (DMS is an important precursor of cloud condensation nuclei (CCN, particularly in the remote marine atmosphere. The SE Pacific is consistently covered with a persistent stratocumulus layer that increases the albedo over this large area. It is not certain whether the source of CCN to these clouds is natural and oceanic or anthropogenic and terrestrial. This unknown currently limits our ability to reliably model either the cloud behaviour or the oceanic heat budget of the region. In order to better constrain the marine source of CCN, it is necessary to have an improved understanding of the sea-air flux of DMS. Of the factors that govern the magnitude of this flux, the greatest unknown is the surface seawater DMS concentration. In the study area, there is a paucity of such data, although previous measurements suggest that the concentration can be substantially variable. In order to overcome such data scarcity, a number of climatologies and algorithms have been devised in the last decade to predict seawater DMS. Here we test some of these in the SE Pacific by comparing predictions with measurements of surface seawater made during the Vamos Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx in October and November of 2008. We conclude that none of the existing algorithms reproduce local variability in seawater DMS in this region very well. From these findings, we recommend the best algorithm choice for the SE Pacific and suggest lines of investigation for future work.

  12. Identification of related multilingual documents using ant clustering algorithms Identificación de documentos multilingües relacionados mediante algoritmos de clustering de hormigas

    Directory of Open Access Journals (Sweden)

    Ángel Cobo

    2011-12-01

    Full Text Available This paper presents a document representation strategy and a bio-inspired algorithm to cluster multilingual collections of documents in the field of economics and business. The proposed approach allows the user to identify groups of related economics documents written in Spanish and English using techniques inspired on clustering and sorting behaviours observed in some types of ants. In order to obtain a language independent vector representation of each document two multilingual resources are used: an economic glossary and a thesaurus. Each document is represented using four feature vectors: words, proper names, economic terms in the glossary and thesaurus descriptors. The proper name identification, word extraction and lemmatization are performed using specific tools. The tf-idf scheme is used to measure the importance of each feature in the document, and a convex linear combination of angular separations between feature vectors is used as similarity measure of documents. The paper shows experimental results of the application of the proposed algorithm in a Spanish-English corpus of research papers in economics and management areas. The results demonstrate the usefulness and effectiveness of the ant clustering algorithm and the proposed representation scheme.Este artículo presenta una estrategia de representación documental y un algoritmo bioinspirado para realizar procesos de agrupamiento en colecciones multilingües de documentos en las áreas de la economía y la empresa. El enfoque propuesto permite al usuario identificar grupos de documentos económicos relacionados escritos en español o inglés usando técnicas inspiradas en comportamientos de organización y agrupamiento de objetos observados en algunos tipos de hormigas. Para conseguir una representación vectorial de cada documento independiente del idioma, se han utilizado dos recursos lingüísticos: un glosario económico y un tesauro. Cada documento es representado usando

  13. Identification of the c(10×6)-CN/Cu(001) surface structure

    KAUST Repository

    Shuttleworth, I.G.

    2014-01-01

    © 2014 Elsevier B.V. All rights reserved. A systematic survey of all possible c(10 x 6)-CN/Cu(0 0 1) structures has been performed using density functional theory (DFT). A group of four preferred structures is presented with one of the structures identified as optimal. An analysis of the bonding within the optimal structure has shown that a significant localisation of the surface Cu 4s bonds occurs in the saturated system.

  14. Identification of the c(10×6)-CN/Cu(001) surface structure

    KAUST Repository

    Shuttleworth, I.G.

    2014-12-01

    © 2014 Elsevier B.V. All rights reserved. A systematic survey of all possible c(10 x 6)-CN/Cu(0 0 1) structures has been performed using density functional theory (DFT). A group of four preferred structures is presented with one of the structures identified as optimal. An analysis of the bonding within the optimal structure has shown that a significant localisation of the surface Cu 4s bonds occurs in the saturated system.

  15. Porous silicon surfaces for metabonomics: Detection and identification of nucleotides without matrix interference

    Energy Technology Data Exchange (ETDEWEB)

    Gomez, D.; Azcarate, Sabino [Dpto. de Micro y Nanotecnologias, Fundacion Tekniker, Av. Otaola 20, 20600 Eibar (Spain); Fernandez, Jose A.; Astigarraga, Egoitz [Dpto. de Quimica Fisica, Universidad del Pais Vasco, Campus de Lejona, Lejona (Spain); Marcaide, Arrate [Dpto. de Procesos de Fabricacion, Fundacion Tekniker, Av. Otaola 20, 20600 Eibar (Spain)

    2007-07-01

    In present work, porous silicon surfaces (PSS) have been developed for time of flight mass spectrometric experiments (TOF-MS) in the monitoring of nucleotides, commonly found as metabolites in the cell. The mass range of the studied molecules ({proportional_to} 400 amu) is common to several important messengers and other metabolites. Different porosified surfaces have been developed by means of electrochemical etching and different degree of porosity and pore size achieved as function of silicon dopant concentration, silicon resistivity, current density and the presence or absence of illumination along the process. As main conclusion, it can be said that an interesting commercial nucleotide (Cyclic adenosine monophosphate, c-AMP) has been detected on low concentrations ({proportional_to}hundreds of femtomols) for some of the fabricated porous surfaces. Taking into account that these concentrations are similar to the ones found in real samples, this result opens the possibility to the fabrication of DIOS (Desorption Ionization On Silicon) chips for the detection of nucleotides in biological fluids. (copyright 2007 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  16. Reliable identification of deep sulcal pits: the effects of scan session, scanner, and surface extraction tool.

    Directory of Open Access Journals (Sweden)

    Kiho Im

    Full Text Available Sulcal pit analysis has been providing novel insights into brain function and development. The purpose of this study was to evaluate the reliability of sulcal pit extraction with respect to the effects of scan session, scanner, and surface extraction tool. Five subjects were scanned 4 times at 3 MRI centers and other 5 subjects were scanned 3 times at 2 MRI centers, including 1 test-retest session. Sulcal pits were extracted on the white matter surfaces reconstructed with both Montreal Neurological Institute and Freesurfer pipelines. We estimated similarity of the presence of sulcal pits having a maximum value of 1 and their spatial difference within the same subject. The tests showed high similarity of the sulcal pit presence and low spatial difference. The similarity was more than 0.90 and the spatial difference was less than 1.7 mm in most cases according to different scan sessions or scanners, and more than 0.85 and about 2.0 mm across surface extraction tools. The reliability of sulcal pit extraction was more affected by the image processing-related factors than the scan session or scanner factors. Moreover, the similarity of sulcal pit distribution appeared to be largely influenced by the presence or absence of the sulcal pits on the shallow and small folds. We suggest that our sulcal pit extraction from MRI is highly reliable and could be useful for clinical applications as an imaging biomarker.

