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.

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.

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.

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.

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.

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

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.

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...

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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)

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.

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.

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.

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.

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

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)

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.

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

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.

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.

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

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.

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)

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

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

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.

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.

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

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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.

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.

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

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.

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.

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...

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.

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.

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.

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

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.

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.

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)

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)

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. 

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...

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)

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.

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)

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.

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

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.

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.

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.

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.

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.

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.

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 ...

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.

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.

[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.

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...

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.

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%.

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/ .

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.

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.

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

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.

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

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

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.

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.

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.

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

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.

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...

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...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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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.

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

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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.

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

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.

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.

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.

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.

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

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.

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.

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

[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.

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.

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

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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.

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

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.

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.

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.

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

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.

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.

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.

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.

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

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.

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.

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

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

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).

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.

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.

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.

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)

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)

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

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.

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.

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.

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.

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.

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.

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.

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

Inference-Based Surface Reconstruction of Cluttered Environments

KAUST Repository

Biggers, K.

2012-08-01

We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion. © 2012 IEEE.

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.

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

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.

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.

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...

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

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.

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.

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

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.

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.

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.

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)

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

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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.

Damage identification on spatial Timoshenko arches by means of genetic algorithms

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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.

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

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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.

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)

Advances of operational modal identification

International Nuclear Information System (INIS)

Zhang, L.

2001-01-01

Operational modal analysis has shown many advantages compared to the traditional one. In this paper, the development of ambient modal identification in time domain is summarized. The mathematical models for modal identification have been presented as unified framework for time domain (TD) System realization algorithms, such as polyrefence (PRCE), extended Ibrahim time domain (EITD) and eigensystem realization algorithm (ERA), etc., and recently developed Stochastic subspace technique (SST). The latest technique named as frequency domain decomposition (FDD) is introduced for operational modal identification, which has many advantages as a frequency domain (FD) technique. Applications of the operational modal analysis in civil and mechanical engineering have shown the success and accuracy of the advanced operational modal identification algorithms- FDD and SST techniques. The major issues of TD and FD operational modal identification are also discussed. (author)

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

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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

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

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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.

Electron identification capabilities of CBM

Energy Technology Data Exchange (ETDEWEB)

Lebedev, Semen [GSI, Darmstadt (Germany)]|[JINR, Dubna (Russian Federation)

2008-07-01

The Compressed Baryonic Matter (CBM) experiment at the future FAIR facility at Darmstadt will measure dileptons emitted from the hot and dense phase in heavy-ion collisions. In case of an electron measurement, a high purity of identified electrons is required in order to suppress the background. Electron identification in CBM will be performed by a RICH and TRD detectors. In this contribution we will present routines which have been developed for electron identification in CBM. A RICH ring recognition algorithm based on the Hough Transform has been implemented. An ellipse fitting algorithm has been elaborated because most of the CBM RICH rings have elliptic shapes, moreover, it helps to improve ring-track matching and electron identification procedures. An Artificial Neural Network can be used in order to suppress fake rings. The electron identification in RICH is substantially improved by the use of TRD information for which 3 different algorithms are implemented. Results of primary electron identification are presented. All developed algorithms were tested on large statistics of simulated events and are included into the CBM software framework for common use.

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)

A speedup technique for (l, d-motif finding algorithms

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Dinh Hieu

2011-03-01

Full Text Available Abstract Background The discovery of patterns in DNA, RNA, and protein sequences has led to the solution of many vital biological problems. For instance, the identification of patterns in nucleic acid sequences has resulted in the determination of open reading frames, identification of promoter elements of genes, identification of intron/exon splicing sites, identification of SH RNAs, location of RNA degradation signals, identification of alternative splicing sites, etc. In protein sequences, patterns have proven to be extremely helpful in domain identification, location of protease cleavage sites, identification of signal peptides, protein interactions, determination of protein degradation elements, identification of protein trafficking elements, etc. Motifs are important patterns that are helpful in finding transcriptional regulatory elements, transcription factor binding sites, functional genomics, drug design, etc. As a result, numerous papers have been written to solve the motif search problem. Results Three versions of the motif search problem have been proposed in the literature: Simple Motif Search (SMS, (l, d-motif search (or Planted Motif Search (PMS, and Edit-distance-based Motif Search (EMS. In this paper we focus on PMS. Two kinds of algorithms can be found in the literature for solving the PMS problem: exact and approximate. An exact algorithm identifies the motifs always and an approximate algorithm may fail to identify some or all of the motifs. The exact version of PMS problem has been shown to be NP-hard. Exact algorithms proposed in the literature for PMS take time that is exponential in some of the underlying parameters. In this paper we propose a generic technique that can be used to speedup PMS algorithms. Conclusions We present a speedup technique that can be used on any PMS algorithm. We have tested our speedup technique on a number of algorithms. These experimental results show that our speedup technique is indeed very

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.

Modeling of Energy Demand in the Greenhouse Using PSO-GA Hybrid Algorithms

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Jiaoliao Chen

2015-01-01

Full Text Available Modeling of energy demand in agricultural greenhouse is very important to maintain optimum inside environment for plant growth and energy consumption decreasing. This paper deals with the identification parameters for physical model of energy demand in the greenhouse using hybrid particle swarm optimization and genetic algorithms technique (HPSO-GA. HPSO-GA is developed to estimate the indistinct internal parameters of greenhouse energy model, which is built based on thermal balance. Experiments were conducted to measure environment and energy parameters in a cooling greenhouse with surface water source heat pump system, which is located in mid-east China. System identification experiments identify model parameters using HPSO-GA such as inertias and heat transfer constants. The performance of HPSO-GA on the parameter estimation is better than GA and PSO. This algorithm can improve the classification accuracy while speeding up the convergence process and can avoid premature convergence. System identification results prove that HPSO-GA is reliable in solving parameter estimation problems for modeling the energy demand in the greenhouse.

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

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

Research on Palmprint Identification Method Based on Quantum Algorithms

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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%.

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

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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.

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.

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.

FORENSIC LINGUISTICS: AUTOMATIC WEB AUTHOR IDENTIFICATION

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A. A. Vorobeva

2016-03-01

Full Text Available Internet is anonymous, this allows posting under a false name, on behalf of others or simply anonymous. Thus, individuals, criminal or terrorist organizations can use Internet for criminal purposes; they hide their identity to avoid the prosecuting. Existing approaches and algorithms for author identification of web-posts on Russian language are not effective. The development of proven methods, technics and tools for author identification is extremely important and challenging task. In this work the algorithm and software for authorship identification of web-posts was developed. During the study the effectiveness of several classification and feature selection algorithms were tested. The algorithm includes some important steps: 1 Feature extraction; 2 Features discretization; 3 Feature selection with the most effective Relief-f algorithm (to find the best feature set with the most discriminating power for each set of candidate authors and maximize accuracy of author identification; 4 Author identification on model based on Random Forest algorithm. Random Forest and Relief-f algorithms are used to identify the author of a short text on Russian language for the first time. The important step of author attribution is data preprocessing - discretization of continuous features; earlier it was not applied to improve the efficiency of author identification. The software outputs top q authors with maximum probabilities of authorship. This approach is helpful for manual analysis in forensic linguistics, when developed tool is used to narrow the set of candidate authors. For experiments on 10 candidate authors, real author appeared in to top 3 in 90.02% cases, on first place real author appeared in 70.5% of cases.

[A new peak detection algorithm of Raman spectra].

Science.gov (United States)

Jiang, Cheng-Zhi; Sun, Qiang; Liu, Ying; Liang, Jing-Qiu; An, Yan; Liu, Bing

2014-01-01

The authors proposed a new Raman peak recognition method named bi-scale correlation algorithm. The algorithm uses the combination of the correlation coefficient and the local signal-to-noise ratio under two scales to achieve Raman peak identification. We compared the performance of the proposed algorithm with that of the traditional continuous wavelet transform method through MATLAB, and then tested the algorithm with real Raman spectra. The results show that the average time for identifying a Raman spectrum is 0.51 s with the algorithm, while it is 0.71 s with the continuous wavelet transform. When the signal-to-noise ratio of Raman peak is greater than or equal to 6 (modern Raman spectrometers feature an excellent signal-to-noise ratio), the recognition accuracy with the algorithm is higher than 99%, while it is less than 84% with the continuous wavelet transform method. The mean and the standard deviations of the peak position identification error of the algorithm are both less than that of the continuous wavelet transform method. Simulation analysis and experimental verification prove that the new algorithm possesses the following advantages: no needs of human intervention, no needs of de-noising and background removal operation, higher recognition speed and higher recognition accuracy. The proposed algorithm is operable in Raman peak identification.

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

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.

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.

Optimizations for the EcoPod field identification tool

Directory of Open Access Journals (Sweden)

Yu YuanYuan

2008-03-01

Full Text Available Abstract Background We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species. Results Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required. Conclusion Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing

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.

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

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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.

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.

Sequential blind identification of underdetermined mixtures using a novel deflation scheme.

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Zhang, Mingjian; Yu, Simin; Wei, Gang

2013-09-01

In this brief, we consider the problem of blind identification in underdetermined instantaneous mixture cases, where there are more sources than sensors. A new blind identification algorithm, which estimates the mixing matrix in a sequential fashion, is proposed. By using the rank-1 detecting device, blind identification is reformulated as a constrained optimization problem. The identification of one column of the mixing matrix hence reduces to an optimization task for which an efficient iterative algorithm is proposed. The identification of the other columns of the mixing matrix is then carried out by a generalized eigenvalue decomposition-based deflation method. The key merit of the proposed deflation method is that it does not suffer from error accumulation. The proposed sequential blind identification algorithm provides more flexibility and better robustness than its simultaneous counterpart. Comparative simulation results demonstrate the superior performance of the proposed algorithm over the simultaneous blind identification algorithm.

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

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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.

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.

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

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

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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.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

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Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

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

IDENTIFICATION ASPECT OF METHODOLOGY DESIGN OF CONTROL SYSTEM TIME-VARIANT PROCESS

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M. M. Blagoveshchenskaia

2014-01-01

Full Text Available Summary. Specificity of a food manufacture demands perfection of automatic control systems of processes in devices, units and installations. Creation of an adaptive control system by technological process of a food on the basis of model of control object it is necessary to carry out the additional analysis for choice algorithm of identification on real enough to representative sample of input data and output signal/data. In article on the basis of simulation it is analyzed over 53 algorithms of recurrent identification plus the basic modifications of these algorithms by 47 criteria for time-varying multivariable linear dynamic objects. On the basis of this analysis for engineering practice for a considered class of objects some algorithms are recommended. Possibilities of the software suite having for today the fullest set of parametrical identification algorithms are discussed. For given specific conditions of comparison in the package identification algorithms for identification of stationary coefficients in the equation object of the most effective were: Yzerman-1, Kaczmarz, Nagumo-Noda, Rastrigin, Kalman filter, the forgetting factor, Zipkin. When pointwise object - Kaczmarz, Nagumo-Noda, Kalman filter; showed the best result identification algorithm-Nagumo Noda.

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

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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.

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.

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.

IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism

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Cuevas-Jiménez E.

2013-01-01

Full Text Available Infinite-impulse-response (IIR filtering provides a powerful approach for solving a variety of problems. However, its design represents a very complicated task, since the error surface of IIR filters is generally multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a new method based on the Electromagnetism-Like Optimization Algorithm (EMO is proposed for IIR filter modeling. EMO originates from the electro-magnetism theory of physics by assuming potential solutions as electrically charged particles which spread around the solution space. The charge of each particle depends on its objective function value. This algorithm employs a collective attraction-repulsion mechanism to move the particles towards optimality. The experimental results confirm the high performance of the proposed method in solving various benchmark identification problems.

A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

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.

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

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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.

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.

Minimum Probability of Error-Based Equalization Algorithms for Fading Channels

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Janos Levendovszky

2007-06-01

Full Text Available Novel channel equalizer algorithms are introduced for wireless communication systems to combat channel distortions resulting from multipath propagation. The novel algorithms are based on newly derived bounds on the probability of error (PE and guarantee better performance than the traditional zero forcing (ZF or minimum mean square error (MMSE algorithms. The new equalization methods require channel state information which is obtained by a fast adaptive channel identification algorithm. As a result, the combined convergence time needed for channel identification and PE minimization still remains smaller than the convergence time of traditional adaptive algorithms, yielding real-time equalization. The performance of the new algorithms is tested by extensive simulations on standard mobile channels.

Identification of dental root canals and their medial line from micro-CT and cone-beam CT records

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Benyó Balázs

2012-10-01

Full Text Available Abstract Background Shape of the dental root canal is highly patient specific. Automated identification methods of the medial line of dental root canals and the reproduction of their 3D shape can be beneficial for planning endodontic interventions as severely curved root canals or multi-rooted teeth may pose treatment challenges. Accurate shape information of the root canals may also be used by manufacturers of endodontic instruments in order to make more efficient clinical tools. Method Novel image processing procedures dedicated to the automated detection of the medial axis of the root canal from dental micro-CT and cone-beam CT records are developed. For micro-CT, the 3D model of the root canal is built up from several hundred parallel cross sections, using image enhancement, histogram based fuzzy c-means clustering, center point detection in the segmented slice, three dimensional inner surface reconstruction, and potential field driven curve skeleton extraction in three dimensions. Cone-beam CT records are processed with image enhancement filters and fuzzy chain based regional segmentation, followed by the reconstruction of the root canal surface and detecting its skeleton via a mesh contraction algorithm. Results The proposed medial line identification and root canal detection algorithms are validated on clinical data sets. 25 micro-CT and 36 cone-beam-CT records are used in the validation procedure. The overall success rate of the automatic dental root canal identification was about 92% in both procedures. The algorithms proved to be accurate enough for endodontic therapy planning. Conclusions Accurate medial line identification and shape detection algorithms of dental root canal have been developed. Different procedures are defined for micro-CT and cone-beam CT records. The automated execution of the subsequent processing steps allows easy application of the algorithms in the dental care. The output data of the image processing procedures

Fast algorithm for Morphological Filters

International Nuclear Information System (INIS)

Lou Shan; Jiang Xiangqian; Scott, Paul J

2011-01-01

In surface metrology, morphological filters, which evolved from the envelope filtering system (E-system) work well for functional prediction of surface finish in the analysis of surfaces in contact. The naive algorithms are time consuming, especially for areal data, and not generally adopted in real practice. A fast algorithm is proposed based on the alpha shape. The hull obtained by rolling the alpha ball is equivalent to the morphological opening/closing in theory. The algorithm depends on Delaunay triangulation with time complexity O(nlogn). In comparison to the naive algorithms it generates the opening and closing envelope without combining dilation and erosion. Edge distortion is corrected by reflective padding for open profiles/surfaces. Spikes in the sample data are detected and points interpolated to prevent singularities. The proposed algorithm works well both for morphological profile and area filters. Examples are presented to demonstrate the validity and superiority on efficiency of this algorithm over the naive algorithm.

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.

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

Identification of surface proteins in Enterococcus faecalis V583

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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.

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.

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.

Recursive Subspace Identification of AUV Dynamic Model under General Noise Assumption

Directory of Open Access Journals (Sweden)

Zheping Yan

2014-01-01

Full Text Available A recursive subspace identification algorithm for autonomous underwater vehicles (AUVs is proposed in this paper. Due to the advantages at handling nonlinearities and couplings, the AUV model investigated here is for the first time constructed as a Hammerstein model with nonlinear feedback in the linear part. To better take the environment and sensor noises into consideration, the identification problem is concerned as an errors-in-variables (EIV one which means that the identification procedure is under general noise assumption. In order to make the algorithm recursively, propagator method (PM based subspace approach is extended into EIV framework to form the recursive identification method called PM-EIV algorithm. With several identification experiments carried out by the AUV simulation platform, the proposed algorithm demonstrates its effectiveness and feasibility.

Note: Design of FPGA based system identification module with application to atomic force microscopy

Science.gov (United States)

Ghosal, Sayan; Pradhan, Sourav; Salapaka, Murti

2018-05-01

The science of system identification is widely utilized in modeling input-output relationships of diverse systems. In this article, we report field programmable gate array (FPGA) based implementation of a real-time system identification algorithm which employs forgetting factors and bias compensation techniques. The FPGA module is employed to estimate the mechanical properties of surfaces of materials at the nano-scale with an atomic force microscope (AFM). The FPGA module is user friendly which can be interfaced with commercially available AFMs. Extensive simulation and experimental results validate the design.

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...

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.

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

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.

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.

The secondary vertex finding algorithm with the ATLAS detector

CERN Document Server

Heer, Sebastian; The ATLAS collaboration

2017-01-01

A high performance identification of jets, produced via fragmentation of bottom quarks, is crucial for the ATLAS physics program. These jets can be identified by exploiting the presence of cascade decay vertices from bottom hadrons. A general vertex-finding algorithm is introduced and its ap- plication to the search for secondary vertices inside jets is described. Kinematic properties of the reconstructed vertices are used to construct several b-jet identification algorithms. The features and performance of the secondary vertex finding algorithm in a jet, as well as the performance of the jet tagging algorithms, are studied using simulated $pp$ -> $t\\bar{t}$ events at a centre-of-mass energy of 13 TeV.

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)

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

OPTICAL correlation identification technology applied in underwater laser imaging target identification

Science.gov (United States)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

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.