  17. Reliable identification of deep sulcal pits: the effects of scan session, scanner, and surface extraction tool.

    Science.gov (United States)

    Im, Kiho; Lee, Jong-Min; Jeon, Seun; Kim, Jong-Heon; Seo, Sang Won; Na, Duk L; Grant, P Ellen

    2013-01-01

    Sulcal pit analysis has been providing novel insights into brain function and development. The purpose of this study was to evaluate the reliability of sulcal pit extraction with respect to the effects of scan session, scanner, and surface extraction tool. Five subjects were scanned 4 times at 3 MRI centers and other 5 subjects were scanned 3 times at 2 MRI centers, including 1 test-retest session. Sulcal pits were extracted on the white matter surfaces reconstructed with both Montreal Neurological Institute and Freesurfer pipelines. We estimated similarity of the presence of sulcal pits having a maximum value of 1 and their spatial difference within the same subject. The tests showed high similarity of the sulcal pit presence and low spatial difference. The similarity was more than 0.90 and the spatial difference was less than 1.7 mm in most cases according to different scan sessions or scanners, and more than 0.85 and about 2.0 mm across surface extraction tools. The reliability of sulcal pit extraction was more affected by the image processing-related factors than the scan session or scanner factors. Moreover, the similarity of sulcal pit distribution appeared to be largely influenced by the presence or absence of the sulcal pits on the shallow and small folds. We suggest that our sulcal pit extraction from MRI is highly reliable and could be useful for clinical applications as an imaging biomarker.

  18. Identification of Aspergillus fumigatus Surface Components That Mediate Interaction of Conidia and Hyphae With Human Platelets.

    Science.gov (United States)

    Rambach, Günter; Blum, Gerhard; Latgé, Jean-Paul; Fontaine, Thierry; Heinekamp, Thorsten; Hagleitner, Magdalena; Jeckström, Hanna; Weigel, Günter; Würtinger, Philipp; Pfaller, Kristian; Krappmann, Sven; Löffler, Jürgen; Lass-Flörl, Cornelia; Speth, Cornelia

    2015-10-01

    Platelets were recently identified as a part of innate immunity. They are activated by contact with Aspergillus fumigatus; putative consequences include antifungal defense but also thrombosis, excessive inflammation, and thrombocytopenia. We aimed to identify those fungal surface structures that mediate interaction with platelets. Human platelets were incubated with Aspergillus conidia and hyphae, isolated wall components, or fungal surface mutants. Interaction was visualized microscopically; activation was quantified by flow cytometry of specific markers. The capacity of A. fumigatus conidia to activate platelets is at least partly due to melanin, because this effect can be mimicked with "melanin ghosts"; a mutant lacking melanin showed reduced platelet stimulating potency. In contrast, conidial hydrophobin masks relevant structures, because an A. fumigatus mutant lacking the hydrophobin protein induced stronger platelet activation than wild-type conidia. A. fumigatus hyphae also contain surface structures that interact with platelets. Wall proteins, galactomannan, chitin, and β-glucan are not the relevant hyphal components; instead, the recently identified fungal polysaccharide galactosaminogalactan potently triggered platelet activation. Conidial melanin and hydrophobin as well as hyphal galactosaminogalactan represent important pathogenicity factors that modulate platelet activity and thus might influence immune responses, inflammation, and thrombosis in infected patients. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. Land Surface Model and Particle Swarm Optimization Algorithm Based on the Model-Optimization Method for Improving Soil Moisture Simulation in a Semi-Arid Region.

    Science.gov (United States)

    Yang, Qidong; Zuo, Hongchao; Li, Weidong

    2016-01-01

    Improving the capability of land-surface process models to simulate soil moisture assists in better understanding the atmosphere-land interaction. In semi-arid regions, due to limited near-surface observational data and large errors in large-scale parameters obtained by the remote sensing method, there exist uncertainties in land surface parameters, which can cause large offsets between the simulated results of land-surface process models and the observational data for the soil moisture. In this study, observational data from the Semi-Arid Climate Observatory and Laboratory (SACOL) station in the semi-arid loess plateau of China were divided into three datasets: summer, autumn, and summer-autumn. By combing the particle swarm optimization (PSO) algorithm and the land-surface process model SHAW (Simultaneous Heat and Water), the soil and vegetation parameters that are related to the soil moisture but difficult to obtain by observations are optimized using three datasets. On this basis, the SHAW model was run with the optimized parameters to simulate the characteristics of the land-surface process in the semi-arid loess plateau. Simultaneously, the default SHAW model was run with the same atmospheric forcing as a comparison test. Simulation results revealed the following: parameters optimized by the particle swarm optimization algorithm in all simulation tests improved simulations of the soil moisture and latent heat flux; differences between simulated results and observational data are clearly reduced, but simulation tests involving the adoption of optimized parameters cannot simultaneously improve the simulation results for the net radiation, sensible heat flux, and soil temperature. Optimized soil and vegetation parameters based on different datasets have the same order of magnitude but are not identical; soil parameters only vary to a small degree, but the variation range of vegetation parameters is large.

  20. Atomistic modeling of metal surfaces under electric fields: direct coupling of electric fields to a molecular dynamics algorithm

    CERN Document Server

    Djurabekova, Flyura; Pohjonen, Aarne; Nordlund, Kai

    2011-01-01

    The effect of electric fields on metal surfaces is fairly well studied, resulting in numerous analytical models developed to understand the mechanisms of ionization of surface atoms observed at very high electric fields, as well as the general behavior of a metal surface in this condition. However, the derivation of analytical models does not include explicitly the structural properties of metals, missing the link between the instantaneous effects owing to the applied field and the consequent response observed in the metal surface as a result of an extended application of an electric field. In the present work, we have developed a concurrent electrodynamic–molecular dynamic model for the dynamical simulation of an electric-field effect and subsequent modification of a metal surface in the framework of an atomistic molecular dynamics (MD) approach. The partial charge induced on the surface atoms by the electric field is assessed by applying the classical Gauss law. The electric forces acting on the partially...

  1. Surface Papillary Epithelial Hyperplasia (Rough Mucosa) is a Helpful Clue for Identification of Polymorphous Low-Grade Adenocarcinoma.

    Science.gov (United States)

    Chi, Angela C; Neville, Brad W

    2015-06-01

    The purpose of this study is to evaluate surface papillary epithelial hyperplasia, a microscopic finding that corresponds to the clinical finding of rough or stippled mucosa, as a predictor of polymorphous low-grade adenocarcinoma (PLGA). We conducted a retrospective review of minor salivary gland neoplasms submitted to our biopsy service from 1991 to 2013. Our review was limited to lesions involving the oral cavity/soft palate with the following diagnoses: PLGA, pleomorphic adenoma (PA), mucoepidermoid carcinoma (MEC), and adenoid cystic carcinoma (ACC). A total of 202 minor salivary gland neoplasms were included in the study. Among cases in which surface epithelium was present for evaluation (n = 112), surface papillary epithelial hyperplasia was evident in 30 % of PLGA and 1 % of non-PLGA (i.e., MEC, ACC, PA). The greater frequency of surface papillary epithelial hyperplasia in the PLGA versus non-PLGA cases and in the benign versus malignant cases was significant (p = .0001 and p = .041, respectively). The sensitivity and specificity of papillary epithelial hyperplasia for PLGA were 30 % (95 % confidence interval (CI) 11.97-54.27 %) and 99 % (95 % CI 94-99.82 %), respectively. The clinical presentation of PLGA appeared relatively nonspecific, with all analyzed tumor types exhibiting a predilection for females, middle-aged to older adults, palatal location, pink/tan/normal color, and firm consistency. In conclusion, papillary epithelial hyperplasia was evident in only a minority of PLGA. However, when present within the context of a palatal salivary gland neoplasm, it appears to indicate a high probability of PLGA. Accordingly, rough mucosa may be a useful clinical pearl for identification of PLGA.

  2. Identification of novel surface-exposed proteins of Rickettsia rickettsii by affinity purification and proteomics.

    Directory of Open Access Journals (Sweden)

    Wenping Gong

    Full Text Available Rickettsia rickettsii, the causative agent of Rocky Mountain spotted fever, is the most pathogenic member among Rickettsia spp. Surface-exposed proteins (SEPs of R. rickettsii may play important roles in its pathogenesis or immunity. In this study, R. rickettsii organisms were surface-labeled with sulfo-NHS-SS-biotin and the labeled proteins were affinity-purified with streptavidin. The isolated proteins were separated by two-dimensional electrophoresis, and 10 proteins were identified among 23 protein spots by electrospray ionization tandem mass spectrometry. Five (OmpA, OmpB, GroEL, GroES, and a DNA-binding protein of the 10 proteins were previously characterized as surface proteins of R. rickettsii. Another 5 proteins (Adr1, Adr2, OmpW, Porin_4, and TolC were first recognized as SEPs of R. rickettsii herein. The genes encoding the 5 novel SEPs were expressed in Escherichia coli cells, resulting in 5 recombinant SEPs (rSEPs, which were used to immunize mice. After challenge with viable R. rickettsii cells, the rickettsial load in the spleen, liver, or lung of mice immunized with rAdr2 and in the lungs of mice immunized with other rSEPs excluding rTolC was significantly lower than in mice that were mock-immunized with PBS. The in vitro neutralization test revealed that sera from mice immunized with rAdr1, rAdr2, or rOmpW reduced R. rickettsii adherence to and invasion of vascular endothelial cells. The immuno-electron microscopic assay clearly showed that the novel SEPs were located in the outer and/or inner membrane of R. rickettsii. Altogether, the 5 novel SEPs identified herein might be involved in the interaction of R. rickettsii with vascular endothelial cells, and all of them except TolC were protective antigens.

  3. Identification of Novel Surface-Exposed Proteins of Rickettsia rickettsii by Affinity Purification and Proteomics

    Science.gov (United States)

    Gong, Wenping; Xiong, Xiaolu; Qi, Yong; Jiao, Jun; Duan, Changsong; Wen, Bohai

    2014-01-01

    Rickettsia rickettsii, the causative agent of Rocky Mountain spotted fever, is the most pathogenic member among Rickettsia spp. Surface-exposed proteins (SEPs) of R. rickettsii may play important roles in its pathogenesis or immunity. In this study, R. rickettsii organisms were surface-labeled with sulfo-NHS-SS-biotin and the labeled proteins were affinity-purified with streptavidin. The isolated proteins were separated by two-dimensional electrophoresis, and 10 proteins were identified among 23 protein spots by electrospray ionization tandem mass spectrometry. Five (OmpA, OmpB, GroEL, GroES, and a DNA-binding protein) of the 10 proteins were previously characterized as surface proteins of R. rickettsii. Another 5 proteins (Adr1, Adr2, OmpW, Porin_4, and TolC) were first recognized as SEPs of R. rickettsii herein. The genes encoding the 5 novel SEPs were expressed in Escherichia coli cells, resulting in 5 recombinant SEPs (rSEPs), which were used to immunize mice. After challenge with viable R. rickettsii cells, the rickettsial load in the spleen, liver, or lung of mice immunized with rAdr2 and in the lungs of mice immunized with other rSEPs excluding rTolC was significantly lower than in mice that were mock-immunized with PBS. The in vitro neutralization test revealed that sera from mice immunized with rAdr1, rAdr2, or rOmpW reduced R. rickettsii adherence to and invasion of vascular endothelial cells. The immuno-electron microscopic assay clearly showed that the novel SEPs were located in the outer and/or inner membrane of R. rickettsii. Altogether, the 5 novel SEPs identified herein might be involved in the interaction of R. rickettsii with vascular endothelial cells, and all of them except TolC were protective antigens. PMID:24950252

  4. Identification of cell surface targets for HIV-1 therapeutics using genetic screens

    International Nuclear Information System (INIS)

    Dunn, Stephen J.; Khan, Imran H.; Chan, Ursula A.; Scearce, Robin L.; Melara, Claudia L.; Paul, Amber M.; Sharma, Vikram; Bih, Fong-Yih; Holzmayer, Tanya A.; Luciw, Paul A.; Abo, Arie