Backtracking algorithm for lepton reconstruction with HADES

International Nuclear Information System (INIS)

Sellheim, P

2015-01-01

The High Acceptance Di-Electron Spectrometer (HADES) at the GSI Helmholtzzentrum für Schwerionenforschung investigates dilepton and strangeness production in elementary and heavy-ion collisions. In April - May 2012 HADES recorded 7 billion Au+Au events at a beam energy of 1.23 GeV/u with the highest multiplicities measured so far. The track reconstruction and particle identification in the high track density environment are challenging. The most important detector component for lepton identification is the Ring Imaging Cherenkov detector. Its main purpose is the separation of electrons and positrons from large background of charged hadrons produced in heavy-ion collisions. In order to improve lepton identification this backtracking algorithm was developed. In this contribution we will show the results of the algorithm compared to the currently applied method for e +/- identification. Efficiency and purity of a reconstructed e +/- sample will be discussed as well. (paper)

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

Investigation of energy windowing algorithms for effective cargo screening with radiation portal monitors

International Nuclear Information System (INIS)

Hevener, Ryne; Yim, Man-Sung; Baird, Ken

2013-01-01

Radiation portal monitors (RPMs) are distributed across the globe in an effort to decrease the illicit trafficking of nuclear materials. Many current generation RPMs utilizes large polyvinyltoluene (PVT) plastic scintillators. These detectors are low cost and reliable but have very poor energy resolution. The lack of spectroscopic detail available from PVT spectra has restricted these systems primarily to performing simple gross counting measurements in the past. A common approach to extend the capability of PVT detectors beyond simple “gross-gamma” use is to apply a technique known as energy windowing (EW) to perform rough nuclide identification with limited spectral information. An approach to creating EW algorithms was developed in this work utilizing a specific set of calibration sources and modified EW equations; this algorithm provided a degree of increased identification capability. A simulated real-time emulation of the algorithm utilizing actual port-of-entry RPM data supplied by ORNL provided an extensive proving ground for the algorithm. This algorithm is able to identify four potential threat nuclides and the major NORM source with a high degree of accuracy. High-energy masking, a major detriment of EW algorithms, is reduced by the algorithm's design. - Highlights: • Gross counting algorithms do not produce detailed screenings. • Energy windowing algorithms enhance nuclide identification capability. • Proper use of EW algorithm can identify multiple threat nuclides. • Utilizing specific set of calibration sources is important for nuclide identification

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.

The advantages of the surface Laplacian in brain-computer interface research.

Science.gov (United States)

McFarland, Dennis J

2015-09-01

Brain-computer interface (BCI) systems frequently use signal processing methods, such as spatial filtering, to enhance performance. The surface Laplacian can reduce spatial noise and aid in identification of sources. In BCI research, these two functions of the surface Laplacian correspond to prediction accuracy and signal orthogonality. In the present study, an off-line analysis of data from a sensorimotor rhythm-based BCI task dissociated these functions of the surface Laplacian by comparing nearest-neighbor and next-nearest neighbor Laplacian algorithms. The nearest-neighbor Laplacian produced signals that were more orthogonal while the next-nearest Laplacian produced signals that resulted in better accuracy. Both prediction and signal identification are important for BCI research. Better prediction of user's intent produces increased speed and accuracy of communication and control. Signal identification is important for ruling out the possibility of control by artifacts. Identifying the nature of the control signal is relevant both to understanding exactly what is being studied and in terms of usability for individuals with limited motor control. Copyright © 2014 Elsevier B.V. All rights reserved.

Noise Reduction with Microphone Arrays for Speaker Identification

Energy Technology Data Exchange (ETDEWEB)

Cohen, Z

2011-12-22

Reducing acoustic noise in audio recordings is an ongoing problem that plagues many applications. This noise is hard to reduce because of interfering sources and non-stationary behavior of the overall background noise. Many single channel noise reduction algorithms exist but are limited in that the more the noise is reduced; the more the signal of interest is distorted due to the fact that the signal and noise overlap in frequency. Specifically acoustic background noise causes problems in the area of speaker identification. Recording a speaker in the presence of acoustic noise ultimately limits the performance and confidence of speaker identification algorithms. In situations where it is impossible to control the environment where the speech sample is taken, noise reduction filtering algorithms need to be developed to clean the recorded speech of background noise. Because single channel noise reduction algorithms would distort the speech signal, the overall challenge of this project was to see if spatial information provided by microphone arrays could be exploited to aid in speaker identification. The goals are: (1) Test the feasibility of using microphone arrays to reduce background noise in speech recordings; (2) Characterize and compare different multichannel noise reduction algorithms; (3) Provide recommendations for using these multichannel algorithms; and (4) Ultimately answer the question - Can the use of microphone arrays aid in speaker identification?

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.

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.

System identification using Nuclear Norm & Tabu Search optimization

Science.gov (United States)

Ahmed, Asif A.; Schoen, Marco P.; Bosworth, Ken W.

2018-01-01

In recent years, subspace System Identification (SI) algorithms have seen increased research, stemming from advanced minimization methods being applied to the Nuclear Norm (NN) approach in system identification. These minimization algorithms are based on hard computing methodologies. To the authors’ knowledge, as of now, there has been no work reported that utilizes soft computing algorithms to address the minimization problem within the nuclear norm SI framework. A linear, time-invariant, discrete time system is used in this work as the basic model for characterizing a dynamical system to be identified. The main objective is to extract a mathematical model from collected experimental input-output data. Hankel matrices are constructed from experimental data, and the extended observability matrix is employed to define an estimated output of the system. This estimated output and the actual - measured - output are utilized to construct a minimization problem. An embedded rank measure assures minimum state realization outcomes. Current NN-SI algorithms employ hard computing algorithms for minimization. In this work, we propose a simple Tabu Search (TS) algorithm for minimization. TS algorithm based SI is compared with the iterative Alternating Direction Method of Multipliers (ADMM) line search optimization based NN-SI. For comparison, several different benchmark system identification problems are solved by both approaches. Results show improved performance of the proposed SI-TS algorithm compared to the NN-SI ADMM algorithm.

Inclusive Flavour Tagging Algorithm

International Nuclear Information System (INIS)

Likhomanenko, Tatiana; Derkach, Denis; Rogozhnikov, Alex

2016-01-01

Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment. (paper)

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.

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

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.

Basics of identification measurement technology

Science.gov (United States)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Optimization of an individual re-identification modeling process using biometric features

Energy Technology Data Exchange (ETDEWEB)

Heredia-Langner, Alejandro; Amidan, Brett G.; Matzner, Shari; Jarman, Kristin H.

2014-09-24

We present results from the optimization of a re-identification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available produce better re-identification rates than two other approaches that use all the information available.

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

Electron identification capabilities of the CBM experiment at FAIR

Energy Technology Data Exchange (ETDEWEB)

Hoehne, Claudia; Kisel, Ivan [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Darmstadt (Germany); Lebedev, Semen [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Darmstadt (Germany); Laboratory of Information Technologies, Joint Institute for Nuclear Research, Dubna (Russian Federation); Ososkov, Gennady [Laboratory of Information Technologies, Joint Institute for Nuclear Research, Dubna (Russian Federation)

2010-07-01

The Compressed Baryonic Matter (CBM) experiment at the future FAIR facility at Darmstadt will measure dileptons emitted from the hot and dense phase in heavy-ion collisions. In case of an electron measurement, a high purity of identified electrons is required in order to suppress the background. Electron identification in CBM will be performed by a RICH and TRD detectors. In this contribution, methods which have been developed for the electron identification in CBM are presented. A fast and efficient RICH ring recognition algorithm based on the Hough Transform has been implemented. An ellipse fitting algorithm has been elaborated because most of the CBM RICH rings have elliptic shapes. An Artificial Neural Network can be used in order to suppress fake rings. The electron identification in RICH is substantially improved by the use of TRD detectors for which several different algorithms for electron identification are implemented. Results of electron identification and pion suppression are presented.

Snake Model Based on Improved Genetic Algorithm in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Mingying Zhang

2016-12-01

Full Text Available Automatic fingerprint identification technology is a quite mature research field in biometric identification technology. As the preprocessing step in fingerprint identification, fingerprint segmentation can improve the accuracy of fingerprint feature extraction, and also reduce the time of fingerprint preprocessing, which has a great significance in improving the performance of the whole system. Based on the analysis of the commonly used methods of fingerprint segmentation, the existing segmentation algorithm is improved in this paper. The snake model is used to segment the fingerprint image. Additionally, it is improved by using the global optimization of the improved genetic algorithm. Experimental results show that the algorithm has obvious advantages both in the speed of image segmentation and in the segmentation effect.

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)

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)

LAT Onboard Science: Gamma-Ray Burst Identification

International Nuclear Information System (INIS)

Kuehn, Frederick; Hughes, Richard; Smith, Patrick; Winer, Brian; Bonnell, Jerry; Norris, Jay; Ritz, Steven; Russell, James

2007-01-01

The main goal of the Large Area Telescope (LAT) onboard science program is to provide quick identification and localization of Gamma Ray Bursts (GRB) onboard the LAT for follow-up observations by other observatories. The GRB identification and localization algorithm will provide celestial coordinates with an error region that will be distributed via the Gamma ray burst Coordinate Network (GCN). We present results that show our sensitivity to bursts as characterized using Monte Carlo simulations of the GLAST observatory. We describe and characterize the method of onboard track determination and the GRB identification and localization algorithm. Onboard track determination is considerably different than in the on-ground case, resulting in a substantially altered point spread function. The algorithm contains tunable parameters which may be adjusted after launch when real bursts characteristics at very high energies have been identified

Remote measurement of surface roughness, surface reflectance, and body reflectance with LiDAR.

Science.gov (United States)

Li, Xiaolu; Liang, Yu

2015-10-20

Light detection and ranging (LiDAR) intensity data are attracting increasing attention because of the great potential for use of such data in a variety of remote sensing applications. To fully investigate the data potential for target classification and identification, we carried out a series of experiments with typical urban building materials and employed our reconstructed built-in-lab LiDAR system. Received intensity data were analyzed on the basis of the derived bidirectional reflectance distribution function (BRDF) model and the established integration method. With an improved fitting algorithm, parameters involved in the BRDF model can be obtained to depict the surface characteristics. One of these parameters related to surface roughness was converted to a most used roughness parameter, the arithmetical mean deviation of the roughness profile (Ra), which can be used to validate the feasibility of the BRDF model in surface characterizations and performance evaluations.

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)

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.

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.

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-...

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.

Automatic contact algorithm in ppercase[dyna3d] for crashworthiness and impact problems

International Nuclear Information System (INIS)

Whirley, Robert G.; Engelmann, Bruce E.

1994-01-01

This paper presents a new approach for the automatic definition and treatment of mechanical contact in explicit non-linear finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. Key aspects of the proposed new method include automatic identification of adjacent and opposite surfaces in the global search phase, and the use of a well-defined surface normal which allows a consistent treatment of shell intersection and corner contact conditions without adhoc rules. The paper concludes with three examples which illustrate the performance of the newly proposed algorithm in the public ppercase[dyna3d] code. ((orig.))

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.

Dynamic training algorithm for dynamic neural networks

International Nuclear Information System (INIS)

Tan, Y.; Van Cauwenberghe, A.; Liu, Z.

1996-01-01

The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper

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.

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.

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.

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.

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.

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.

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

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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.

Overhead longwave infrared hyperspectral material identification using radiometric models

Energy Technology Data Exchange (ETDEWEB)

Zelinski, M. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2018-01-09

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimal atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.

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

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Directory of Open Access Journals (Sweden)

Ossmann Daniel

2015-03-01

Full Text Available We propose linear parameter-varying (LPV model-based approaches to the synthesis of robust fault detection and diagnosis (FDD systems for loss of efficiency (LOE faults of flight actuators. The proposed methods are applicable to several types of parametric (or multiplicative LOE faults such as actuator disconnection, surface damage, actuator power loss or stall loads. For the detection of these parametric faults, advanced LPV-model detection techniques are proposed, which implicitly provide fault identification information. Fast detection of intermittent stall loads (seen as nuisances, rather than faults is important in enhancing the performance of various fault detection schemes dealing with large input signals. For this case, a dedicated fast identification algorithm is devised. The developed FDD systems are tested on a nonlinear actuator model which is implemented in a full nonlinear aircraft simulation model. This enables the validation of the FDD system’s detection and identification characteristics under realistic conditions.

Optimized Bayesian dynamic advising theory and algorithms

CERN Document Server

Karny, Miroslav

2006-01-01

Written by one of the world's leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, the book comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modelling by dynamic mixture models

The NNSYSID Toolbox - A MATLAB Toolbox for System Identification with Neural Networks

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Ravn, Ole; Hansen, Lars Kai

1996-01-01

To assist the identification of nonlinear dynamic systems, a set of tools has been developed for the MATLAB(R) environment. The tools include a number of different model structures, highly effective training algorithms, functions for validating trained networks, and pruning algorithms for determi......To assist the identification of nonlinear dynamic systems, a set of tools has been developed for the MATLAB(R) environment. The tools include a number of different model structures, highly effective training algorithms, functions for validating trained networks, and pruning algorithms...

Parameter Estimation of Damped Compound Pendulum Using Bat Algorithm

Directory of Open Access Journals (Sweden)

Saad Mohd Sazli

2016-01-01

Full Text Available In this study, the parameter identification of the damped compound pendulum system is proposed using one of the most promising nature inspired algorithms which is Bat Algorithm (BA. The procedure used to achieve the parameter identification of the experimental system consists of input-output data collection, ARX model order selection and parameter estimation using bat algorithm (BA method. PRBS signal is used as an input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the autoregressive with exogenous input (ARX model. The performance of the model is validated using mean squares error (MSE between the actual and predicted output responses of the models. Finally, comparative study is conducted between BA and the conventional estimation method (i.e. Least Square. Based on the results obtained, MSE produce from Bat Algorithm (BA is outperformed the Least Square (LS method.

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.)

Novel search algorithms for a mid-infrared spectral library of cotton contaminants.

Science.gov (United States)

Loudermilk, J Brian; Himmelsbach, David S; Barton, Franklin E; de Haseth, James A

2008-06-01

During harvest, a variety of plant based contaminants are collected along with cotton lint. The USDA previously created a mid-infrared, attenuated total reflection (ATR), Fourier transform infrared (FT-IR) spectral library of cotton contaminants for contaminant identification as the contaminants have negative impacts on yarn quality. This library has shown impressive identification rates for extremely similar cellulose based contaminants in cases where the library was representative of the samples searched. When spectra of contaminant samples from crops grown in different geographic locations, seasons, and conditions and measured with a different spectrometer and accessories were searched, identification rates for standard search algorithms decreased significantly. Six standard algorithms were examined: dot product, correlation, sum of absolute values of differences, sum of the square root of the absolute values of differences, sum of absolute values of differences of derivatives, and sum of squared differences of derivatives. Four categories of contaminants derived from cotton plants were considered: leaf, stem, seed coat, and hull. Experiments revealed that the performance of the standard search algorithms depended upon the category of sample being searched and that different algorithms provided complementary information about sample identity. These results indicated that choosing a single standard algorithm to search the library was not possible. Three voting scheme algorithms based on result frequency, result rank, category frequency, or a combination of these factors for the results returned by the standard algorithms were developed and tested for their capability to overcome the unpredictability of the standard algorithms' performances. The group voting scheme search was based on the number of spectra from each category of samples represented in the library returned in the top ten results of the standard algorithms. This group algorithm was able to identify

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

Stability Analysis of Neural Networks-Based System Identification

Directory of Open Access Journals (Sweden)

Talel Korkobi

2008-01-01

Full Text Available This paper treats some problems related to nonlinear systems identification. A stability analysis neural network model for identifying nonlinear dynamic systems is presented. A constrained adaptive stable backpropagation updating law is presented and used in the proposed identification approach. The proposed backpropagation training algorithm is modified to obtain an adaptive learning rate guarantying convergence stability. The proposed learning rule is the backpropagation algorithm under the condition that the learning rate belongs to a specified range defining the stability domain. Satisfying such condition, unstable phenomena during the learning process are avoided. A Lyapunov analysis leads to the computation of the expression of a convenient adaptive learning rate verifying the convergence stability criteria. Finally, the elaborated training algorithm is applied in several simulations. The results confirm the effectiveness of the CSBP algorithm.

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.

A Joint Approach for Single-Channel Speaker Identification and Speech Separation

DEFF Research Database (Denmark)

Mowlaee, Pejman; Saeidi, Rahim; Christensen, Mads Græsbøll

2012-01-01

) accuracy, here, we report the objective and subjective results as well. The results show that the proposed system performs as well as the best of the state-of-the-art in terms of perceived quality while its performance in terms of speaker identification and automatic speech recognition results......In this paper, we present a novel system for joint speaker identification and speech separation. For speaker identification a single-channel speaker identification algorithm is proposed which provides an estimate of signal-to-signal ratio (SSR) as a by-product. For speech separation, we propose...... a sinusoidal model-based algorithm. The speech separation algorithm consists of a double-talk/single-talk detector followed by a minimum mean square error estimator of sinusoidal parameters for finding optimal codevectors from pre-trained speaker codebooks. In evaluating the proposed system, we start from...

Denture identification using unique identification authority of India barcode

OpenAIRE

Sudhindra Mahoorkar; Anoop Jain

2013-01-01

Over the years, various denture marking systems have been reported in the literature for personal identification. They have been broadly divided into surface marking and inclusion methods. In this technique, patient's unique identification number and barcode printed in the patient's Aadhaar card issued by Unique Identification Authority of India (UIDAI) are used as denture markers. This article describes a simple, quick, and economical method for identification of individual.

Denture identification using unique identification authority of India barcode.

Science.gov (United States)

Mahoorkar, Sudhindra; Jain, Anoop

2013-01-01

Over the years, various denture marking systems have been reported in the literature for personal identification. They have been broadly divided into surface marking and inclusion methods. In this technique, patient's unique identification number and barcode printed in the patient's Aadhaar card issued by Unique Identification Authority of India (UIDAI) are used as denture markers. This article describes a simple, quick, and economical method for identification of individual.

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.

Automated Identification of Fiducial Points on 3D Torso Images

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Manas M. Kawale

2013-01-01

Full Text Available Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D coordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship.

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.

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.

Identification of computer graphics objects

Directory of Open Access Journals (Sweden)

Rossinskyi Yu.M.

2016-04-01

Full Text Available The article is devoted to the use of computer graphics methods in problems of creating drawings, charts, drafting, etc. The widespread use of these methods requires the development of efficient algorithms for the identification of objects of drawings. The article analyzes the model-making algorithms for this problem and considered the possibility of reducing the time using graphics editing operations. Editing results in such operations as copying, moving and deleting objects specified images. These operations allow the use of a reliable identification of images of objects methods. For information on the composition of the image of the object along with information about the identity and the color should include information about the spatial location and other characteristics of the object (the thickness and style of contour lines, fill style, and so on. In order to enable the pixel image analysis to structure the information it is necessary to enable the initial code image objects color. The article shows the results of the implementation of the algorithm of encoding object identifiers. To simplify the process of building drawings of any kind, and reduce time-consuming, method of drawing objects identification is proposed based on the use as the ID information of the object color.

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.

PARAMETRIC IDENTIFICATION OF STOCHASTIC SYSTEM BY NON-GRADIENT RANDOM SEARCHING

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A. A. Lobaty

2017-01-01

Full Text Available At this moment we know a great variety of identification objects, tasks and methods and its significance is constantly increasing in various fields of science and technology.  The identification problem is dependent on a priori information about identification object, besides that  the existing approaches and methods of identification are determined by the form of mathematical models (deterministic, stochastic, frequency, temporal, spectral etc.. The paper considers a problem for determination of system parameters  (identification object which is assigned by the stochastic mathematical model including random functions of time. It has been shown  that while making optimization of the stochastic systems subject to random actions deterministic methods can be applied only for a limited approximate optimization of the system by taking into account average random effects and fixed structure of the system. The paper proposes an algorithm for identification of  parameters in a mathematical model of  the stochastic system by non-gradient random searching. A specific  feature  of the algorithm is its applicability  practically to mathematic models of any type because the applied algorithm does not depend on linearization and differentiability of functions included in the mathematical model of the system. The proposed algorithm  ensures searching of  an extremum for the specified quality criteria in terms of external uncertainties and limitations while using random searching of parameters for a mathematical model of the system. The paper presents results of the investigations on operational capability of the considered identification method  while using mathematical simulation of hypothetical control system with a priori unknown parameter values of the mathematical model. The presented results of the mathematical simulation obviously demonstrate the operational capability of the proposed identification method.

Enhanced object-based tracking algorithm for convective rain storms and cells

Science.gov (United States)

Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

2018-03-01

This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

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.

Subspace System Identification of the Kalman Filter

Directory of Open Access Journals (Sweden)

David Di Ruscio

2003-07-01

Full Text Available Some proofs concerning a subspace identification algorithm are presented. It is proved that the Kalman filter gain and the noise innovations process can be identified directly from known input and output data without explicitly solving the Riccati equation. Furthermore, it is in general and for colored inputs, proved that the subspace identification of the states only is possible if the deterministic part of the system is known or identified beforehand. However, if the inputs are white, then, it is proved that the states can be identified directly. Some alternative projection matrices which can be used to compute the extended observability matrix directly from the data are presented. Furthermore, an efficient method for computing the deterministic part of the system is presented. The closed loop subspace identification problem is also addressed and it is shown that this problem is solved and unbiased estimates are obtained by simply including a filter in the feedback. Furthermore, an algorithm for consistent closed loop subspace estimation is presented. This algorithm is using the controller parameters in order to overcome the bias problem.

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.

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.

Effects of surface-mapping corrections and synthetic-aperture focusing techniques on ultrasonic imaging

International Nuclear Information System (INIS)

Barna, B.A.; Johnson, J.A.

1981-01-01

Improvements in ultrasonic imaging that can be obtained using algorithms that map the surface of targets are evaluated. This information is incorporated in the application of synthetic-aperture focusing techniques which also have the potential to improve image resolution. Images obtained using directed-beam (flat) transducers and the focused transducers normally used for synthetic-aperture processing are quantitatively compared by using no processing, synthetic-aperture processing with no corrections for surface variations, and synthetic-aperture processing with surface mapping. The unprocessed images have relatively poor lateral resolutions because echoes from two adjacent reflectors show interference effects which prevent their identification even if the spacing is larger than the single-hole resolution. The synthetic-aperture-processed images show at least a twofold improvement in lateral resolution and greatly reduced interference effects in multiple-hole images compared to directed-beam images. Perhaps more importantly, in images of test blocks with substantial surface variations portions of the image are displaced from their actual positions by several wavelengths. To correct for this effect an algorithm has been developed for calculating the surface variations. The corrected images produced using this algorithm are accurate within the experimental error. In addition, the same algorithm, when applied to the directed-beam data, produced images that are not only accurately positioned, but that also have a resolution comparable to conventional synthetic-aperture-processed images obtained from focused-transducer data. This suggests that using synthetic-aperture processing on the type of data normally collected during directed-beam ultrasonic inspections would eliminate the need to rescan for synthetic-aperture enhancement

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.

Integrated identification, modeling and control with applications

Science.gov (United States)

Shi, Guojun

This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing

Advanced hybrid query tree algorithm based on slotted backoff mechanism in RFID

Directory of Open Access Journals (Sweden)

XIE Xiaohui

2013-12-01

Full Text Available The merits of performance quality for a RFID system are determined by the effectiveness of tag anti-collision algorithm.Many algorithms for RFID system of tag identification have been proposed,but they all have obvious weaknesses,such as slow speed of identification,unstable and so on.The existing algorithms can be divided into two groups,one is based on ALOHA and another is based on query tree.This article is based on the hybrid query tree algorithm,combined with a slotted backoff mechanism and a specific encoding (Manchester encoding.The number of value“1” in every three consecutive bits of tags is used to determine the tag response time slots,which will greatly reduce the time slot of the collision and improve the recognition efficiency.

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

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.

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.

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.

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.

Identification of Super Phenix steam generator by a simple polynomial model

International Nuclear Information System (INIS)

Rousseau, I.

1981-01-01

This note suggests a method of identification for the steam generator of the Super-Phenix fast neutron power plant for simple polynomial models. This approach is justified in the selection of the adaptive control. The identification algorithms presented will be applied to multivariable input-output behaviours. The results obtained with the representation in self-regressive form and by simple polynomial models will be compared and the effect of perturbations on the output signal will be tested, in order to select a good identification algorithm for multivariable adaptive regulation [fr

Chaotic invasive weed optimization algorithm with application to parameter estimation of chaotic systems

International Nuclear Information System (INIS)

Ahmadi, Mohamadreza; Mojallali, Hamed

2012-01-01

Highlights: ► A new meta-heuristic optimization algorithm. ► Integration of invasive weed optimization and chaotic search methods. ► A novel parameter identification scheme for chaotic systems. - Abstract: This paper introduces a novel hybrid optimization algorithm by taking advantage of the stochastic properties of chaotic search and the invasive weed optimization (IWO) method. In order to deal with the weaknesses associated with the conventional method, the proposed chaotic invasive weed optimization (CIWO) algorithm is presented which incorporates the capabilities of chaotic search methods. The functionality of the proposed optimization algorithm is investigated through several benchmark multi-dimensional functions. Furthermore, an identification technique for chaotic systems based on the CIWO algorithm is outlined and validated by several examples. The results established upon the proposed scheme are also supplemented which demonstrate superior performance with respect to other conventional methods.

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

Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

Directory of Open Access Journals (Sweden)

Jinfeng Zou

Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

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.

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

Identification of the Parameters of the Instantaneous Point Pollution Source in the Azov Sea Based on the Adjoint Method

Directory of Open Access Journals (Sweden)

V.S. Kochergin

2017-02-01

Full Text Available The passive admixture transport model in the Azov Sea is considered. The problem of cartelistic impulse local source identification at the sea surface based on adjoint method is solving by integration of independent series of adjoint tasks. Simultaneous solution of this problem at the parallel mode is realized by the aforementioned approach. The efficiency of the algorithm optimal value power of source search agreed with the data measurements is shown in the test example. The measurement data assimilation algorithm in the passive admixture transfer model is implemented applying variational methods of filtration for optimal estimate retrieval. The retrieval is carried out by means of the method of adjoint equations and solving of linear systems. On the basis of the variational filtration method of data assimilation, the optimal estimate retrieval algorithm for pollution source power identification is constructed. In application of the algorithm, the integration of the main, linked and adjoint problems is implemented. Integration problems are solved using TVD approximations. For the application of the procedure, the Azov current fields and turbulent diffusion coefficients are obtained using the sigma coordinate ocean model (POM under the eastern wind stress conditions being dominant at the observed time period. Furthermore, the results can be used to perform numerical data assimilation on loads of suspended matter.

Discrimination of human and nonhuman blood using Raman spectroscopy with self-reference algorithm

Science.gov (United States)

Bian, Haiyi; Wang, Peng; Wang, Jun; Yin, Huancai; Tian, Yubing; Bai, Pengli; Wu, Xiaodong; Wang, Ning; Tang, Yuguo; Gao, Jing

2017-09-01

We report a self-reference algorithm to discriminate human and nonhuman blood by calculating the ratios of identification Raman peaks to reference Raman peaks and choosing appropriate threshold values. The influence of using different reference peaks and identification peaks was analyzed in detail. The Raman peak at 1003 cm-1 was proved to be a stable reference peak to avoid the influencing factors, such as the incident laser intensity and the amount of sample. The Raman peak at 1341 cm-1 was found to be an efficient identification peak, which indicates that the difference between human and nonhuman blood results from the C-H bend in tryptophan. The comparison between self-reference algorithm and partial least square method was made. It was found that the self-reference algorithm not only obtained the discrimination results with the same accuracy, but also provided information on the difference of chemical composition. In addition, the performance of self-reference algorithm whose true positive rate is 100% is significant for customs inspection to avoid genetic disclosure and forensic science.

Estimating spatial travel times using automatic vehicle identification data

Science.gov (United States)

2001-01-01

Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

Embedded gamma spectrometry: new algorithms for spectral analysis

International Nuclear Information System (INIS)

Martin-Burtart, Nicolas

2012-01-01

Airborne gamma spectrometry was first used for mining prospecting. Three main families were looked for: K-40, U-238 and Th-232. The Chernobyl accident acted as a trigger and for the last fifteen years, a lot of new systems have been developed for intervention in case of nuclear accident or environmental purposes. Depending on their uses, new algorithms were developed, mainly for medium or high energy signal extraction. These spectral regions are characteristics of natural emissions (K-40, U-238 and Th-232 decay chains) and fissions products (mainly Cs-137 and Co-60). Below 400 keV, where special nuclear materials emit, these methods can still be used but are greatly imprecise. A new algorithm called 2-windows (extended to 3), was developed. It allows an accurate extraction, taking the flight altitude into account to minimize false detection. Watching radioactive materials traffic appeared with homeland security policy a few years ago. This particular use of dedicated sensors require a new type of algorithms. Before, one algorithm was very efficient for a particular nuclide or spectral region. Now, we need algorithm able to detect an anomaly wherever it is and whatever it is: industrial, medical or SNM. This work identified two families of methods working under these circumstances. Finally, anomalies have to be identified. IAEA recommend to watch around 30 radionuclides. A brand new identification algorithm was developed, using several rays per element and avoiding identifications conflicts. (author) [fr

Classification of grass pollen through the quantitative analysis of surface ornamentation and texture.

Science.gov (United States)

Mander, Luke; Li, Mao; Mio, Washington; Fowlkes, Charless C; Punyasena, Surangi W

2013-11-07

Taxonomic identification of pollen and spores uses inherently qualitative descriptions of morphology. Consequently, identifications are restricted to categories that can be reliably classified by multiple analysts, resulting in the coarse taxonomic resolution of the pollen and spore record. Grass pollen represents an archetypal example; it is not routinely identified below family level. To address this issue, we developed quantitative morphometric methods to characterize surface ornamentation and classify grass pollen grains. This produces a means of quantifying morphological features that are traditionally described qualitatively. We used scanning electron microscopy to image 240 specimens of pollen from 12 species within the grass family (Poaceae). We classified these species by developing algorithmic features that quantify the size and density of sculptural elements on the pollen surface, and measure the complexity of the ornamentation they form. These features yielded a classification accuracy of 77.5%. In comparison, a texture descriptor based on modelling the statistical distribution of brightness values in image patches yielded a classification accuracy of 85.8%, and seven human subjects achieved accuracies between 68.33 and 81.67%. The algorithmic features we developed directly relate to biologically meaningful features of grass pollen morphology, and could facilitate direct interpretation of unsupervised classification results from fossil material.

A triangle voting algorithm based on double feature constraints for star sensors

Science.gov (United States)

Fan, Qiaoyun; Zhong, Xuyang

2018-02-01

A novel autonomous star identification algorithm is presented in this study. In the proposed algorithm, each sensor star constructs multi-triangle with its bright neighbor stars and obtains its candidates by triangle voting process, in which the triangle is considered as the basic voting element. In order to accelerate the speed of this algorithm and reduce the required memory for star database, feature extraction is carried out to reduce the dimension of triangles and each triangle is described by its base and height. During the identification period, the voting scheme based on double feature constraints is proposed to implement triangle voting. This scheme guarantees that only the catalog star satisfying two features can vote for the sensor star, which improves the robustness towards false stars. The simulation and real star image test demonstrate that compared with the other two algorithms, the proposed algorithm is more robust towards position noise, magnitude noise and false stars.

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....

Optimized design of embedded DSP system hardware supporting complex algorithms

Science.gov (United States)

Li, Yanhua; Wang, Xiangjun; Zhou, Xinling

2003-09-01

The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.

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.

Machine learning based global particle indentification algorithms at LHCb experiment

CERN Multimedia

Derkach, Denis; Likhomanenko, Tatiana; Rogozhnikov, Aleksei; Ratnikov, Fedor

2017-01-01

One of the most important aspects of data processing at LHC experiments is the particle identification (PID) algorithm. In LHCb, several different sub-detector systems provide PID information: the Ring Imaging CHerenkov (RICH) detector, the hadronic and electromagnetic calorimeters, and the muon chambers. To improve charged particle identification, several neural networks including a deep architecture and gradient boosting have been applied to data. These new approaches provide higher identification efficiencies than existing implementations for all charged particle types. It is also necessary to achieve a flat dependency between efficiencies and spectator variables such as particle momentum, in order to reduce systematic uncertainties during later stages of data analysis. For this purpose, "flat” algorithms that guarantee the flatness property for efficiencies have also been developed. This talk presents this new approach based on machine learning and its performance.

Effective Deffect Identifications in Honeycombs

Directory of Open Access Journals (Sweden)

Jarmila Dedkova

2008-01-01

Full Text Available The image reconstruction problem based on Electrical Impedance Tomography (EIT is an ill-posed inverse problem of finding such conductivity distribution that minimizes some optimisation criterion, which can be given by a suitable primal objective function. This paper describes new algorithms for the reconstruction of the surface conductivity distribution, which are based on stochastic methods to be used for the acquirement of more accurate reconstruction results and stable solution. The proposed methods are expected to non-destructive test of materials. There are shown examples of the identification of voids or cracks in special structures called honeycombs. Instead of the experimental data we used the phantom evaluated voltage values based on the application of finite element method. The results obtained by this new approach are compared with results from the known deterministic approach to the same image reconstruction

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.

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.

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...

Efficient Identification Using a Prime-Feature-Based Technique

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar; Haq, Shaiq A.; Valente, Andrea

2011-01-01

. Fingerprint identification system, implemented on PC/104 based real-time systems, can accurately identify the operator. Traditionally, the uniqueness of a fingerprint is determined by the overall pattern of ridges and valleys as well as the local ridge anomalies e.g., a ridge bifurcation or a ridge ending......, which are called minutiae points. Designing a reliable automatic fingerprint matching algorithm for minimal platform is quite challenging. In real-time systems, efficiency of the matching algorithm is of utmost importance. To achieve this goal, a prime-feature-based indexing algorithm is proposed......Identification of authorized train drivers through biometrics is a growing area of interest in locomotive radio remote control systems. The existing technique of password authentication is not very reliable and potentially unauthorized personnel may also operate the system on behalf of the operator...

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.

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.

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 ...

IMPLANT-ASSOCIATED PATHOLOGY: AN ALGORITHM FOR IDENTIFYING PARTICLES IN HISTOPATHOLOGIC SYNOVIALIS/SLIM DIAGNOSTICS

Directory of Open Access Journals (Sweden)

V. Krenn

2014-01-01

Full Text Available In histopathologic SLIM diagnostic (synovial-like interface membrane, SLIM apart from diagnosing periprosthetic infection particle identification has an important role to play. The differences in particle pathogenesis and variability of materials in endoprosthetics explain the particle heterogeneity that hampers the diagnostic identification of particles. For this reason, a histopathological particle algorithm has been developed. With minimal methodical complexity this histopathological particle algorithm offers a guide to prosthesis material-particle identification. Light microscopic-morphological as well as enzyme-histochemical characteristics and polarization-optical proporties have set and particles are defined by size (microparticles, macroparticles and supra- macroparticles and definitely characterized in accordance with a dichotomous principle. Based on these criteria, identification and validation of the particles was carried out in 120 joint endoprosthesis pathological cases. A histopathological particle score (HPS is proposed that summarizes the most important information for the orthopedist, material scientist and histopathologist concerning particle identification in the SLIM.