    2004-01-01

    Human immunodeficiency virus (HIV) drugs designed to interfere with obligatory utilization of certain host cell factors by virus are less likely to encounter development of resistant strains than drugs directed against viral components. Several cellular genes required for productive infection by HIV were identified by the use of genetic suppressor element (GSE) technology as potential targets for anti-HIV drug development. Fragmented cDNA libraries from various pools of human peripheral blood mononuclear cells (PBMC) were expressed in vitro in human immunodeficiency virus type 1 (HIV-1)-susceptible cell lines and subjected to genetic screens to identify GSEs that interfered with viral replication. After three rounds of selection, more than 15 000 GSEs were sequenced, and the cognate genes were identified. The GSEs that inhibited the virus were derived from a diverse set of genes including cell surface receptors, cytokines, signaling proteins, transcription factors, as well as genes with unknown function. Approximately 2.5% of the identified genes were previously shown to play a role in the HIV-1 life cycle; this finding supports the biological relevance of the assay. GSEs were derived from the following 12 cell surface proteins: CXCR4, CCR4, CCR7, CD11C, CD44, CD47, CD68, CD69, CD74, CSF3R, GABBR1, and TNFR2. Requirement of some of these genes for viral infection was also investigated by using RNA interference (RNAi) technology; accordingly, 10 genes were implicated in early events of the viral life cycle, before viral DNA synthesis. Thus, these cell surface proteins represent novel targets for the development of therapeutics against HIV-1 infection and AIDS

  5. Identification of a surface antigen on Theileria parva sporozoites by monoclonal antibody.

    OpenAIRE

    Dobbelaere, D A; Shapiro, S Z; Webster, P

    1985-01-01

    A mouse monoclonal antibody (mAbD1) that neutralizes sporozoites of different stocks of the protozoan parasite Theileria parva has been used to localize and identify a sporozoite antigen. Protein A-colloidal gold was used to localize bound mAbD1 in immunoelectron microscopic studies. mAbD1 bound to sporozoite antigen, which was evenly spread over the surface of all sporozoites. Immune complexes were obtained by incubation of sporozoite suspensions with mAbD1 followed by Zwittergent 3-14 extra...

  6. Rapid identification of bacterial resistance to Ciprofloxacin using surface-enhanced Raman spectroscopy

    Science.gov (United States)

    Kastanos, Evdokia; Hadjigeorgiou, Katerina; Pitris, Costas

    2014-02-01

    Due to its effectiveness and broad coverage, Ciprofloxacin is the fifth most prescribed antibiotic in the US. As current methods of infection diagnosis and antibiotic sensitivity testing (i.e. an antibiogram) are very time consuming, physicians prescribe ciprofloxacin before obtaining antibiogram results. In order to avoid increasing resistance to the antibiotic, a method was developed to provide both a rapid diagnosis and the sensitivity to the antibiotic. Using Surface Enhanced Raman Spectroscopy, an antibiogram was obtained after exposing the bacteria to Ciprofloxacin for just two hours. Spectral analysis revealed clear separation between sensitive and resistant bacteria and could also offer some inside into the mechanisms of resistance.

  7. Can a semi-automated surface matching and principal axis-based algorithm accurately quantify femoral shaft fracture alignment in six degrees of freedom?

    Science.gov (United States)

    Crookshank, Meghan C; Beek, Maarten; Singh, Devin; Schemitsch, Emil H; Whyne, Cari M

    2013-07-01

    Accurate alignment of femoral shaft fractures treated with intramedullary nailing remains a challenge for orthopaedic surgeons. The aim of this study is to develop and validate a cone-beam CT-based, semi-automated algorithm to quantify the malalignment in six degrees of freedom (6DOF) using a surface matching and principal axes-based approach. Complex comminuted diaphyseal fractures were created in nine cadaveric femora and cone-beam CT images were acquired (27 cases total). Scans were cropped and segmented using intensity-based thresholding, producing superior, inferior and comminution volumes. Cylinders were fit to estimate the long axes of the superior and inferior fragments. The angle and distance between the two cylindrical axes were calculated to determine flexion/extension and varus/valgus angulation and medial/lateral and anterior/posterior translations, respectively. Both surfaces were unwrapped about the cylindrical axes. Three methods of matching the unwrapped surface for determination of periaxial rotation were compared based on minimizing the distance between features. The calculated corrections were compared to the input malalignment conditions. All 6DOF were calculated to within current clinical tolerances for all but two cases. This algorithm yielded accurate quantification of malalignment of femoral shaft fractures for fracture gaps up to 60 mm, based on a single CBCT image of the fractured limb. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

  8. Identification of tectonic deformations on the south polar surface of the moon

    Science.gov (United States)

    Mukherjee, Saumitra; Singh, Priyadarshini

    2015-07-01

    Recent extensional and contractional tectonic features present globally over the lunar surface have been studied to infer lunar crustal tectonism. Investigation of indicators of recent crustal tectonics, such as fault lines, thrust fault scarps, and dislocation of debris along the identified fault planes, primarily using data from the miniature-synthetic aperture radar (mini-SAR) aboard CHANDRAYAAN-1 mission and Narrow angle camera (NAC) images, are the focus of this study. Spatial orientation of these tectonic features helps to elucidate the change in the interior geological dynamics of any planetary body with time. The ability of microwave sensors to penetrate the lunar regolith, along with application of m-χ decomposition method on Mini-SAR data has been used to reveal unique features indicative of hidden tectonics. The m-χ decomposition derived radar images expose hidden lineaments and lobate scarps present within shadowed crater floors as well as over the illuminated regions of the lunar surface. The area around and within Cabeus B crater in the South Polar Region contains lobate scarps, hidden lineaments and debris avalanches (associated with the identified lineaments) indicative of relatively recent crustal tectonism.

  9. Identification of nonlinear coupling in wave turbulence at the surface of water

    Science.gov (United States)

    Campagne, Antoine; Hassaini, Roumaissa; Redor, Ivan; Aubourg, Quentin; Sommeria, Joël; Mordant, Nicolas

    2017-11-01

    The Weak Turbulence Theory is a theory, in the limit of vanishing nonlinearity, that derive analytically statistical features of wave turbulence. The stationary spectrum for the surface elevation in the case of gravity waves, is predicted to E(k) k - 5 / 2 . This spectral exponent -5/2 remains elusive in all experiments. in which the measured exponent is systematically lower than the prediction. Furthermore in the experiments the weaker the nonlinearity the further the spectral exponent is from the prediction. In order to investigate the reason for this observation we developed an experiment in the CORIOLIS facility in Grenoble. It is a 13m-diameter circular pool filled with water with a 70 cm depth. We generate wave turbulence by using two wedge wavemakers. Surface elevation measurements are performed by a stereoscopic optical technique and by capacitive probes. The nonlinear coupling at work in this system are analyzed by computing 3- and 4-wave correlations of the Fourier wave amplitudes in frequency. Theory predicts that coupling should occur through 4-wave resonant interaction. In our data, strong 3-wave correlations are observed in addition to the 4-wave correlation. Most our observations are consistent with field observation in the Black Sea (Leckler et al. 2015). This project has received funding from the European Research Council (ERC, Grant Agreement No 647018-WATU).