Neural network based electron identification in the ZEUS calorimeter

International Nuclear Information System (INIS)

Abramowicz, H.; Caldwell, A.; Sinkus, R.

1995-01-01

We present an electron identification algorithm based on a neural network approach applied to the ZEUS uranium calorimeter. The study is motivated by the need to select deep inelastic, neutral current, electron proton interactions characterized by the presence of a scattered electron in the final state. The performance of the algorithm is compared to an electron identification method based on a classical probabilistic approach. By means of a principle component analysis the improvement in the performance is traced back to the number of variables used in the neural network approach. (orig.)

Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

Directory of Open Access Journals (Sweden)

Minghong She

2018-01-01

Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

Multiscale global identification of porous structures

Science.gov (United States)

Hatłas, Marcin; Beluch, Witold

2018-01-01

The paper is devoted to the evolutionary identification of the material constants of porous structures based on measurements conducted on a macro scale. Numerical homogenization with the RVE concept is used to determine the equivalent properties of a macroscopically homogeneous material. Finite element method software is applied to solve the boundary-value problem in both scales. Global optimization methods in form of evolutionary algorithm are employed to solve the identification task. Modal analysis is performed to collect the data necessary for the identification. A numerical example presenting the effectiveness of proposed attitude is attached.

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.

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.

Identification of systems with distributed parameters

International Nuclear Information System (INIS)

Moret, J.M.

1990-10-01

The problem of finding a model for the dynamical response of a system with distributed parameters based on measured data is addressed. First a mathematical formalism is developed in order to obtain the specific properties of such a system. Then a linear iterative identification algorithm is proposed that includes these properties, and that produces better results than usual non linear minimisation techniques. This algorithm is further improved by an original data decimation that allow to artificially increase the sampling period without losing between sample information. These algorithms are tested with real laboratory data

A Student Information Management System Based on Fingerprint Identification and Data Security Transmission

Directory of Open Access Journals (Sweden)

Pengtao Yang

2017-01-01

Full Text Available A new type of student information management system is designed to implement student information identification and management based on fingerprint identification. In order to ensure the security of data transmission, this paper proposes a data encryption method based on an improved AES algorithm. A new S-box is cleverly designed, which can significantly reduce the encryption time by improving ByteSub, ShiftRow, and MixColumn in the round transformation of the traditional AES algorithm with the process of look-up table. Experimental results show that the proposed algorithm can significantly improve the encryption time compared with the traditional AES algorithm.

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

Sensitivity Analysis and Identification of Parameters to the Van Genuchten Equation

Directory of Open Access Journals (Sweden)

Guangzhou Chen

2016-01-01

Full Text Available Van Genuchten equation is the soil water characteristic curve equation used commonly, and identifying (estimating accurately its parameters plays an important role in the study on the movement of soil water. Selecting the desorption and absorption experimental data of silt loam from a northwest region in China as an instance, Monte-Carlo method was firstly applied to analyze sensitivity of the parameters and uncertainty of model so as to get the key parameters and posteriori parameter distribution to guide subsequent parameter identification. Then, the optimization model of the parameters was set up, and a new type of intelligent algorithm-difference search algorithm was employed to identify them. In order to overcome the fault that the base difference search algorithm needed more iterations and to further enhance the optimization performance, a hybrid algorithm, which coupled the difference search algorithm with simplex method, was employed to identification of the parameters. By comparison with other optimization algorithms, the results show that the difference search algorithm has the following characteristics: good optimization performance, the simple principle, easy implement, short program code, and less control parameters required to run the algorithm. In addition, the proposed hybrid algorithm outperforms the basic difference search algorithm on the comprehensive performance of algorithm.

Hydrodynamic Coefficients Identification and Experimental Investigation for an Underwater Vehicle

Directory of Open Access Journals (Sweden)

Shaorong XIE

2014-02-01

Full Text Available Hydrodynamic coefficients are the foundation of unmanned underwater vehicles modeling and controller design. In order to reduce identification complexity and acquire necessary hydrodynamic coefficients for controllers design, the motion of the unmanned underwater vehicle was separated into vertical motion and horizontal motion models. Hydrodynamic coefficients were regarded as mapping parameters from input forces and moments to output velocities and acceleration of the unmanned underwater vehicle. The motion models of the unmanned underwater vehicle were nonlinear and Genetic Algorithm was adopted to identify those hydrodynamic coefficients. To verify the identification quality, velocities and acceleration of the unmanned underwater vehicle was measured using inertial sensor under the same conditions as Genetic Algorithm identification. Curves similarity between measured velocities and acceleration and those identified by Genetic Algorithm were used as optimizing standard. It is found that the curves similarity were high and identified hydrodynamic coefficients of the unmanned underwater vehicle satisfied the measured motion states well.

Recursive automatic classification algorithms

Energy Technology Data Exchange (ETDEWEB)

Bauman, E V; Dorofeyuk, A A

1982-03-01

A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

The Problem of Informational Object Identification in Case of the Considerable Quantity of Identifying Features

Directory of Open Access Journals (Sweden)

S. D. Kulik

2010-03-01

Full Text Available The modification of the algorithm of identification of the informational object, used for identification of the hand-written texts performer in an automated workplace of the forensic expert, is presented. As modification, it is offered to use a method of association rules discovery for definition of statistically dependent sets of feature of hand-written capital letters of the Russian language. The algorithm is approved on set of 691 samples of hand-written documents for which about 2000 identifying feature are defined. The modification of the identification algorithm allows to lower level of errors and to raise quality of accepted decisions for information security.

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

Preliminary results of the ice_sheet_CCI round robin activity on the estimation of surface elevation changes

DEFF Research Database (Denmark)

Ticconi, F.; Fredenslund Levinsen, Joanna; Khvorostovsky, K.

2013-01-01

This work presents the first results of a research activity aiming to compare estimates of Surface Elevation Changes (SEC) over the Jakobshavn Isbræ basin (Greenland) using different repeat altimetry techniques and different sensors (laser vs. radar altimetry). The goal of this comparison...... is the identification of the best performing algorithm, in terms of accuracy, coverage and processing effort, for the generation of surface elevation change maps. The methods investigated here are the cross-over and repeat-track. The results of the inter-comparison are here reported and, from a first analysis...

Methodology for Identification of the Coolant Thermalhydraulic Regimes in the Core of Nuclear Reactors

International Nuclear Information System (INIS)

Sharaevsky, L.G.; Sharaevskaya, E.I.; Domashev, E.D.; Arkhypov, A.P.; Kolochko, V.N.

2002-01-01

real WWER core assemblies were analysed as well. On the basis of model of Bayes classifier for bubble structure of two-phase flow in fuel assemblies of WWER-440 (intends usage of 28 dimensional accidental realizations of ASD of neutron noise) the reliable identification of the pointed regimes of fuel assemblies in WWERs up to 98% was obtained. On the basis of geometrical mathematical model of identification at essentially more limited volume of teaching sampling the recognition of ASD realizations of the neutron noise of the same both dimensions and quantity of the reliability of correct identification of these parameters was up to 92%. The recognition of the pointed thermalhydraulic parameters was carried out on the basis of experimental research of ASD of acoustic noise parameters of the experimental fuel assembly with electrically heated imitators using the two recognition models - statistical and geometrical. It confirmed high efficiency of the algorithms developed. The average reliability of identification of the first vapor bubbles activation regime at the heat transfer surface was not low then 90%. (authors)

Computational methods for protein identification from mass spectrometry data.

Directory of Open Access Journals (Sweden)

Leo McHugh

2008-02-01

Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.

Electron and photon identification in the D0 experiment

Energy Technology Data Exchange (ETDEWEB)

Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Avila, C.; Badaud, F.; Bagby, L.; Baldin, B.; Bandurin, D. V.; Banerjee, S.; Barberis, E.; Baringer, P.; Bartlett, J. F.; Bassler, U.; Bazterra, V.; Bean, A.; Begalli, M.; Bellantoni, L.; Beri, S. B.; Bernardi, G.; Bernhard, R.; Bertram, I.; Besançon, M.; Beuselinck, R.; Bhat, P. C.; Bhatia, S.; Bhatnagar, V.; Blazey, G.; Blessing, S.; Bloom, K.; Boehnlein, A.; Boline, D.; Boos, E. E.; Borissov, G.; Borysova, M.; Brandt, A.; Brandt, O.; Brock, R.; Bross, A.; Brown, D.; Bu, X. B.; Buehler, M.; Buescher, V.; Bunichev, V.; Burdin, S.; Buszello, C. P.; Camacho-Pérez, E.; Casey, B. C. K.; Castilla-Valdez, H.; Caughron, S.; Chakrabarti, S.; Chan, K. M.; Chandra, A.; Chapon, E.; Chen, G.; Cho, S. W.; Choi, S.; Choudhary, B.; Cihangir, S.; Claes, D.; Clutter, J.; Cooke, M.; Cooper, W. E.; Corcoran, M.; Couderc, F.; Cousinou, M. -C.; Cutts, D.; Das, A.; Davies, G.; de Jong, S. J.; De La Cruz-Burelo, E.; Déliot, F.; Demina, R.; Denisov, D.; Denisov, S. P.; Desai, S.; Deterre, C.; DeVaughan, K.; Diehl, H. T.; Diesburg, M.; Ding, P. F.; Dominguez, A.; Dubey, A.; Dudko, L. V.; Duperrina, A.; Dutt, S.; Eads, M.; Edmunds, D.; Ellison, J.; Elvira, V. D.; Enari, Y.; Evans, H.; Evdokimov, V. N.; Feng, L.; Ferbel, T.; Fiedler, F.; Filthaut, F.; Fisher, W.; Fisk, H. E.; Fortner, M.; Fox, H.; Fuess, S.; Garbincius, P. H.; Garcia-Bellido, A.; García-González, J. A.; Gavrilov, V.; Geng, W.; Gerber, C. E.; Gershtein, Y.; Ginther, G.; Golovanov, G.; Grannis, P. D.; Greder, S.; Greenlee, H.; Grenier, G.; Gris, Ph.; Grivaz, J. -F.; Grohsjean, A.; Grünendahl, S.; Grünewald, M. W.; Guillemin, T.; Gutierrez, G.; Gutierrez, P.; Haley, J.; Han, L.; Harder, K.; Harel, A.; Hauptman, J. M.; Hays, J.; Head, T.; Hebbeker, T.; Hedin, D.; Hegab, H.; Heinson, A. P.; Heintz, U.; Hensel, C.; Heredia-De La Cruz, I.; Herner, K.; Hesketh, G.; Hildreth, M. D.; Hirosky, R.; Hoang, T.; Hobbs, J. D.; Hoeneisen, B.; Hogan, J.; Hohlfeld, M.; Holzbauer, J. L.; Howley, I.; Hubacek, Z.; Hynek, V.; Iashvili, I.; Ilchenko, Y.; Illingworth, R.; Ito, A. S.; Jabeen, S.; Jaffré, M.; Jayasinghe, A.; Jeong, M. S.; Jesik, R.; Jiang, P.; Johns, K.; Johnson, E.; Johnson, M.; Jonckheere, A.; Jonsson, P.; Joshi, J.; Jung, A. W.; Juste, A.; Kajfasz, E.; Karmanov, D.; Katsanos, I.; Kehoe, R.; Kermiche, S.; Khalatyan, N.; Khanov, A.; Kharchilava, A.; Kharzheev, Y. N.; Kiselevich, I.; Kohli, J. M.; Kozelov, A. V.; Kraus, J.; Kumar, A.; Kupco, A.; Kurča, T.; Kuzmin, V. A.; Lammers, S.; Lebrun, P.; Lee, H. S.; Lee, S. W.; Lee, W. M.; Lei, X.; Lellouch, J.; Li, D.; Li, H.; Li, L.; Li, Q. Z.; Lim, J. K.; Lincoln, D.; Linnemann, J.; Lipaev, V. V.; Lipton, R.; Liu, H.; Liu, Y.; Lobodenko, A.; Lokajicek, M.; Lopes de Sa, R.; Luna-Garcia, R.; Lyon, A. L.; Maciel, A. K. A.; Madar, R.; Magaña-Villalba, R.; Malik, S.; Malyshev, V. L.; Mansour, J.; Martínez-Ortega, J.; McCarthy, R.; McGivern, C. L.; Meijer, M. M.; Melnitchouk, A.; Menezes, D.; Mercadante, P. G.; Merkin, M.; Meyer, A.; Meyer, J.; Miconi, F.; Mondal, N. K.; Mulhearn, M.; Nagy, E.; Narain, M.; Nayyar, R.; Neal, H. A.; Negret, J. P.; Neustroev, P.; Nguyen, H. T.; Nunnemann, T.; Orduna, J.; Osman, N.; Osta, J.; Pal, A.; Parashar, N.; Parihar, V.; Park, S. K.; Partridge, R.; Parua, N.; Patwa, A.; Penning, B.; Perfilov, M.; Peters, Y.; Petridis, K.; Petrillo, G.; Pétroff, P.; Pleier, M. -A.; Podstavkov, V. M.; Popov, A. V.; Prewitt, M.; Price, D.; Prokopenko, N.; Qian, J.; Quadt, A.; Quinn, B.; Raja, R.; Ratoff, P. N.; Razumov, I.; Ripp-Baudot, I.; Rizatdinova, F.; Rominsky, M.; Ross, A.; Royon, C.; Rubinov, P.; Ruchti, R.; Sajot, G.; Sánchez-Hernández, A.; Sanders, M. P.; Santos, A. S.; Savage, G.; Sawyer, L.; Scanlon, T.; Schamberger, R. D.; Scheglov, Y.; Schellman, H.; Schwanenberger, C.; Schwienhorst, R.; Sekaric, J.; Severini, H.; Shabalina, E.; Shary, V.; Shaw, S.; Shchukin, A. A.; Simak, V.; Skubic, P.; Slattery, P.; Smirnov, D.; Snow, G. R.; Snow, J.; Snyder, S.; Söldner-Rembold, S.; Sonnenschein, L.; Soustruznik, K.; Stark, J.; Stoyanova, D. A.; Strauss, M.; Suter, L.; Svoisky, P.; Titov, M.; Tokmenin, V. V.; Tsai, Y. -T.; Tsybychev, D.; Tuchming, B.; Tully, C.; Uvarov, L.; Uvarov, S.; Uzunyan, S.; Van Kooten, R.; van Leeuwen, W. M.; Varelas, N.; Varnes, E. W.; Vasilyev, I. A.; Verkheev, A. Y.; Vertogradov, L. S.; Verzocchi, M.; Vesterinen, M.; Vilanova, D.; Vokac, P.; Wahl, H. D.; Wang, M. H. L. S.; Warchol, J.; Watts, G.; Wayne, M.; Weichert, J.; Welty-Rieger, L.; Williams, M. R. J.; Wilson, G. W.; Wobisch, M.; Wood, D. R.; Wyatt, T. R.; Xie, Y.; Yamada, R.; Yang, S.; Yasuda, T.; Yatsunenko, Y. A.; Ye, W.; Ye, Z.; Yin, H.; Yip, K.; Youn, S. W.; Yu, J. M.; Zennamo, J.; Zhao, T. G.; Zhou, B.; Zhu, J.; Zielinski, M.; Zieminska, D.; Zivkovic, L.

2014-06-01

The electron and photon reconstruction and identification algorithms used by the D0 Collaboration at the Fermilab Tevatron collider are described. The determination of the electron energy scale and resolution is presented. Studies of the performance of the electron and photon reconstruction and identification are summarized.

Health monitoring system for transmission shafts based on adaptive parameter identification

Science.gov (United States)

Souflas, I.; Pezouvanis, A.; Ebrahimi, K. M.

2018-05-01

A health monitoring system for a transmission shaft is proposed. The solution is based on the real-time identification of the physical characteristics of the transmission shaft i.e. stiffness and damping coefficients, by using a physical oriented model and linear recursive identification. The efficacy of the suggested condition monitoring system is demonstrated on a prototype transient engine testing facility equipped with a transmission shaft capable of varying its physical properties. Simulation studies reveal that coupling shaft faults can be detected and isolated using the proposed condition monitoring system. Besides, the performance of various recursive identification algorithms is addressed. The results of this work recommend that the health status of engine dynamometer shafts can be monitored using a simple lumped-parameter shaft model and a linear recursive identification algorithm which makes the concept practically viable.

Implementation of Human Trafficking Education and Treatment Algorithm in the Emergency Department.

Science.gov (United States)

Egyud, Amber; Stephens, Kimberly; Swanson-Bierman, Brenda; DiCuccio, Marge; Whiteman, Kimberly

2017-11-01

Health care professionals have not been successful in recognizing or rescuing victims of human trafficking. The purpose of this project was to implement a screening system and treatment algorithm in the emergency department to improve the identification and rescue of victims of human trafficking. The lack of recognition by health care professionals is related to inadequate education and training tools and confusion with other forms of violence such as trauma and sexual assault. A multidisciplinary team was formed to assess the evidence related to human trafficking and make recommendations for practice. After receiving education, staff completed a survey about knowledge gained from the training. An algorithm for identification and treatment of sex trafficking victims was implemented and included a 2-pronged identification approach: (1) medical red flags created by a risk-assessment tool embedded in the electronic health record and (2) a silent notification process. Outcome measures were the number of victims who were identified either by the medical red flags or by silent notification and were offered and accepted intervention. Survey results indicated that 75% of participants reported that the education improved their competence level. The results demonstrated that an education and treatment algorithm may be an effective strategy to improve recognition. One patient was identified as an actual victim of human trafficking; the remaining patients reported other forms of abuse. Education and a treatment algorithm were effective strategies to improve recognition and rescue of human trafficking victims and increase identification of other forms of abuse. Copyright © 2017 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.

CONTROLLED CONDENSATION IN K-NN AND ITS APPLICATION FOR REAL TIME COLOR IDENTIFICATION

Directory of Open Access Journals (Sweden)

Carmen Villar Patiño

2017-04-01

Full Text Available k-NN algorithms are frequently used in statistical classification. They are accurate and distribution free. Despite these advantages, k-NN algorithms imply a high computational cost. To find efficient ways to implement them is an important challenge in pattern recognition. In this article, an improved version of the k-NN Controlled Condensation algorithm is introduced. Its potential for instantaneous color identification in real time is also analyzed. This algorithm is based on the representation of data in terms of a reduced set of informative prototypes. It includes two parameters to control the balance between speed and precision. This gives us the opportunity to achieve a convenient percentage of condensation without incurring in an important loss of accuracy. We test our proposal in an instantaneous color identification exercise in video images. We achieve the real time identification by using k-NN Controlled Condensation executed through multi-threading programming methods. The results are encouraging.

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.)

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.

Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network

International Nuclear Information System (INIS)

Bobin, C.; Bichler, O.; Lourenço, V.; Thiam, C.; Thévenin, M.

2016-01-01

Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes’ rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ( 241 Am, 133 Ba, 207 Bi, 60 Co, 137 Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. - Highlights: • A fast radionuclide identification algorithm applicable in spectroscopic portal monitors is presented. • The proposed algorithm combines a Bayesian sequential approach and a spiking neural network. • The algorithm was validated using the mixture of γ-emitter spectra provided by a well-type NaI(Tl) detector. • The radionuclide identification process is implemented using the whole γ-spectrum without energy calibration.

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

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

Closed and Open Loop Subspace System Identification of the Kalman Filter

Directory of Open Access Journals (Sweden)

David Di Ruscio

2009-04-01

Full Text Available Some methods for consistent closed loop subspace system identification presented in the literature are analyzed and compared to a recently published subspace algorithm for both open as well as for closed loop data, the DSR_e algorithm. Some new variants of this algorithm are presented and discussed. Simulation experiments are included in order to illustrate if the algorithms are variance efficient or not.

Automatic segmentation of thermal images of diabetic-at-risk feet using the snakes algorithm

Science.gov (United States)

Etehadtavakol, Mahnaz; Ng, E. Y. K.; Kaabouch, Naima

2017-11-01

Diabetes is a disease with multi-systemic problems. It is a leading cause of death, medical costs, and loss of productivity. Foot ulcers are one generally known problem of uncontrolled diabetes that can lead to amputation signs of foot ulcers are not always obvious. Sometimes, symptoms won't even show up until ulcer is infected. Hence, identification of pre-ulceration of the plantar surface of the foot in diabetics is beneficial. Thermography has the potential to identify regions of the plantar with no evidence of ulcer but yet risk. Thermography is a technique that is safe, easy, non-invasive, with no contact, and repeatable. In this study, 59 thermographic images of the plantar foot of patients with diabetic neuropathy are implemented using the snakes algorithm to separate two feet from background automatically and separating the right foot from the left on each image. The snakes algorithm both separates the right and left foot into segmented different clusters according to their temperatures. The hottest regions will have the highest risk of ulceration for each foot. This algorithm also worked perfectly for all the current images.

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

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

Science.gov (United States)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time

Contact-impact algorithms on parallel computers

International Nuclear Information System (INIS)

Zhong Zhihua; Nilsson, Larsgunnar

1994-01-01

Contact-impact algorithms on parallel computers are discussed within the context of explicit finite element analysis. The algorithms concerned include a contact searching algorithm and an algorithm for contact force calculations. The contact searching algorithm is based on the territory concept of the general HITA algorithm. However, no distinction is made between different contact bodies, or between different contact surfaces. All contact segments from contact boundaries are taken as a single set. Hierarchy territories and contact territories are expanded. A three-dimensional bucket sort algorithm is used to sort contact nodes. The defence node algorithm is used in the calculation of contact forces. Both the contact searching algorithm and the defence node algorithm are implemented on the connection machine CM-200. The performance of the algorithms is examined under different circumstances, and numerical results are presented. ((orig.))

Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient

Directory of Open Access Journals (Sweden)

ChunPing Ren

2017-01-01

Full Text Available We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering. Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm. The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME-NCG algorithm is available for identifying the random dynamic force due to smaller root mean-square-error (RMSE, lower restoration time, and fewer iterative steps. Example of engineering application shows that L-curve method is introduced which is better than Generalized Cross Validation (GCV method and is applied to select regularization parameter; thus the proposed algorithm can be helpful to alleviate the ill-conditioned problem in identification of dynamic force and to acquire an optimal solution of inverse problem in practical engineering.

Fuzzy Algorithm for the Detection of Incidents in the Transport System

Science.gov (United States)

Nikolaev, Andrey B.; Sapego, Yuliya S.; Jakubovich, Anatolij N.; Berner, Leonid I.; Stroganov, Victor Yu.

2016-01-01

In the paper it's proposed an algorithm for the management of traffic incidents, aimed at minimizing the impact of incidents on the road traffic in general. The proposed algorithm is based on the theory of fuzzy sets and provides identification of accidents, as well as the adoption of appropriate measures to address them as soon as possible. A…

Advanced LWIR hyperspectral sensor for on-the-move proximal detection of liquid/solid contaminants on surfaces

Science.gov (United States)

Giblin, Jay P.; Dixon, John; Dupuis, Julia R.; Cosofret, Bogdan R.; Marinelli, William J.

2017-05-01

Sensor technologies capable of detecting low vapor pressure liquid surface contaminants, as well as solids, in a noncontact fashion while on-the-move continues to be an important need for the U.S. Army. In this paper, we discuss the development of a long-wave infrared (LWIR, 8-10.5 μm) spatial heterodyne spectrometer coupled with an LWIR illuminator and an automated detection algorithm for detection of surface contaminants from a moving vehicle. The system is designed to detect surface contaminants by repetitively collecting LWIR reflectance spectra of the ground. Detection and identification of surface contaminants is based on spectral correlation of the measured LWIR ground reflectance spectra with high fidelity library spectra and the system's cumulative binary detection response from the sampled ground. We present the concepts of the detection algorithm through a discussion of the system signal model. In addition, we present reflectance spectra of surfaces contaminated with a liquid CWA simulant, triethyl phosphate (TEP), and a solid simulant, acetaminophen acquired while the sensor was stationary and on-the-move. Surfaces included CARC painted steel, asphalt, concrete, and sand. The data collected was analyzed to determine the probability of detecting 800 μm diameter contaminant particles at a 0.5 g/m2 areal density with the SHSCAD traversing a surface.

Fluid-structure-coupling algorithm

International Nuclear Information System (INIS)

McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.

1980-01-01

A fluid-structure-interaction algorithm has been developed and incorporated into the two dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure, and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed here have been extended to three dimensions and implemented in the computer code PELE-3D

Fluid structure coupling algorithm

International Nuclear Information System (INIS)

McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.

1980-01-01

A fluid-structure-interaction algorithm has been developed and incorporated into the two-dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed have been extended to three dimensions and implemented in the computer code PELE-3D

Implementation of Minutiae Based Fingerprint Identification System Using Crossing Number Concept

Directory of Open Access Journals (Sweden)

Atul S. CHAUDHARI

2014-01-01

Full Text Available Biometric system is essentially a pattern recognition system which recognizes a person by determining the authenticity of a specific physiological (e.g., fingerprints, face, retina, iris or behavioral (e.g., gait, signature characteristic possessed by that person. Among all the presently employed biometric techniques, fingerprint identification systems have received the most attention due to the long history of fingerprints and its extensive use in forensics. Fingerprint is reliable biometric characteristic as it is unique and persistence. Fingerprint is the pattern of ridges and valleys on the surface of fingertip. However, recognizing fingerprints in poor quality images is still a very complex job, so the fingerprint image must be preprocessed before matching. It is very difficult to extract fingerprint features directly from gray scale fingerprint image. In this paper we have proposed the system which uses minutiae based matching algorithm for fingerprint identification. There are three main phases in proposed algorithm. First phase enhance the input fingerprint image by preprocessing it. The enhanced fingerprint image is converted into thinned binary image and then minutiae are extracted by using Crossing Number Concept in second phase. Third stage compares input fingerprint image (after preprocessing and minutiae extraction with fingerprint images enrolled in database and makes decision whether the input fingerprint is matched with the fingerprint stored in database or not.

Tau Identification at CMS in Run II

CERN Document Server

Ojalvo, Isabel

2016-01-01

During LHC Long Shutdown 1 necessary upgrades to the CMS detector were made. CMS also took the opportunity to improve further particle reconstruction. A number of improvements were made to the Hadronic Tau reconstruction and Identification algorithms. In particular, electromag- netic strip reconstruction of the Hadron plus Strips (HPS) algorithm was improved to better model signal of pi0 from tau decays. This modification improves energy response and removes the tau footprint from isolation area. In addition to this, improvement to discriminators combining iso- lation and tau life time variables, and anti-electron in MultiVariate Analysis technique was also developed. The results of these improvements are presented and validation of Tau Identification using a variety of techniques is shown.

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.

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.

A novel feature ranking algorithm for biometric recognition with PPG signals.

Science.gov (United States)

Reşit Kavsaoğlu, A; Polat, Kemal; Recep Bozkurt, M

2014-06-01

This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Automated de-identification of free-text medical records

Directory of Open Access Journals (Sweden)

Long William J

2008-07-01

Full Text Available Abstract Background Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA requires that protected health information (PHI be removed from medical records before they can be disseminated. Manual de-identification of large medical record databases is prohibitively expensive, time-consuming and prone to error, necessitating automatic methods for large-scale, automated de-identification. Methods We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. The software uses lexical look-up tables, regular expressions, and simple heuristics to locate both HIPAA PHI, and an extended PHI set that includes doctors' names and years of dates. To develop the de-identification approach, we assembled a gold standard corpus of re-identified nursing notes with real PHI replaced by realistic surrogate information. This corpus consists of 2,434 nursing notes containing 334,000 words and a total of 1,779 instances of PHI taken from 163 randomly selected patient records. This gold standard corpus was used to refine the algorithm and measure its sensitivity. To test the algorithm on data not used in its development, we constructed a second test corpus of 1,836 nursing notes containing 296,400 words. The algorithm's false negative rate was evaluated using this test corpus. Results Performance evaluation of the de-identification software on the development corpus yielded an overall recall of 0.967, precision value of 0.749, and fallout value of approximately 0.002. On the test corpus, a total of 90 instances of false negatives were found, or 27 per 100,000 word count, with an estimated recall of 0.943. Only one full date and one age over 89 were missed. No patient names were missed in either

An on-line modified least-mean-square algorithm for training neurofuzzy controllers.

Science.gov (United States)

Tan, Woei Wan

2007-04-01

The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates "learning interference" by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.

An effective one-dimensional anisotropic fingerprint enhancement algorithm

Science.gov (United States)

Ye, Zhendong; Xie, Mei

2012-01-01

Fingerprint identification is one of the most important biometric technologies. The performance of the minutiae extraction and the speed of the fingerprint verification system rely heavily on the quality of the input fingerprint images, so the enhancement of the low fingerprint is a critical and difficult step in a fingerprint verification system. In this paper we proposed an effective algorithm for fingerprint enhancement. Firstly we use normalization algorithm to reduce the variations in gray level values along ridges and valleys. Then we utilize the structure tensor approach to estimate each pixel of the fingerprint orientations. At last we propose a novel algorithm which combines the advantages of onedimensional Gabor filtering method and anisotropic method to enhance the fingerprint in recoverable region. The proposed algorithm has been evaluated on the database of Fingerprint Verification Competition 2004, and the results show that our algorithm performs within less time.

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

Science.gov (United States)

Schultheiss, Sebastian J; Busch, Wolfgang; Lohmann, Jan U; Kohlbacher, Oliver; Rätsch, Gunnar

2009-08-15

Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor (TF) binding sites in promoter regions of potential TF target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling, or heuristics to extend seed oligos. Such algorithms succeed in identifying single, relatively well-conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites, as those often found in cis-regulatory modules. We propose a new algorithm that combines the benefits of existing motif finding with the ones of support vector machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana, we were able to show that the newly developed strategy significantly improves the recognition of TF targets. The python source code (open source-licensed under GPL), the data for the experiments and a Galaxy-based web service are available at http://www.fml.mpg.de/raetsch/suppl/kirmes/.

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Science.gov (United States)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Escalante Del Valle, A.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Seva, T.; Starling, E.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; David, P.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; Damiao, D. De Jesus; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Thomas-wilsker, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; Zhao, J.; Ban, Y.; Chen, G.; Li, J.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Wang, Y.; Avila, C.; Cabrera, A.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M., Jr.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Ellithi Kamel, A.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Blanco, J. Martin; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Teroerde, M.; Zhukov, V.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Anuar, A. A. Bin; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Defranchis, M. M.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. 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I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. 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P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Hiltbrand, J.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2018-05-01

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated bar t events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

Science.gov (United States)

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-12-04

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

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.

Influence of Head Motion on the Accuracy of 3D Reconstruction with Cone-Beam CT: Landmark Identification Errors in Maxillofacial Surface Model.

Directory of Open Access Journals (Sweden)

Kyung-Min Lee

Full Text Available The purpose of this study was to investigate the influence of head motion on the accuracy of three-dimensional (3D reconstruction with cone-beam computed tomography (CBCT scan.Fifteen dry skulls were incorporated into a motion controller which simulated four types of head motion during CBCT scan: 2 horizontal rotations (to the right/to the left and 2 vertical rotations (upward/downward. Each movement was triggered to occur at the start of the scan for 1 second by remote control. Four maxillofacial surface models with head motion and one control surface model without motion were obtained for each skull. Nine landmarks were identified on the five maxillofacial surface models for each skull, and landmark identification errors were compared between the control model and each of the models with head motion.Rendered surface models with head motion were similar to the control model in appearance; however, the landmark identification errors showed larger values in models with head motion than in the control. In particular, the Porion in the horizontal rotation models presented statistically significant differences (P < .05. Statistically significant difference in the errors between the right and left side landmark was present in the left side rotation which was opposite direction to the scanner rotation (P < .05.Patient movement during CBCT scan might cause landmark identification errors on the 3D surface model in relation to the direction of the scanner rotation. Clinicians should take this into consideration to prevent patient movement during CBCT scan, particularly horizontal movement.

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.

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

Science.gov (United States)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Sparse Matrix for ECG Identification with Two-Lead Features

Directory of Open Access Journals (Sweden)

Kuo-Kun Tseng

2015-01-01

Full Text Available Electrocardiograph (ECG human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

Energy Technology Data Exchange (ETDEWEB)

Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu

2013-08-01

In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.