  10. Identification and characterization of Ixodes scapularis antigens that elicit tick immunity using yeast surface display.

    Directory of Open Access Journals (Sweden)

    Tim J Schuijt

    2011-01-01

    Full Text Available Repeated exposure of rabbits and other animals to ticks results in acquired resistance or immunity to subsequent tick bites and is partially elicited by antibodies directed against tick antigens. In this study we demonstrate the utility of a yeast surface display approach to identify tick salivary antigens that react with tick-immune serum. We constructed an Ixodes scapularis nymphal salivary gland yeast surface display library and screened the library with nymph-immune rabbit sera and identified five salivary antigens. Four of these proteins, designated P8, P19, P23 and P32, had a predicted signal sequence. We generated recombinant (r P8, P19 and P23 in a Drosophila expression system for functional and immunization studies. rP8 showed anti-complement activity and rP23 demonstrated anti-coagulant activity. Ixodes scapularis feeding was significantly impaired when nymphs were fed on rabbits immunized with a cocktail of rP8, rP19 and rP23, a hall mark of tick-immunity. These studies also suggest that these antigens may serve as potential vaccine candidates to thwart tick feeding.

  11. Mapping the surface of MNKr2 and CopZ - identification of residues critical for metallotransfer

    International Nuclear Information System (INIS)

    Jones, C.E.; Cobine, P.A.; Dameron, C.T.

    2001-01-01

    Full text: Cells utilise a network of proteins that include CPx-type ATPases and metallochaperones to balance intracellular copper concentration. The Menkes ATPase has six N-terminal domains which bind Cu(I) and are critical for ATPase function. The NMR solution structure of the second domain (MNKr2) shows that the structure adopts an 'open-faced β-sandwich' fold, in which two α-helices lie over a single four stranded β-sheet. The global fold is identical to the bacterial copper chaperone CopZ MNKr2 is unable to substitute for CopZ in copper transfer to the cop operon represser, CopY. To investigate how structure affects function we have analysed the surface features of MNKr2 and CopZ Despite having the same global fold, MNKr2 and CopZ have contrasting electrostatic surfaces, which may partially explain the inability of MNKr2 to transfer copper to CopY

  12. Identification of ionic chloroacetanilide-herbicide metabolites in surface water and groundwater by HPLC/MS using negative ion spray

    Science.gov (United States)

    Ferrer, I.; Thurman, E.M.; Barcelo, D.

    1997-01-01

    Solid-phase extraction (SPE) was combined with high-performance liquid chromatography/high-flow pneumatically assisted electrospray mass spectrometry (HPLC/ESP/MS) for the trace analysis of oxanilic and sulfonic acids of acetochlor, alachlor, and metolachlor. The isolation procedure separated the chloroacetanilide metabolites from the parent herbicides during the elution from C18 cartridges using ethyl acetate for parent compounds, followed by methanol for the anionic metabolites. The metabolites were separated chromatographically using reversed-phase HPLC and analyzed by negative-ion MS using electrospray ionization in selected ion mode. Quantitation limits were 0.01 ??g/L for both the oxanilic and sulfonic acids based on a 100-mL water sample. This combination of methods represents an important advance in environmental analysis of chloroacetanilide-herbicide metabolites in surface water and groundwater for two reasons. First, anionic chloroacetanilide metabolites are a major class of degradation products that are readily leached to groundwater in agricultural areas. Second, anionic metabolites, which are not able to be analyzed by conventional methods such as liquid extraction and gas chromatography/mass spectrometry, are effectively analyzed by SPE and high-flow pneumatically assisted electrospray mass spectrometry. This paper reports the first HPLC/MS identification of these metabolites in surface water and groundwater.

  13. Identification of lactobacilli with inhibitory effect on biofilm formation by pathogenic bacteria on stainless steel surfaces.

    Science.gov (United States)

    Ait Ouali, Fatma; Al Kassaa, Imad; Cudennec, Benoit; Abdallah, Marwan; Bendali, Farida; Sadoun, Djamila; Chihib, Nour-Eddine; Drider, Djamel

    2014-11-17

    Two hundred and thirty individual clones of microorganisms were recovered from milk tanks and milking machine surfaces at two distinct farms (Bejaja City, Algeria). Of these clones, 130 were identified as lactic acid bacteria (LAB). In addition Escherichia coli, Salmonella, Staphylococcus aureus and Pseudomonas aeruginosa species were identified in the remaining 100 isolates-spoilage isolate. These isolates were assayed for ability to form biofilms. S. aureus, Lactobacillus brevis strains LB1F2, LB14F1 and LB15F1, and Lactobacillus pentosus strains LB2F2 and LB3F2 were identified as the best biofilm formers. Besides, these LAB isolates were able to produce proteinaceous substances with antagonism against the aforementioned spoilage isolates, when grown in MRS or TSB-YE media. During the screening, L. pentosus LB3F2 exhibited the highest antibacterial activity when grown in TSB-YE medium at 30 °C. Additionally, L. pentosus LB3F2 was able to strongly hamper the adhesion of S. aureus SA3 on abiotic surfaces as polystyrene and stainless steel slides. LAB isolates did not show any hemolytic activity and all of them were sensitive to different families of antibiotic tested. It should be pointed out that LB3F2 isolate was not cytotoxic on the intestinal cells but could stimulate their metabolic activity. This report unveiled the potential of LB1F2, LB14F1, LB15F1, LB2F2, and LB3F2 isolates to be used as natural barrier or competitive exclusion organism in the food processing sector as well as a positive biofilm forming bacteria. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Identification of Cell Surface Proteins as Potential Immunotherapy Targets in 12 Pediatric Cancers

    Energy Technology Data Exchange (ETDEWEB)

    Orentas, Rimas J. [Immunology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD (United States); Yang, James J. [Immunology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD (United States); Oncogenomics Section, Advanced Technology Center, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Gaithersburg, MD (United States); Wen, Xinyu; Wei, Jun S. [Oncogenomics Section, Advanced Technology Center, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Gaithersburg, MD (United States); Mackall, Crystal L. [Immunology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD (United States); Khan, Javed, E-mail: rimas.orentas@nih.gov [Oncogenomics Section, Advanced Technology Center, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Gaithersburg, MD (United States)