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

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.

arXiv Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

CERN Document Server

Sirunyan, Albert M; CMS Collaboration; Adam, Wolfgang; Ambrogi, Federico; Asilar, Ece; Bergauer, Thomas; Brandstetter, Johannes; Brondolin, Erica; Dragicevic, Marko; Erö, Janos; Escalante Del Valle, Alberto; Flechl, Martin; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Grossmann, Johannes; Hrubec, Josef; Jeitler, Manfred; König, Axel; Krammer, Natascha; Krätschmer, Ilse; Liko, Dietrich; Madlener, Thomas; Mikulec, Ivan; Pree, Elias; Rad, Navid; Rohringer, Herbert; Schieck, Jochen; Schöfbeck, Robert; Spanring, Markus; Spitzbart, Daniel; Waltenberger, Wolfgang; Wittmann, Johannes; Wulz, Claudia-Elisabeth; Zarucki, Mateusz; Chekhovsky, Vladimir; Mossolov, Vladimir; Suarez Gonzalez, Juan; De Wolf, Eddi A; Di Croce, Davide; Janssen, Xavier; Lauwers, Jasper; Van De Klundert, Merijn; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Abu Zeid, Shimaa; Blekman, Freya; D'Hondt, Jorgen; De Bruyn, Isabelle; De Clercq, Jarne; Deroover, Kevin; Flouris, Giannis; Lontkovskyi, Denys; Lowette, Steven; Marchesini, Ivan; Moortgat, Seth; Moreels, Lieselotte; Python, Quentin; Skovpen, Kirill; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Parijs, Isis; Beghin, Diego; Bilin, Bugra; Brun, Hugues; Clerbaux, Barbara; De Lentdecker, Gilles; Delannoy, Hugo; Dorney, Brian; Fasanella, Giuseppe; Favart, Laurent; Goldouzian, Reza; Grebenyuk, Anastasia; Lenzi, Thomas; Luetic, Jelena; Maerschalk, Thierry; Marinov, Andrey; Seva, Tomislav; Starling, Elizabeth; Vander Velde, Catherine; Vanlaer, Pascal; Vannerom, David; Yonamine, Ryo; Zenoni, Florian; Zhang, Fengwangdong; Cimmino, Anna; Cornelis, Tom; Dobur, Didar; Fagot, Alexis; Gul, Muhammad; Khvastunov, Illia; Poyraz, Deniz; Roskas, Christos; Salva Diblen, Sinem; Tytgat, Michael; Verbeke, Willem; Zaganidis, Nicolas; Bakhshiansohi, Hamed; Bondu, Olivier; Brochet, Sébastien; Bruno, Giacomo; Caputo, Claudio; Caudron, Adrien; David, Pieter; De Visscher, Simon; Delaere, Christophe; Delcourt, Martin; Francois, Brieuc; Giammanco, Andrea; Komm, Matthias; Krintiras, Georgios; Lemaitre, Vincent; Magitteri, Alessio; Mertens, Alexandre; Musich, Marco; Piotrzkowski, Krzysztof; Quertenmont, Loic; Saggio, Alessia; Vidal Marono, Miguel; Wertz, Sébastien; Zobec, Joze; Aldá Júnior, Walter Luiz; Alves, Fábio Lúcio; Alves, Gilvan; Brito, Lucas; Correa Martins Junior, Marcos; Hensel, Carsten; Moraes, Arthur; Pol, Maria Elena; Rebello Teles, Patricia; Belchior Batista Das Chagas, Ewerton; Carvalho, Wagner; Chinellato, Jose; Coelho, Eduardo; Melo Da Costa, Eliza; Da Silveira, Gustavo Gil; De Jesus Damiao, Dilson; Fonseca De Souza, Sandro; Huertas Guativa, Lina Milena; Malbouisson, Helena; Melo De Almeida, Miqueias; Mora Herrera, Clemencia; Mundim, Luiz; Nogima, Helio; Sanchez Rosas, Luis Junior; Santoro, Alberto; Sznajder, Andre; Thiel, Mauricio; Tonelli Manganote, Edmilson José; Torres Da Silva De Araujo, Felipe; Vilela Pereira, Antonio; Ahuja, Sudha; Bernardes, Cesar Augusto; Tomei, Thiago; De Moraes Gregores, Eduardo; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Romero Abad, David; Ruiz Vargas, José Cupertino; Aleksandrov, Aleksandar; Hadjiiska, Roumyana; Iaydjiev, Plamen; Misheva, Milena; Rodozov, Mircho; Shopova, Mariana; Sultanov, Georgi; Dimitrov, Anton; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Fang, Wenxing; Gao, Xuyang; Yuan, Li; Ahmad, Muhammad; Chen, Guo-Ming; Chen, He-Sheng; Chen, Mingshui; Chen, Ye; Jiang, Chun-Hua; Leggat, Duncan; Liao, Hongbo; Liu, Zhenan; Romeo, Francesco; Shaheen, Sarmad Masood; Spiezia, Aniello; Tao, Junquan; Thomas-wilsker, Joshuha; Wang, Chunjie; Wang, Zheng; Yazgan, Efe; Zhang, Huaqiao; Zhang, Sijing; Zhao, Jingzhou; Ban, Yong; Chen, Geng; Li, Jing; Li, Qiang; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Wang, Dayong; Xu, Zijun; Wang, Yi; Avila, Carlos; Cabrera, Andrés; Carrillo Montoya, Camilo Andres; Chaparro Sierra, Luisa Fernanda; Florez, Carlos; González Hernández, Carlos Felipe; Ruiz Alvarez, José David; Segura Delgado, Manuel Alejandro; Courbon, Benoit; Godinovic, Nikola; Lelas, Damir; Puljak, Ivica; Ribeiro Cipriano, Pedro M; Sculac, Toni; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Ferencek, Dinko; Kadija, Kreso; Mesic, Benjamin; Starodumov, Andrei; Susa, Tatjana; Ather, Mohsan Waseem; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Rykaczewski, Hans; Finger, Miroslav; Finger Jr, Michael; Carrera Jarrin, Edgar; El-khateeb, Esraa; Elgammal, Sherif; Ellithi Kamel, Ali; Dewanjee, Ram Krishna; Kadastik, Mario; Perrini, Lucia; Raidal, Martti; Tiko, Andres; Veelken, Christian; Eerola, Paula; Kirschenmann, Henning; Pekkanen, Juska; Voutilainen, Mikko; Havukainen, Joona; Heikkilä, Jaana Kristiina; Jarvinen, Terhi; Karimäki, Veikko; Kinnunen, Ritva; Lampén, Tapio; Lassila-Perini, Kati; Laurila, Santeri; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Siikonen, Hannu; Tuominen, Eija; Tuominiemi, Jorma; Tuuva, Tuure; Besancon, Marc; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Ghosh, Saranya; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Kucher, Inna; Leloup, Clément; Locci, Elizabeth; Machet, Martina; Malcles, Julie; Negro, Giulia; Rander, John; Rosowsky, André; Sahin, Mehmet Özgür; Titov, Maksym; Abdulsalam, Abdulla; Amendola, Chiara; Antropov, Iurii; Baffioni, Stephanie; Beaudette, Florian; Busson, Philippe; Cadamuro, Luca; Charlot, Claude; Granier de Cassagnac, Raphael; Jo, Mihee; Lisniak, Stanislav; Lobanov, Artur; Martin Blanco, Javier; Nguyen, Matthew; Ochando, Christophe; Ortona, Giacomo; Paganini, Pascal; Pigard, Philipp; Salerno, Roberto; Sauvan, Jean-Baptiste; Sirois, Yves; Stahl Leiton, Andre Govinda; Strebler, Thomas; Yilmaz, Yetkin; Zabi, Alexandre; Zghiche, Amina; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Brom, Jean-Marie; Buttignol, Michael; Chabert, Eric Christian; Chanon, Nicolas; Collard, Caroline; Conte, Eric; Coubez, Xavier; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Jansová, Markéta; Le Bihan, Anne-Catherine; Tonon, Nicolas; Van Hove, Pierre; Gadrat, Sébastien; Beauceron, Stephanie; Bernet, Colin; Boudoul, Gaelle; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Finco, Linda; Gascon, Susan; Gouzevitch, Maxime; Grenier, Gérald; Ille, Bernard; Lagarde, Francois; Laktineh, Imad Baptiste; Lethuillier, Morgan; Mirabito, Laurent; Pequegnot, Anne-Laure; Perries, Stephane; Popov, Andrey; Sordini, Viola; Vander Donckt, Muriel; Viret, Sébastien; Khvedelidze, Arsen; Tsamalaidze, Zviad; Autermann, Christian; Feld, Lutz; Kiesel, Maximilian Knut; Klein, Katja; Lipinski, Martin; Preuten, Marius; Schomakers, Christian; Schulz, Johannes; Teroerde, Marius; Zhukov, Valery; Albert, Andreas; Dietz-Laursonn, Erik; Duchardt, Deborah; Endres, Matthias; Erdmann, Martin; Erdweg, Sören; Esch, Thomas; Fischer, Robert; Güth, Andreas; Hamer, Matthias; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Knutzen, Simon; Merschmeyer, Markus; Meyer, Arnd; Millet, Philipp; Mukherjee, Swagata; Pook, Tobias; Radziej, Markus; Reithler, Hans; Rieger, Marcel; Scheuch, Florian; Teyssier, Daniel; Thüer, Sebastian; Flügge, Günter; Kargoll, Bastian; Kress, Thomas; Künsken, Andreas; Müller, Thomas; Nehrkorn, Alexander; Nowack, Andreas; Pistone, Claudia; Pooth, Oliver; Stahl, Achim; Aldaya Martin, Maria; Arndt, Till; Asawatangtrakuldee, Chayanit; Beernaert, Kelly; Behnke, Olaf; Behrens, Ulf; Bermúdez Martínez, Armando; Bin Anuar, Afiq Aizuddin; Borras, Kerstin; Botta, Valeria; Campbell, Alan; Connor, Patrick; Contreras-Campana, Christian; Costanza, Francesco; Defranchis, Matteo Maria; Diez Pardos, Carmen; Eckerlin, Guenter; Eckstein, Doris; Eichhorn, Thomas; Eren, Engin; Gallo, Elisabetta; Garay Garcia, Jasone; Geiser, Achim; Grados Luyando, Juan Manuel; Grohsjean, Alexander; Gunnellini, Paolo; Guthoff, Moritz; Harb, Ali; Hauk, Johannes; Hempel, Maria; Jung, Hannes; Kasemann, Matthias; Keaveney, James; Kleinwort, Claus; Korol, Ievgen; Krücker, Dirk; Lange, Wolfgang; Lelek, Aleksandra; Lenz, Teresa; Leonard, Jessica; Lipka, Katerina; Lohmann, Wolfgang; Mankel, Rainer; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mittag, Gregor; Mnich, Joachim; Mussgiller, Andreas; Ntomari, Eleni; Pitzl, Daniel; Raspereza, Alexei; Savitskyi, Mykola; Saxena, Pooja; Shevchenko, Rostyslav; Spannagel, Simon; Stefaniuk, Nazar; Van Onsem, Gerrit Patrick; Walsh, Roberval; Wen, Yiwen; Wichmann, Katarzyna; Wissing, Christoph; Zenaiev, Oleksandr; Aggleton, Robin; Bein, Samuel; Blobel, Volker; Centis Vignali, Matteo; Dreyer, Torben; Garutti, Erika; Gonzalez, Daniel; Haller, Johannes; Hinzmann, Andreas; Hoffmann, Malte; Karavdina, Anastasia; Klanner, Robert; Kogler, Roman; Kovalchuk, Nataliia; Kurz, Simon; Lapsien, Tobias; Marconi, Daniele; Meyer, Mareike; Niedziela, Marek; Nowatschin, Dominik; Pantaleo, Felice; Peiffer, Thomas; Perieanu, Adrian; Scharf, Christian; Schleper, Peter; Schmidt, Alexander; Schumann, Svenja; Schwandt, Joern; Sonneveld, Jory; Stadie, Hartmut; Steinbrück, Georg; Stober, Fred-Markus Helmut; Stöver, Marc; Tholen, Heiner; Troendle, Daniel; Usai, Emanuele; Vanhoefer, Annika; Vormwald, Benedikt; Akbiyik, Melike; Barth, Christian; Baselga, Marta; Baur, Sebastian; Butz, Erik; Caspart, René; Chwalek, Thorsten; Colombo, Fabio; De Boer, Wim; Dierlamm, Alexander; El Morabit, Karim; Faltermann, Nils; Freund, Benedikt; Friese, Raphael; Giffels, Manuel; Harrendorf, Marco Alexander; Hartmann, Frank; Heindl, Stefan Michael; Husemann, Ulrich; Kassel, Florian; Kudella, Simon; Mildner, Hannes; Mozer, Matthias Ulrich; Müller, Thomas; Plagge, Michael; Quast, Gunter; Rabbertz, Klaus; Schröder, Matthias; Shvetsov, Ivan; Sieber, Georg; Simonis, Hans-Jürgen; Ulrich, Ralf; Wayand, Stefan; Weber, Marc; Weiler, Thomas; Williamson, Shawn; Wöhrmann, Clemens; Wolf, Roger; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Kyriakis, Aristotelis; Loukas, Demetrios; Topsis-Giotis, Iasonas; Karathanasis, George; Kesisoglou, Stilianos; Panagiotou, Apostolos; Saoulidou, Niki; Kousouris, Konstantinos; Evangelou, Ioannis; Foudas, Costas; Gianneios, Paraskevas; Katsoulis, Panagiotis; Kokkas, Panagiotis; Mallios, Stavros; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Strologas, John; Triantis, Frixos A; Tsitsonis, Dimitrios; Csanad, Mate; Filipovic, Nicolas; Pasztor, Gabriella; Surányi, Olivér; Veres, Gabor Istvan; Bencze, Gyorgy; Hajdu, Csaba; Horvath, Dezso; Hunyadi, Ádám; Sikler, Ferenc; Veszpremi, Viktor; Beni, Noemi; Czellar, Sandor; Karancsi, János; Makovec, Alajos; Molnar, Jozsef; Szillasi, Zoltan; Bartók, Márton; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Choudhury, Somnath; Komaragiri, Jyothsna Rani; Bahinipati, Seema; Bhowmik, Sandeep; Mal, Prolay; Mandal, Koushik; Nayak, Aruna; Sahoo, Deepak Kumar; Sahoo, Niladribihari; Swain, Sanjay Kumar; Bansal, Sunil; Beri, Suman Bala; Bhatnagar, Vipin; Chawla, Ridhi; Dhingra, Nitish; Kalsi, Amandeep Kaur; Kaur, Anterpreet; Kaur, Manjit; Kaur, Sandeep; Kumar, Ramandeep; Kumari, Priyanka; Mehta, Ankita; Singh, Jasbir; Walia, Genius; Kumar, Ashok; Shah, Aashaq; Bhardwaj, Ashutosh; Chauhan, Sushil; Choudhary, Brajesh C; Garg, Rocky Bala; Keshri, Sumit; Kumar, Ajay; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Sharma, Ramkrishna; Bhardwaj, Rishika; Bhattacharya, Rajarshi; Bhattacharya, Satyaki; Bhawandeep, Bhawandeep; Dey, Sourav; Dutt, Suneel; Dutta, Suchandra; Ghosh, Shamik; Majumdar, Nayana; Modak, Atanu; Mondal, Kuntal; Mukhopadhyay, Supratik; Nandan, Saswati; Purohit, Arnab; Roy, Ashim; Roy Chowdhury, Suvankar; Sarkar, Subir; Sharan, Manoj; Thakur, Shalini; Behera, Prafulla Kumar; Chudasama, Ruchi; Dutta, Dipanwita; Jha, Vishwajeet; Kumar, Vineet; Mohanty, Ajit Kumar; Netrakanti, Pawan Kumar; Pant, Lalit Mohan; Shukla, Prashant; Topkar, Anita; Aziz, Tariq; Dugad, Shashikant; Mahakud, Bibhuprasad; Mitra, Soureek; Mohanty, Gagan Bihari; Sur, Nairit; Sutar, Bajrang; Banerjee, Sudeshna; Bhattacharya, Soham; Chatterjee, Suman; Das, Pallabi; Guchait, Monoranjan; Jain, Sandhya; Kumar, Sanjeev; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Sarkar, Tanmay; Wickramage, Nadeesha; Chauhan, Shubhanshu; Dube, Sourabh; Hegde, Vinay; Kapoor, Anshul; Kothekar, Kunal; Pandey, Shubham; Rane, Aditee; Sharma, Seema; Chenarani, Shirin; Eskandari Tadavani, Esmaeel; Etesami, Seyed Mohsen; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Naseri, Mohsen; Paktinat Mehdiabadi, Saeid; Rezaei Hosseinabadi, Ferdos; Safarzadeh, Batool; Zeinali, Maryam; Felcini, Marta; Grunewald, Martin; Abbrescia, Marcello; Calabria, Cesare; Colaleo, Anna; Creanza, Donato; Cristella, Leonardo; De Filippis, Nicola; De Palma, Mauro; Errico, Filippo; Fiore, Luigi; Iaselli, Giuseppe; Lezki, Samet; Maggi, Giorgio; Maggi, Marcello; Miniello, Giorgia; My, Salvatore; Nuzzo, Salvatore; Pompili, Alexis; Pugliese, Gabriella; Radogna, Raffaella; Ranieri, Antonio; Selvaggi, Giovanna; Sharma, Archana; Silvestris, Lucia; Venditti, Rosamaria; Verwilligen, Piet; Abbiendi, Giovanni; Battilana, Carlo; Bonacorsi, Daniele; Borgonovi, Lisa; Braibant-Giacomelli, Sylvie; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Chhibra, Simranjit Singh; Codispoti, Giuseppe; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Montanari, Alessandro; Navarria, Francesco; Perrotta, Andrea; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Albergo, Sebastiano; Costa, Salvatore; Di Mattia, Alessandro; Giordano, Ferdinando; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Chatterjee, Kalyanmoy; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Russo, Lorenzo; Sguazzoni, Giacomo; Strom, Derek; Viliani, Lorenzo; Benussi, Luigi; Bianco, Stefano; Fabbri, Franco; Piccolo, Davide; Primavera, Federica; Calvelli, Valerio; Ferro, Fabrizio; Ravera, Fabio; Robutti, Enrico; Tosi, Silvano; Benaglia, Andrea; Beschi, Andrea; Brianza, Luca; Brivio, Francesco; Ciriolo, Vincenzo; Dinardo, Mauro Emanuele; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Govoni, Pietro; Malberti, Martina; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pauwels, Kristof; Pedrini, Daniele; Pigazzini, Simone; Ragazzi, Stefano; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; Di Guida, Salvatore; Fabozzi, Francesco; Fienga, Francesco; Iorio, Alberto Orso Maria; Khan, Wajid Ali; Lista, Luca; Meola, Sabino; Paolucci, Pierluigi; Sciacca, Crisostomo; Thyssen, Filip; Azzi, Patrizia; Bacchetta, Nicola; Benato, Lisa; Bisello, Dario; Boletti, Alessio; Checchia, Paolo; Dall'Osso, Martino; De Castro Manzano, Pablo; Dorigo, Tommaso; Dosselli, Umberto; Fanzago, Federica; Gasparini, Fabrizio; Gasparini, Ugo; Gozzelino, Andrea; Lacaprara, Stefano; Lujan, Paul; Margoni, Martino; Meneguzzo, Anna Teresa; Pozzobon, Nicola; Ronchese, Paolo; Rossin, Roberto; Simonetto, Franco; Torassa, Ezio; Ventura, Sandro; Zanetti, Marco; Zotto, Pierluigi; Braghieri, Alessandro; Magnani, Alice; Montagna, Paolo; Ratti, Sergio P; Re, Valerio; Ressegotti, Martina; Riccardi, Cristina; Salvini, Paola; Vai, Ilaria; Vitulo, Paolo; Alunni Solestizi, Luisa; Biasini, Maurizio; Bilei, Gian Mario; Cecchi, Claudia; Ciangottini, Diego; Fanò, Livio; Leonardi, Roberto; Manoni, Elisa; Mantovani, Giancarlo; Mariani, Valentina; Menichelli, Mauro; Rossi, Alessandro; Santocchia, Attilio; Spiga, Daniele; Androsov, Konstantin; Azzurri, Paolo; Bagliesi, Giuseppe; Boccali, Tommaso; Borrello, Laura; Castaldi, Rino; Ciocci, Maria Agnese; Dell'Orso, Roberto; Fedi, Giacomo; Giannini, Leonardo; Giassi, Alessandro; Grippo, Maria Teresa; Ligabue, Franco; Lomtadze, Teimuraz; Manca, Elisabetta; Mandorli, Giulio; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Savoy-Navarro, Aurore; Spagnolo, Paolo; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Barone, Luciano; Cavallari, Francesca; Cipriani, Marco; Daci, Nadir; Del Re, Daniele; Di Marco, Emanuele; Diemoz, Marcella; Gelli, Simone; Longo, Egidio; Margaroli, Fabrizio; Marzocchi, Badder; Meridiani, Paolo; Organtini, Giovanni; Paramatti, Riccardo; Preiato, Federico; Rahatlou, Shahram; Rovelli, Chiara; Santanastasio, Francesco; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Bartosik, Nazar; Bellan, Riccardo; Biino, Cristina; Cartiglia, Nicolo; Cenna, Francesca; Costa, Marco; Covarelli, Roberto; Degano, Alessandro; Demaria, Natale; Kiani, Bilal; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Monteil, Ennio; Monteno, Marco; Obertino, Maria Margherita; Pacher, Luca; Pastrone, Nadia; Pelliccioni, Mario; Pinna Angioni, Gian Luca; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Shchelina, Ksenia; Sola, Valentina; Solano, Ada; Staiano, Amedeo; Traczyk, Piotr; Belforte, Stefano; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Zanetti, Anna; Kim, Dong Hee; Kim, Gui Nyun; Kim, Min Suk; Lee, Jeongeun; Lee, Sangeun; Lee, Seh Wook; Moon, Chang-Seong; Oh, Young Do; Sekmen, Sezen; Son, Dong-Chul; Yang, Yu Chul; Lee, Ari; Kim, Hyunchul; Moon, Dong Ho; Oh, Geonhee; Brochero Cifuentes, Javier Andres; Goh, Junghwan; Kim, Tae Jeong; Cho, Sungwoong; Choi, Suyong; Go, Yeonju; Gyun, Dooyeon; Ha, Seungkyu; Hong, Byung-Sik; Jo, Youngkwon; Kim, Yongsun; Lee, Kisoo; Lee, Kyong Sei; Lee, Songkyo; Lim, Jaehoon; Park, Sung Keun; Roh, Youn; Almond, John; Kim, Junho; Kim, Jae Sung; Lee, Haneol; Lee, Kyeongpil; Nam, Kyungwook; Oh, Sung Bin; Radburn-Smith, Benjamin Charles; Seo, Seon-hee; Yang, Unki; Yoo, Hwi Dong; Yu, Geum Bong; Kim, Hyunyong; Kim, Ji Hyun; Lee, Jason Sang Hun; Park, Inkyu; Choi, Young-Il; Hwang, Chanwook; Lee, Jongseok; Yu, Intae; Dudenas, Vytautas; Juodagalvis, Andrius; Vaitkus, Juozas; Ahmed, Ijaz; Ibrahim, Zainol Abidin; Md Ali, Mohd Adli Bin; Mohamad Idris, Faridah; Wan Abdullah, Wan Ahmad Tajuddin; Yusli, Mohd Nizam; Zolkapli, Zukhaimira; Reyes-Almanza, Rogelio; Ramirez-Sanchez, Gabriel; Duran-Osuna, Cecilia; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-De La Cruz, Ivan; Rabadán-Trejo, Raúl Iraq; Lopez-Fernandez, Ricardo; Mejia Guisao, Jhovanny; Sánchez Hernández, Alberto; Carrillo Moreno, Salvador; Oropeza Barrera, Cristina; Vazquez Valencia, Fabiola; Eysermans, Jan; Pedraza, Isabel; Salazar Ibarguen, Humberto Antonio; Uribe Estrada, Cecilia; Morelos Pineda, Antonio; Krofcheck, David; Butler, Philip H; Ahmad, Ashfaq; Ahmad, Muhammad; Hassan, Qamar; Hoorani, Hafeez R; Saddique, Asif; Shah, Mehar Ali; Shoaib, Muhammad; Waqas, Muhammad; Bialkowska, Helena; Bluj, Michal; Boimska, Bozena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Szleper, Michal; Zalewski, Piotr; Bunkowski, Karol; Byszuk, Adrian; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Olszewski, Michal; Pyskir, Andrzej; Walczak, Marek; Bargassa, Pedrame; Beirão Da Cruz E Silva, Cristóvão; Di Francesco, Agostino; Faccioli, Pietro; Galinhas, Bruno; Gallinaro, Michele; Hollar, Jonathan; Leonardo, Nuno; Lloret Iglesias, Lara; Nemallapudi, Mythra Varun; Seixas, Joao; Strong, Giles; Toldaiev, Oleksii; Vadruccio, Daniele; Varela, Joao; Baginyan, Andrey; Golunov, Alexey; Golutvin, Igor; Kamenev, Alexey; Karjavin, Vladimir; Kashunin, Ivan; Korenkov, Vladimir; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Matveev, Viktor; Palichik, Vladimir; Perelygin, Victor; Shmatov, Sergey; Smirnov, Vitaly; Trofimov, Vladimir; Yuldashev, Bekhzod