    2012-12-17

    Technological advances now allow us to rapidly produce CARs and other antibody-derived therapeutics targeting cell surface receptors. To maximize the potential of these new technologies, relevant extracellular targets must be identified. The Pediatric Oncology Branch of the NCI curates a freely accessible database of gene expression data for both pediatric cancers and normal tissues, through which we have defined discrete sets of over-expressed transcripts in 12 pediatric cancer subtypes as compared to normal tissues. We coupled gene expression profiles to current annotation databases (i.e., Affymetrix, Gene Ontology, Entrez Gene), in order to categorize transcripts by their sub-cellular location. In this manner we generated a list of potential immune targets expressed on the cell surface, ranked by their difference from normal tissue. Global differences from normal between each of the pediatric tumor types studied varied, indicating that some malignancies expressed transcript sets that were more highly diverged from normal tissues than others. The validity of our approach is seen by our findings for pre-B cell ALL, where targets currently in clinical trials were top-ranked hits (CD19, CD22). For some cancers, reagents already in development could potentially be applied to a new disease class, as exemplified by CD30 expression on sarcomas. Moreover, several potential new targets shared among several pediatric solid tumors are herein identified, such as MCAM (MUC18), metadherin (MTDH), and glypican-2 (GPC2). These targets have been identified at the mRNA level and are yet to be validated at the protein level. The safety of targeting these antigens has yet to be demonstrated and therefore the identified transcripts should be considered preliminary candidates for new CAR and therapeutic antibody targets. Prospective candidate targets will be evaluated by proteomic analysis including Westerns and immunohistochemistry of normal and tumor tissues.

  15. Spatial Variation, Pollution Assessment and Source Identification of Major Nutrients in Surface Sediments of Nansi Lake, China

    Directory of Open Access Journals (Sweden)

    Longfeng Wang

    2017-06-01

    Full Text Available Nansi Lake has been seriously affected by intensive anthropogenic activities in recent years. In this study, an extensive survey on spatial variation, pollution assessment as well as the possible sources identification of major nutrients (Total phosphorus: TP, Total nitrogen: TN, and Total organic carbon: TOC in the surface sediments of Nansi Lake was conducted. Results showed that the mean contents of TP, TN and TOC were 1.13-, 5.40- and 2.50- fold higher than their background values respectively. Most of the TN and TOC contents in the surface sediments of Nansi Lake were four times as high or higher and twice as high or higher than the background values except the Zhaoyang sub-lake, and the spatial distribution of TN and TOC contents were remarkably similar over a large area. Nearly all the TP contents in the surface sediments of Nansi Lake were all higher than its background values except most part of the Zhaoyang sub-lake. Based on the enrichment factor (EF and the organic pollution evaluation index (Org-index, TP, TOC and TN showed minor enrichment (1.13, minor enrichment (2.50 and moderately severe enrichment (5.40, respectively, and most part of the Dushan sub-lake and the vicinity of the Weishan island were in moderate or heavy sediments organic pollution, while the other parts were clean. Moreover, according to the results of multivariate statistical analysis, we deduced that anthropogenic TN and TOC were mainly came from industrial sources including enterprises distributed in Jining, Yanzhou and Zoucheng along with iron and steel industries distributed in the southern of the Weishan sub-lake, whereas TP mainly originated from runoff and soil erosion coming from agricultural lands located in Heze city and Weishan island, the local aquacultural activities as well as the domestic sewage discharge of Jining city.

  16. Identification of hotspots and trends of fecal surface water pollution in developing countries

    Science.gov (United States)

    Reder, Klara; Flörke, Martina; Alcamo, Joseph

    2015-04-01

    Water is the essential resource ensuring human life on earth, which can only prosper when water is available and accessible. But of importance is not only the quantity of accessible water but also its quality, which in case of pollution may pose a risk to human health. The pollutants which pose a risk to human health are manifold, covering several groups such as pathogens, nutrients, human pharmaceuticals, heavy metals, and others. With regards to human health, pathogen contamination is of major interest as 4% of all death and 5.7% of disability or ill health in the world can be attributed to poor water supply, sanitation and personal and domestic hygiene. In developing countries, 2.6 billion people lacked access to improved sanitation in 2011. The lack of sanitation poses a risk to surface water pollution which is a threat to human health. A typical indicator for pathogen pollution is fecal coliform bacteria. The objective our study is to assess fecal pollution in the developing regions Africa, Asia and Latin America using the large-scale water quality model WorldQual. Model runs were carried-out to calculate in-stream concentrations and the respective loadings reaching rivers for the time period 1990 to 2010. We identified hotspots of fecal coliform loadings and in-stream concentrations which were further analyzed and ranked in terms of fecal surface water pollution. Main findings are that loadings mainly originate from the domestic sector, thus loadings are high in highly populated areas. In general, domestic loadings can be attributed to the two subsectors domestic sewered and domestic non sewered. The spatial distribution of both sectors varies across catchments. Hotspot pattern of in-stream concentrations are similar to the loadings pattern although they are different in seasonality. As the dilution varies with climate its dilution capacity is high during seasons with high precipitation, which in turn decreases the in-stream concentrations. The fecal

  17. Sea Surface Salinity and Wind Retrieval Algorithm Using Combined Passive-Active L-Band Microwave Data

    Science.gov (United States)

    Yueh, Simon H.; Chaubell, Mario J.

    2011-01-01

    Aquarius is a combined passive/active L-band microwave instrument developed to map the salinity field at the surface of the ocean from space. The data will support studies of the coupling between ocean circulation, the global water cycle, and climate. The primary science objective of this mission is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean with a spatial resolution of 150 kilometers and a retrieval accuracy of 0.2 practical salinity units globally on a monthly basis. The measurement principle is based on the response of the L-band (1.413 gigahertz) sea surface brightness temperatures (T (sub B)) to sea surface salinity. To achieve the required 0.2 practical salinity units accuracy, the impact of sea surface roughness (e.g. wind-generated ripples and waves) along with several factors on the observed brightness temperature has to be corrected to better than a few tenths of a degree Kelvin. To the end, Aquarius includes a scatterometer to help correct for this surface roughness effect.

  18. Identification and characterization of the murine cell surface receptor for the urokinase-type plasminogen activator

    DEFF Research Database (Denmark)

    Solberg, H; Løber, D; Eriksen, J

    1992-01-01

    -blotting analysis. Binding of mouse u-PA to its receptor showed species specificity in ligand-blotting analysis, since mouse u-PA did not bind to human u-PAR and human u-PA did not bind to mouse u-PAR. The apparent M(r) of mouse u-PAR varied between different mouse cell lines and ranged over M(r) 45......,000-60,000. In four of the cell lines, mouse u-PA bound to two mouse u-PAR variant proteins, whereas in the other two cell lines studied, there was only one mouse u-PA-binding protein. In the monocyte macrophage cell line P388D.1, trypsin-treatment of intact cells could remove only the large mouse u-PAR variant (M...... to the cell surface by glycosylphosphatidylinositol. Purification of the two mouse u-PAR variant proteins by diisopropylfluorophosphate-inactivated mouse u-PA-Sepharose affinity chromatography yielded two silver-stained bands when analysed by SDS/PAGE, corresponding in electrophoretic mobility to those seen...