S; Zarubin, Anatoli; Ivanov, Yury; Kim, Victor; Kuznetsova, Ekaterina; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sosnov, Dmitry; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Karneyeu, Anton; Kirsanov, Mikhail; Krasnikov, Nikolai; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Pozdnyakov, Ivan; Safronov, Grigory; Spiridonov, Alexander; Stepennov, Anton; Toms, Maria; Vlasov, Evgueni; Zhokin, Alexander; Aushev, Tagir; Bylinkin, Alexander; Chistov, Ruslan; Danilov, Mikhail; Parygin, Pavel; Philippov, Dmitry; Polikarpov, Sergey; Tarkovskii, Evgenii; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Terkulov, Adel; Baskakov, Alexey; Belyaev, Andrey; Boos, Edouard; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Gribushin, Andrey; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Miagkov, Igor; Obraztsov, Stepan; Petrushanko, Sergey; Savrin, Viktor; Snigirev, Alexander; Blinov, Vladimir; Shtol, Dmitry; Skovpen, Yuri; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Elumakhov, Dmitry; Godizov, Anton; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Mandrik, Petr; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Cirkovic, Predrag; Devetak, Damir; Dordevic, Milos; Milosevic, Jovan; Rekovic, Vladimir; Alcaraz Maestre, Juan; Bachiller, Irene; Barrio Luna, Mar; Cerrada, Marcos; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Flix, Jose; Fouz, Maria Cruz; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Moran, Dermot; Pérez-Calero Yzquierdo, Antonio María; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Senghi Soares, Mara; Álvarez Fernández, Adrian; Albajar, Carmen; de Trocóniz, Jorge F; Missiroli, Marino; Cuevas, Javier; Erice, Carlos; Fernandez Menendez, Javier; Gonzalez Caballero, Isidro; González Fernández, Juan Rodrigo; Palencia Cortezon, Enrique; Sanchez Cruz, Sergio; Vischia, Pietro; Vizan Garcia, Jesus Manuel; Cabrillo, Iban Jose; Calderon, Alicia; Chazin Quero, Barbara; Curras, Esteban; Duarte Campderros, Jordi; Fernandez, Marcos; Garcia-Ferrero, Juan; Gomez, Gervasio; Lopez Virto, Amparo; Marco, Jesus; Martinez Rivero, Celso; Martinez Ruiz del Arbol, Pablo; Matorras, Francisco; Piedra Gomez, Jonatan; Rodrigo, Teresa; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Trevisani, Nicolò; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Akgun, Bora; Auffray, Etiennette; Baillon, Paul; Ball, Austin; Barney, David; Bendavid, Joshua; Bianco, Michele; Bloch, Philippe; Bocci, Andrea; Botta, Cristina; Camporesi, Tiziano; Castello, Roberto; Cepeda, Maria; Cerminara, Gianluca; Chapon, Emilien; Chen, Yi; D'Enterria, David; Dabrowski, Anne; Daponte, Vincenzo; David Tinoco Mendes, Andre; De Gruttola, Michele; De Roeck, Albert; Deelen, Nikkie; Dobson, Marc; Du Pree, Tristan; Dünser, Marc; Dupont, Niels; Elliott-Peisert, Anna; Everaerts, Pieter; Fallavollita, Francesco; Franzoni, Giovanni; Fulcher, Jonathan; Funk, Wolfgang; Gigi, Dominique; Gilbert, Andrew; Gill, Karl; Glege, Frank; Gulhan, Doga; Harris, Philip; Hegeman, Jeroen; Innocente, Vincenzo; Jafari, Abideh; Janot, Patrick; Karacheban, Olena; Kieseler, Jan; Knünz, Valentin; Kornmayer, Andreas; Kortelainen, Matti J; Krammer, Manfred; Lange, Clemens; Lecoq, Paul; Lourenco, Carlos; Lucchini, Marco Toliman; Malgeri, Luca; Mannelli, Marcello; Martelli, Arabella; Meijers, Frans; Merlin, Jeremie Alexandre; Mersi, Stefano; Meschi, Emilio; Milenovic, Predrag; Moortgat, Filip; Mulders, Martijn; Neugebauer, Hannes; Ngadiuba, Jennifer; Orfanelli, Styliani; Orsini, Luciano; Pape, Luc; Perez, Emmanuel; Peruzzi, Marco; Petrilli, Achille; Petrucciani, Giovanni; Pfeiffer, Andreas; Pierini, Maurizio; Rabady, Dinyar; Racz, Attila; Reis, Thomas; Rolandi, Gigi; Rovere, Marco; Sakulin, Hannes; Schäfer, Christoph; Schwick, Christoph; Seidel, Markus; Selvaggi, Michele; Sharma, Archana; Silva, Pedro; Sphicas, Paraskevas; Stakia, Anna; Steggemann, Jan; Stoye, Markus; Tosi, Mia; Treille, Daniel; Triossi, Andrea; Tsirou, Andromachi; Veckalns, Viesturs; Verweij, Marta; Zeuner, Wolfram Dietrich; Bertl, Willi; Caminada, Lea; Deiters, Konrad; Erdmann, Wolfram; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; Kotlinski, Danek; Langenegger, Urs; Rohe, Tilman; Wiederkehr, Stephan Albert; Backhaus, Malte; Bäni, Lukas; Berger, Pirmin; Bianchini, Lorenzo; Casal, Bruno; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dorfer, Christian; Grab, Christoph; Heidegger, Constantin; Hits, Dmitry; Hoss, Jan; Kasieczka, Gregor; Klijnsma, Thomas; Lustermann, Werner; Mangano, Boris; Marionneau, Matthieu; Meinhard, Maren Tabea; Meister, Daniel; Micheli, Francesco; Musella, Pasquale; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pata, Joosep; Pauss, Felicitas; Perrin, Gaël; Perrozzi, Luca; Quittnat, Milena; Reichmann, Michael; Sanz Becerra, Diego Alejandro; Schönenberger, Myriam; Shchutska, Lesya; Tavolaro, Vittorio Raoul; Theofilatos, Konstantinos; Vesterbacka Olsson, Minna Leonora; Wallny, Rainer; Zhu, De Hua; Aarrestad, Thea Klaeboe; Amsler, Claude; Canelli, Maria Florencia; De Cosa, Annapaola; Del Burgo, Riccardo; Donato, Silvio; Galloni, Camilla; Hreus, Tomas; Kilminster, Benjamin; Pinna, Deborah; Rauco, Giorgia; Robmann, Peter; Salerno, Daniel; Schweiger, Korbinian; Seitz, Claudia; Takahashi, Yuta; Zucchetta, Alberto; Candelise, Vieri; Chang, Yu-Hsiang; Cheng, Kai-yu; Doan, Thi Hien; Jain, Shilpi; Khurana, Raman; Kuo, Chia-Ming; Lin, Willis; Pozdnyakov, Andrey; Yu, Shin-Shan; Kumar, Arun; Chang, Paoti; Chao, Yuan; Chen, Kai-Feng; Chen, Po-Hsun; Fiori, Francesco; Hou, George Wei-Shu; Hsiung, Yee; Liu, Yueh-Feng; Lu, Rong-Shyang; Paganis, Efstathios; Psallidas, Andreas; Steen, Arnaud; Tsai, Jui-fa; Asavapibhop, Burin; Kovitanggoon, Kittikul; Singh, Gurpreet; Srimanobhas, Norraphat; Bat, Ayse; Boran, Fatma; Cerci, Salim; Damarseckin, Serdal; Demiroglu, Zuhal Seyma; Dozen, Candan; Dumanoglu, Isa; Girgis, Semiray; Gokbulut, Gul; Guler, Yalcin; Hos, Ilknur; Kangal, Evrim Ersin; Kara, Ozgun; Kayis Topaksu, Aysel; Kiminsu, Ugur; Oglakci, Mehmet; Onengut, Gulsen; Ozdemir, Kadri; Sunar Cerci, Deniz; Tali, Bayram; Tok, Ufuk Guney; Turkcapar, Semra; Zorbakir, Ibrahim Soner; Zorbilmez, Caglar; Karapinar, Guler; Ocalan, Kadir; Yalvac, Metin; Zeyrek, Mehmet; Gülmez, Erhan; Kaya, Mithat; Kaya, Ozlem; Tekten, Sevgi; Yetkin, Elif Asli; Nazlim Agaras, Merve; Atay, Serhat; Cakir, Altan; Cankocak, Kerem; Köseoglu, Ilknur; Grynyov, Boris; Levchuk, Leonid; Ball, Fionn; Beck, Lana; Brooke, James John; Burns, Douglas; Clement, Emyr; Cussans, David; Davignon, Olivier; Flacher, Henning; Goldstein, Joel; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Newbold, Dave M; Paramesvaran, Sudarshan; Sakuma, Tai; Seif El Nasr-storey, Sarah; Smith, Dominic; Smith, Vincent J; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Calligaris, Luigi; Cieri, Davide; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Linacre, Jacob; Olaiya, Emmanuel; Petyt, David; Shepherd-Themistocleous, Claire; Thea, Alessandro; Tomalin, Ian R; Williams, Thomas; Auzinger, Georg; Bainbridge, Robert; Borg, Johan; Breeze, Shane; Buchmuller, Oliver; Bundock, Aaron; Casasso, Stefano; Citron, Matthew; Colling, David; Corpe, Louie; Dauncey, Paul; Davies, Gavin; De Wit, Adinda; Della Negra, Michel; Di Maria, Riccardo; Elwood, Adam; Haddad, Yacine; Hall, Geoffrey; Iles, Gregory; James, Thomas; Lane, Rebecca; Laner, Christian; Lyons, Louis; Magnan, Anne-Marie; Malik, Sarah; Mastrolorenzo, Luca; Matsushita, Takashi; Nash, Jordan; Nikitenko, Alexander; Palladino, Vito; Pesaresi, Mark; Raymond, David Mark; Richards, Alexander; Rose, Andrew; Scott, Edward; Seez, Christopher; Shtipliyski, Antoni; Summers, Sioni; Tapper, Alexander; Uchida, Kirika; Vazquez Acosta, Monica; Virdee, Tejinder; Wardle, Nicholas; Winterbottom, Daniel; Wright, Jack; Zenz, Seth Conrad; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Reid, Ivan; Teodorescu, Liliana; Zahid, Sema; Borzou, Ahmad; Call, Kenneth; Dittmann, Jay; Hatakeyama, Kenichi; Liu, Hongxuan; Pastika, Nathaniel; Smith, Caleb; Bartek, Rachel; Dominguez, Aaron; Buccilli, Andrew; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; West, Christopher; Arcaro, Daniel; Avetisyan, Aram; Bose, Tulika; Gastler, Daniel; Rankin, Dylan; Richardson, Clint; Rohlf, James; Sulak, Lawrence; Zou, David; Benelli, Gabriele; Cutts, David; Garabedian, Alex; Hadley, Mary; Hakala, John; Heintz, Ulrich; Hogan, Julie Managan; Kwok, Ka Hei Martin; Laird, Edward; Landsberg, Greg; Lee, Jangbae; Mao, Zaixing; Narain, Meenakshi; Pazzini, Jacopo; Piperov, Stefan; Sagir, Sinan; Syarif, Rizki; Yu, David; Band, Reyer; Brainerd, Christopher; Breedon, Richard; Burns, Dustin; Calderon De La Barca Sanchez, Manuel; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Erbacher, Robin; Flores, Chad; Funk, Garrett; Ko, Winston; Lander, Richard; Mclean, Christine; Mulhearn, Michael; Pellett, Dave; Pilot, Justin; Shalhout, Shalhout; Shi, Mengyao; Smith, John; Stolp, Dustin; Tos, Kyle; Tripathi, Mani; Wang, Zhangqier; Bachtis, Michail; Bravo, Cameron; Cousins, Robert; Dasgupta, Abhigyan; Florent, Alice; Hauser, Jay; Ignatenko, Mikhail; Mccoll, Nickolas; Regnard, Simon; Saltzberg, David; Schnaible, Christian; Valuev, Vyacheslav; Bouvier, Elvire; Burt, Kira; Clare, Robert; Ellison, John Anthony; Gary, J William; Ghiasi Shirazi, Seyyed Mohammad Amin; Hanson, Gail; Heilman, Jesse; Karapostoli, Georgia; Kennedy, Elizabeth; Lacroix, Florent; Long, Owen Rosser; Olmedo Negrete, Manuel; Paneva, Mirena Ivova; Si, Weinan; Wang, Long; Wei, Hua; Wimpenny, Stephen; Yates, Brent; Branson, James G; Cittolin, Sergio; Derdzinski, Mark; Gerosa, Raffaele; Gilbert, Dylan; Hashemi, Bobak; Holzner, André; Klein, Daniel; Kole, Gouranga; Krutelyov, Vyacheslav; Letts, James; Masciovecchio, Mario; Olivito, Dominick; Padhi, Sanjay; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Tadel, Matevz; Vartak, Adish; Wasserbaech, Steven; Wood, John; Würthwein, Frank; Yagil, Avraham; Zevi Della Porta, Giovanni; Amin, Nick; Bhandari, Rohan; Bradmiller-Feld, John; Campagnari, Claudio; Dishaw, Adam; Dutta, Valentina; Franco Sevilla, Manuel; Golf, Frank; Gouskos, Loukas; Heller, Ryan; Incandela, Joe; Ovcharova, Ana; Qu, Huilin; Richman, Jeffrey; Stuart, David; Suarez, Indara; Yoo, Jaehyeok; Anderson, Dustin; Bornheim, Adolf; Lawhorn, Jay Mathew; Newman, Harvey B; Nguyen, Thong; Pena, Cristian; Spiropulu, Maria; Vlimant, Jean-Roch; Xie, Si; Zhang, Zhicai; Zhu, Ren-Yuan; Andrews, Michael Benjamin; Ferguson, Thomas; Mudholkar, Tanmay; Paulini, Manfred; Russ, James; Sun, Menglei; Vogel, Helmut; Vorobiev, Igor; Weinberg, Marc; Cumalat, John Perry; Ford, William T; Jensen, Frank; Johnson, Andrew; Krohn, Michael; Leontsinis, Stefanos; Mulholland, Troy; Stenson, Kevin; Wagner, Stephen Robert; Alexander, James; Chaves, Jorge; Chu, Jennifer; Dittmer, Susan; Mcdermott, Kevin; Mirman, Nathan; Patterson, Juliet Ritchie; Quach, Dan; Rinkevicius, Aurelijus; Ryd, Anders; Skinnari, Louise; Soffi, Livia; Tan, Shao Min; Tao, Zhengcheng; Thom, Julia; Tucker, Jordan; Wittich, Peter; Zientek, Margaret; Abdullin, Salavat; Albrow, Michael; Alyari, Maral; Apollinari, Giorgio; Apresyan, Artur; Apyan, Aram; Banerjee, Sunanda; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Bolla, Gino; Burkett, Kevin; Butler, Joel Nathan; Canepa, Anadi; Cerati, Giuseppe Benedetto; Cheung, Harry; Chlebana, Frank; Cremonesi, Matteo; Duarte, Javier; Elvira, Victor Daniel; Freeman, Jim; Gecse, Zoltan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Grünendahl, Stefan; Gutsche, Oliver; Harris, Robert M; Hasegawa, Satoshi; Hirschauer, James; Hu, Zhen; Jayatilaka, Bodhitha; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kreis, Benjamin; Lammel, Stephan; Lincoln, Don; Lipton, Ron; Liu, Miaoyuan; Liu, Tiehui; Lopes De Sá, Rafael; Lykken, Joseph; Maeshima, Kaori; Magini, Nicolo; Marraffino, John Michael; Mason, David; McBride, Patricia; Merkel, Petra; Mrenna, Stephen; Nahn, Steve; O'Dell, Vivian; Pedro, Kevin; Prokofyev, Oleg; Rakness, Gregory; Ristori, Luciano; Schneider, Basil; Sexton-Kennedy, Elizabeth; Soha, Aron; Spalding, William J; Spiegel, Leonard; Stoynev, Stoyan; Strait, James; Strobbe, Nadja; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vernieri, Caterina; Verzocchi, Marco; Vidal, Richard; Wang, Michael; Weber, Hannsjoerg Artur; Whitbeck, Andrew; Acosta, Darin; Avery, Paul; Bortignon, Pierluigi; Bourilkov, Dimitri; Brinkerhoff, Andrew; Carnes, Andrew; Carver, Matthew; Curry, David; Field, Richard D; Furic, Ivan-Kresimir; Gleyzer, Sergei V; Joshi, Bhargav Madhusudan; Konigsberg, Jacobo; Korytov, Andrey; Kotov, Khristian; Ma, Peisen; Matchev, Konstantin; Mei, Hualin; Mitselmakher, Guenakh; Shi, Kun; Sperka, David; Terentyev, Nikolay; Thomas, Laurent; Wang, Jian; Wang, Sean-Jiun; Yelton, John; Joshi, Yagya Raj; Linn, Stephan; Markowitz, Pete; Rodriguez, Jorge Luis; Ackert, Andrew; Adams, Todd; Askew, Andrew; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Kolberg, Ted; Martinez, German; Perry, Thomas; Prosper, Harrison; Saha, Anirban; Santra, Arka; Sharma, Varun; Yohay, Rachel; Baarmand, Marc M; Bhopatkar, Vallary; Colafranceschi, Stefano; Hohlmann, Marcus; Noonan, Daniel; Roy, Titas; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Berry, Douglas; Betts, Russell Richard; Cavanaugh, Richard; Chen, Xuan; Evdokimov, Olga; Gerber, Cecilia Elena; Hangal, Dhanush Anil; Hofman, David Jonathan; Jung, Kurt; Kamin, Jason; Sandoval Gonzalez, Irving Daniel; Tonjes, Marguerite; Trauger, Hallie; Varelas, Nikos; Wang, Hui; Wu, Zhenbin; Zhang, Jingyu; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Durgut, Süleyman; Gandrajula, Reddy Pratap; Haytmyradov, Maksat; Khristenko, Viktor; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Penzo, Aldo; Snyder, Christina; Tiras, Emrah; Wetzel, James; Yi, Kai; Blumenfeld, Barry; Cocoros, Alice; Eminizer, Nicholas; Fehling, David; Feng, Lei; Gritsan, Andrei; Maksimovic, Petar; Roskes, Jeffrey; Sarica, Ulascan; Swartz, Morris; Xiao, Meng; You, Can; Al-bataineh, Ayman; Baringer, Philip; Bean, Alice; Boren, Samuel; Bowen, James; Castle, James; Khalil, Sadia; Kropivnitskaya, Anna; Majumder, Devdatta; Mcbrayer, William; Murray, Michael; Royon, Christophe; Sanders, Stephen; Schmitz, Erich; Tapia Takaki, Daniel; Wang, Quan; Ivanov, Andrew; Kaadze, Ketino; Maravin, Yurii; Mohammadi, Abdollah; Saini, Lovedeep Kaur; Skhirtladze, Nikoloz; Toda, Sachiko; Rebassoo, Finn; Wright, Douglas; Anelli, Christopher; Baden, Drew; Baron, Owen; Belloni, Alberto; Eno, Sarah Catherine; Feng, Yongbin; Ferraioli, Charles; Hadley, Nicholas John; Jabeen, Shabnam; Jeng, Geng-Yuan; Kellogg, Richard G; Kunkle, Joshua; Mignerey, Alice; Ricci-Tam, Francesca; Shin, Young Ho; Skuja, Andris; Tonwar, Suresh C; Abercrombie, Daniel; Allen, Brandon; Azzolini, Virginia; Barbieri, Richard; Baty, Austin; Bi, Ran; Brandt, Stephanie; Busza, Wit; Cali, Ivan Amos; D'Alfonso, Mariarosaria; Demiragli, Zeynep; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Hsu, Dylan; Hu, Miao; Iiyama, Yutaro; Innocenti, Gian Michele; Klute, Markus; Kovalskyi, Dmytro; Lee, Yen-Jie; Levin, Andrew; Luckey, Paul David; Maier, Benedikt; Marini, Andrea Carlo; Mcginn, Christopher; Mironov, Camelia; Narayanan, Siddharth; Niu, Xinmei; Paus, Christoph; Roland, Christof; Roland, Gunther; Salfeld-Nebgen, Jakob; Stephans, George; Tatar, Kaya; Velicanu, Dragos; Wang, Jing; Wang, Ta-Wei; Wyslouch, Bolek; Benvenuti, Alberto; Chatterjee, Rajdeep Mohan; Evans, Andrew; Hansen, Peter; Hiltbrand, Joshua; Kalafut, Sean; Kubota, Yuichi; Lesko, Zachary; Mans, Jeremy; Nourbakhsh, Shervin; Ruckstuhl, Nicole; Rusack, Roger; Turkewitz, Jared; Wadud, Mohammad Abrar; Acosta, John Gabriel; Oliveros, Sandra; Avdeeva, Ekaterina; Bloom, Kenneth; Claes, Daniel R; Fangmeier, Caleb; Gonzalez Suarez, Rebeca; Kamalieddin, Rami; Kravchenko, Ilya; Monroy, Jose; Siado, Joaquin Emilo; Snow, Gregory R; Stieger, Benjamin; Dolen, James; Godshalk, Andrew; Harrington, Charles; Iashvili, Ia; Nguyen, Duong; Parker, Ashley; Rappoccio, Salvatore; Roozbahani, Bahareh; Alverson, George; Barberis, Emanuela; Freer, Chad; Hortiangtham, Apichart; Massironi, Andrea; Morse, David Michael; Orimoto, Toyoko; Teixeira De Lima, Rafael; Trocino, Daniele; Wamorkar, Tanvi; Wang, Bingran; Wisecarver, Andrew; Wood, Darien; Bhattacharya, Saptaparna; Charaf, Otman; Hahn, Kristan Allan; Mucia, Nicholas; Odell, Nathaniel; Schmitt, Michael Henry; Sung, Kevin; Trovato, Marco; Velasco, Mayda; Bucci, Rachael; Dev, Nabarun; Hildreth, Michael; Hurtado Anampa, Kenyi; Jessop, Colin; Karmgard, Daniel John; Kellams, Nathan; Lannon, Kevin; Li, Wenzhao; Loukas, Nikitas; Marinelli, Nancy; Meng, Fanbo; Mueller, Charles; Musienko, Yuri; Planer, Michael; Reinsvold, Allison; Ruchti, Randy; Siddireddy, Prasanna; Smith, Geoffrey; Taroni, Silvia; Wayne, Mitchell; Wightman, Andrew; Wolf, Matthias; Woodard, Anna; Alimena, Juliette; Antonelli, Louis; Bylsma, Ben; Durkin, Lloyd Stanley; Flowers, Sean; Francis, Brian; Hart, Andrew; Hill, Christopher; Ji, Weifeng; Liu, Bingxuan; Luo, Wuming; Winer, Brian L; Wulsin, Howard Wells; Cooperstein, Stephane; Driga, Olga; Elmer, Peter; Hardenbrook, Joshua; Hebda, Philip; Higginbotham, Samuel; Kalogeropoulos, Alexis; Lange, David; Luo, Jingyu; Marlow, Daniel; Mei, Kelvin; Ojalvo, Isabel; Olsen, James; Palmer, Christopher; Piroué, Pierre; Stickland, David; Tully, Christopher; Malik, Sudhir; Norberg, Scarlet; Barker, Anthony; Barnes, Virgil E; Das, Souvik; Folgueras, Santiago; Gutay, Laszlo; Jha, Manoj; Jones, Matthew; Jung, Andreas Werner; Khatiwada, Ajeeta; Miller, David Harry; Neumeister, Norbert; Peng, Cheng-Chieh; Qiu, Hao; Schulte, Jan-Frederik; Sun, Jian; Wang, Fuqiang; Xiao, Rui; Xie, Wei; Cheng, Tongguang; Parashar, Neeti; Stupak, John; Chen, Zhenyu; Ecklund, Karl Matthew; Freed, Sarah; Geurts, Frank JM; Guilbaud, Maxime; Kilpatrick, Matthew; Li, Wei; Michlin, Benjamin; Padley, Brian Paul; Roberts, Jay; Rorie, Jamal; Shi, Wei; Tu, Zhoudunming; Zabel, James; Zhang, Aobo; Bodek, Arie; de Barbaro, Pawel; Demina, Regina; Duh, Yi-ting; Ferbel, Thomas; Galanti, Mario; Garcia-Bellido, Aran; Han, Jiyeon; Hindrichs, Otto; Khukhunaishvili, Aleko; Lo, Kin Ho; Tan, Ping; Verzetti, Mauro; Ciesielski, Robert; Goulianos, Konstantin; Mesropian, Christina; Agapitos, Antonis; Chou, John Paul; Gershtein, Yuri; Gómez Espinosa, Tirso Alejandro; Halkiadakis, Eva; Heindl, Maximilian; Hughes, Elliot; Kaplan, Steven; Kunnawalkam Elayavalli, Raghav; Kyriacou, Savvas; Lath, Amitabh; Montalvo, Roy; Nash, Kevin; Osherson, Marc; Saka, Halil; Salur, Sevil; Schnetzer, Steve; Sheffield, David; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Thomassen, Peter; Walker, Matthew; Delannoy, Andrés G; Foerster, Mark; Heideman, Joseph; Riley, Grant; Rose, Keith; Spanier, Stefan; Thapa, Krishna; Bouhali, Othmane; Castaneda Hernandez, Alfredo; Celik, Ali; Dalchenko, Mykhailo; De Mattia, Marco; Delgado, Andrea; Dildick, Sven; Eusebi, Ricardo; Gilmore, Jason; Huang, Tao; Kamon, Teruki; Mueller, Ryan; Pakhotin, Yuriy; Patel, Rishi; Perloff, Alexx; Perniè, Luca; Rathjens, Denis; Safonov, Alexei; Tatarinov, Aysen; Ulmer, Keith; Akchurin, Nural; Damgov, Jordan; De Guio, Federico; Dudero, Phillip Russell; Faulkner, James; Gurpinar, Emine; Kunori, Shuichi; Lamichhane, Kamal; Lee, Sung Won; Libeiro, Terence; Mengke, Tielige; Muthumuni, Samila; Peltola, Timo; Undleeb, Sonaina; Volobouev, Igor; Wang, Zhixing; Greene, Senta; Gurrola, Alfredo; Janjam, Ravi; Johns, Willard; Maguire, Charles; Melo, Andrew; Ni, Hong; Padeken, Klaas; Sheldon, Paul; Tuo, Shengquan; Velkovska, Julia; Xu, Qiao; Arenton, Michael Wayne; Barria, Patrizia; Cox, Bradley; Hirosky, Robert; Joyce, Matthew; Ledovskoy, Alexander; Li, Hengne; Neu, Christopher; Sinthuprasith, Tutanon; Wang, Yanchu; Wolfe, Evan; Xia, Fan; Harr, Robert; Karchin, Paul Edmund; Poudyal, Nabin; Sturdy, Jared; Thapa, Prakash; Zaleski, Shawn; Brodski, Michael; Buchanan, James; Caillol, Cécile; Dasu, Sridhara; Dodd, Laura; Duric, Senka; Gomber, Bhawna; Grothe, Monika; Herndon, Matthew; Hervé, Alain; Hussain, Usama; Klabbers, Pamela; Lanaro, Armando; Levine, Aaron; Long, Kenneth; Loveless, Richard; Ruggles, Tyler; Savin, Alexander; Smith, Nicholas; Smith, Wesley H; Taylor, Devin; Woods, Nathaniel