  19. Anticancer drugs in Portuguese surface waters - Estimation of concentrations and identification of potentially priority drugs.

    Science.gov (United States)

    Santos, Mónica S F; Franquet-Griell, Helena; Lacorte, Silvia; Madeira, Luis M; Alves, Arminda

    2017-10-01

    Anticancer drugs, used in chemotherapy, have emerged as new water contaminants due to their increasing consumption trends and poor elimination efficiency in conventional water treatment processes. As a result, anticancer drugs have been reported in surface and even drinking waters, posing the environment and human health at risk. However, the occurrence and distribution of anticancer drugs depend on the area studied and the hydrological dynamics, which determine the risk towards the environment. The main objective of the present study was to evaluate the risk of anticancer drugs in Portugal. This work includes an extensive analysis of the consumption trends of 171 anticancer drugs, sold or dispensed in Portugal between 2007 and 2015. The consumption data was processed aiming at the estimation of predicted environmental loads of anticancer drugs and 11 compounds were identified as potentially priority drugs based on an exposure-based approach (PEC b > 10 ng L -1 and/or PEC c > 1 ng L -1 ). In a national perspective, mycophenolic acid and mycophenolate mofetil are suspected to pose high risk to aquatic biota. Moderate and low risk was also associated to cyclophosphamide and bicalutamide exposition, respectively. Although no evidences of risk exist yet for the other anticancer drugs, concerns may be associated with long term effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

    Science.gov (United States)

    Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

    2016-01-01

    ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is

  1. A comparative analysis of DBSCAN, K-means, and quadratic variation algorithms for automatic identification of swallows from swallowing accelerometry signals.

    Science.gov (United States)

    Dudik, Joshua M; Kurosu, Atsuko; Coyle, James L; Sejdić, Ervin

    2015-04-01

    Cervical auscultation with high resolution sensors is currently under consideration as a method of automatically screening for specific swallowing abnormalities. To be clinically useful without human involvement, any devices based on cervical auscultation should be able to detect specified swallowing events in an automatic manner. In this paper, we comparatively analyze the density-based spatial clustering of applications with noise algorithm (DBSCAN), a k-means based algorithm, and an algorithm based on quadratic variation as methods of differentiating periods of swallowing activity from periods of time without swallows. These algorithms utilized swallowing vibration data exclusively and compared the results to a gold standard measure of swallowing duration. Data was collected from 23 subjects that were actively suffering from swallowing difficulties. Comparing the performance of the DBSCAN algorithm with a proven segmentation algorithm that utilizes k-means clustering demonstrated that the DBSCAN algorithm had a higher sensitivity and correctly segmented more swallows. Comparing its performance with a threshold-based algorithm that utilized the quadratic variation of the signal showed that the DBSCAN algorithm offered no direct increase in performance. However, it offered several other benefits including a faster run time and more consistent performance between patients. All algorithms showed noticeable differentiation from the endpoints provided by a videofluoroscopy examination as well as reduced sensitivity. In summary, we showed that the DBSCAN algorithm is a viable method for detecting the occurrence of a swallowing event using cervical auscultation signals, but significant work must be done to improve its performance before it can be implemented in an unsupervised manner. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Noninvasive identification of bladder cancer with sub-surface backscattered light

    Energy Technology Data Exchange (ETDEWEB)

    Bigio, I.J.; Mourant, J.R.; Boyer, J.; Johnson, T.; Shimada, T. [Los Alamos National Lab., NM (United States); Conn, R.L. [Lovelace Medical Center, Albuquerque, NM (United States). Dept. of Urology

    1994-02-01

    A non-invasive diagnostic tool that could identify malignancy in situ and in real time would have a major impact on the detection and treatment of cancer. We have developed and are testing early prototypes of an optical biopsy system (OBS) for detection of cancer and other tissue pathologies. The OBS invokes a unique approach to optical diagnosis of tissue pathologies based on the elastic scattering properties, over a wide range of wavelengths, of the microscopic structure of the tissue. Absorption bands in the tissue also add useful complexity to the spectral data collected. The use of elastic scattering as the key to optical tissue diagnostics in the OBS is based on the fact that many tissue pathologies, including a majority of cancer forms, manifest significant architectural changes at the cellular and sub-cellular level. Since the cellular components that cause elastic scattering have dimensions typically on the order of visible to near-IR wavelengths, the elastic (Mie) scattering properties will be strongly wavelength dependent. Thus, morphology and size changes can be expected to cause significant changes in an optical signature that is derived from the wavelength-dependence of elastic scattering as well as absorption. The data acquisition and storage/display time with the OBS instrument is {approximately}1 second. Thus, in addition to the reduced invasiveness of this technique compared with current state-of-the-art methods (surgical biopsy and pathology analysis), the OBS offers the possibility of impressively faster diagnostic assessment. The OBS employs a small fiber-optic probe that is amenable to use with any endoscope, catheter or hypodermic, or to direct surface examination (e.g., as in skin cancer or cervical cancer). We report here specifically on its potential application in the detection of bladder cancer.

  3. Identification of new meningococcal serogroup B surface antigens through a systematic analysis of neisserial genomes.

    Science.gov (United States)

    Pajon, Rolando; Yero, Daniel; Niebla, Olivia; Climent, Yanet; Sardiñas, Gretel; García, Darién; Perera, Yasser; Llanes, Alejandro; Delgado, Maité; Cobas, Karem; Caballero, Evelin; Taylor, Stephen; Brookes, Charlotte; Gorringe, Andrew

    2009-12-11

    The difficulty of inducing an effective immune response against the Neisseria meningitidis serogroup B capsular polysaccharide has lead to the search for vaccines for this serogroup based on outer membrane proteins. The availability of the first meningococcal genome (MC58 strain) allowed the expansion of high-throughput methods to explore the protein profile displayed by N. meningitidis. By combining a pan-genome analysis with an extensive experimental validation to identify new potential vaccine candidates, genes coding for antigens likely to be exposed on the surface of the meningococcus were selected after a multistep comparative analysis of entire Neisseria genomes. Eleven novel putative ORF annotations were reported for serogroup B strain MC58. Furthermore, a total of 20 new predicted potential pan-neisserial vaccine candidates were produced as recombinant proteins and evaluated using immunological assays. Potential vaccine candidate coding genes were PCR-amplified from a panel of representative strains and their variability analyzed using maximum likelihood approaches for detecting positive selection. Finally, five proteins all capable of inducing a functional antibody response vs N. meningitidis strain CU385 were identified as new attractive vaccine candidates: NMB0606 a potential YajC orthologue, NMB0928 the neisserial NlpB (BamC), NMB0873 a LolB orthologue, NMB1163 a protein belonging to a curli-like assembly machinery, and NMB0938 (a neisserial specific antigen) with evidence of positive selection appreciated for NMB0928. The new set of vaccine candidates and the novel proposed functions will open a new wave of research in the search for the elusive neisserial vaccine.

  4. Thallium dispersal and contamination in surface sediments from South China and its source identification.

    Science.gov (United States)

    Liu, Juan; Wang, Jin; Chen, Yongheng; Shen, Chuan-Chou; Jiang, Xiuyang; Xie, Xiaofan; Chen, Diyun; Lippold, Holger; Wang, Chunlin

    2016-06-01

    Thallium (Tl) is a non-essential element in humans and it is considered to be highly toxic. In this study, the contents, sources, and dispersal of Tl were investigated in surface sediments from a riverine system (the western Pearl River Basin, China), whose catchment has been contaminated by mining and roasting of Tl-bearing pyrite ores. The isotopic composition of Pb and total contents of Tl and other relevant metals (Pb, Zn, Cd, Co, and Ni) were measured in the pyrite ores, mining and roasting wastes, and the river sediments. Widespread contamination of Tl was observed in the sediments across the river, with the highest concentration of Tl (17.3 mg/kg) measured 4 km downstream from the pyrite industrial site. Application of a modified Institute for Reference Materials and Measurement (IRMM) sequential extraction scheme in representative sediments unveiled that 60-90% of Tl and Pb were present in the residual fraction of the sediments. The sediments contained generally lower (206)Pb/(207)Pb and higher (208)Pb/(206)Pb ratios compared with the natural Pb isotope signature (1.2008 and 2.0766 for (206)Pb/(207)Pb and (208)Pb/(206)Pb, respectively). These results suggested that a significant fraction of non-indigenous Pb could be attributed to the mining and roasting activities of pyrite ores, with low (206)Pb/(207)Pb (1.1539) and high (208)Pb/(206)Pb (2.1263). Results also showed that approximately 6-88% of Tl contamination in the sediments originated from the pyrite mining and roasting activities. This study highlights that Pb isotopic compositions could be used for quantitatively fingerprinting the sources of Tl contamination in sediments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Minimally invasive registration for computer-assisted orthopedic surgery: combining tracked ultrasound and bone surface points via the P-IMLOP algorithm.

    Science.gov (United States)

    Billings, Seth; Kang, Hyun Jae; Cheng, Alexis; Boctor, Emad; Kazanzides, Peter; Taylor, Russell

    2015-06-01

    We present a registration method for computer-assisted total hip replacement (THR) surgery, which we demonstrate to improve the state of the art by both reducing the invasiveness of current methods and increasing registration accuracy. A critical element of computer-guided procedures is the determination of the spatial correspondence between the patient and a computational model of patient anatomy. The current method for establishing this correspondence in robot-assisted THR is to register points intraoperatively sampled by a tracked pointer from the exposed proximal femur and, via auxiliary incisions, from the distal femur. In this paper, we demonstrate a noninvasive technique for sampling points on the distal femur using tracked B-mode ultrasound imaging and present a new algorithm for registering these data called Projected Iterative Most-Likely Oriented Point (P-IMLOP). Points and normal orientations of the distal bone surface are segmented from ultrasound images and registered to the patient model along with points sampled from the exposed proximal femur via a tracked pointer. The proposed approach is evaluated using a bone- and tissue-mimicking leg phantom constructed to enable accurate assessment of experimental registration accuracy with respect to a CT-image-based model of the phantom. These experiments demonstrate that localization of the femur shaft is greatly improved by tracked ultrasound. The experiments further demonstrate that, for ultrasound-based data, the P-IMLOP algorithm significantly improves registration accuracy compared to the standard ICP algorithm. Registration via tracked ultrasound and the P-IMLOP algorithm has high potential to reduce the invasiveness and improve the registration accuracy of computer-assisted orthopedic procedures.

  6. Multi-objective parametric optimization of Inertance type pulse tube refrigerator using response surface methodology and non-dominated sorting genetic algorithm

    Science.gov (United States)

    Rout, Sachindra K.; Choudhury, Balaji K.; Sahoo, Ranjit K.; Sarangi, Sunil K.

    2014-07-01

    The modeling and optimization of a Pulse Tube Refrigerator is a complicated task, due to its complexity of geometry and nature. The aim of the present work is to optimize the dimensions of pulse tube and regenerator for an Inertance-Type Pulse Tube Refrigerator (ITPTR) by using Response Surface Methodology (RSM) and Non-Sorted Genetic Algorithm II (NSGA II). The Box-Behnken design of the response surface methodology is used in an experimental matrix, with four factors and two levels. The diameter and length of the pulse tube and regenerator are chosen as the design variables where the rest of the dimensions and operating conditions of the ITPTR are constant. The required output responses are the cold head temperature (Tcold) and compressor input power (Wcomp). Computational fluid dynamics (CFD) have been used to model and solve the ITPTR. The CFD results agreed well with those of the previously published paper. Also using the results from the 1-D simulation, RSM is conducted to analyse the effect of the independent variables on the responses. To check the accuracy of the model, the analysis of variance (ANOVA) method has been used. Based on the proposed mathematical RSM models a multi-objective optimization study, using the Non-sorted genetic algorithm II (NSGA-II) has been performed to optimize the responses.

  7. An easy-to-implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging (BFN) algorithm

    International Nuclear Information System (INIS)

    Auroux, Didier; Bansart, Patrick; Blum, Jacques

    2008-01-01

    This paper deals with a new data assimilation algorithm called the Back and Forth Nudging. The standard nudging technique consists in adding to the model equations a relaxation term, which is supposed to force the model to the observations. The BFN algorithm consists of repeating forward and backward resolutions of the model with relaxation (or nudging) terms, that have opposite signs in the direct and inverse resolutions, so as to make the backward evolution numerically stable. We then applied the Back and Forth Nudging algorithm to a simple non-linear model: the ID viscous Burgers' equations. The tests were carried out through several case