2018-05-08

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\\mathrm{t}\\overline{\\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been...

Crack identification and evolution law in the vibration failure process of loaded coal

Science.gov (United States)

Li, Chengwu; Ai, Dihao; Sun, Xiaoyuan; Xie, Beijing

2017-08-01

To study the characteristics of coal cracks produced in the vibration failure process, we set up a static load and static and dynamic combination load failure test simulation system, prepared with different particle size, formation pressure, and firmness coefficient coal samples. Through static load damage testing of coal samples and then dynamic load (vibration exciter) and static (jack) combination destructive testing, the crack images of coal samples under the load condition were obtained. Combined with digital image processing technology, an algorithm of crack identification with high precision and in real-time is proposed. With the crack features of the coal samples under different load conditions as the research object, we analyzed the distribution of cracks on the surface of the coal samples and the factors influencing crack evolution using the proposed algorithm and a high-resolution industrial camera. Experimental results showed that the major portion of the crack after excitation is located in the rear of the coal sample where the vibration exciter cannot act. Under the same disturbance conditions, crack size and particle size exhibit a positive correlation, while crack size and formation pressure exhibit a negative correlation. Soft coal is more likely to lead to crack evolution than hard coal, and more easily causes instability failure. The experimental results and crack identification algorithm provide a solid basis for the prevention and control of instability and failure of coal and rock mass, and they are helpful in improving the monitoring method of coal and rock dynamic disasters.

Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT

Directory of Open Access Journals (Sweden)

Cunsuo Pang

2016-09-01

Full Text Available This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT’s performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated pulse radar, SAR (Synthetic aperture radar, or ISAR (Inverse synthetic aperture radar, for improving the probability of target recognition.

Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT.

Science.gov (United States)

Pang, Cunsuo; Han, Yan; Hou, Huiling; Liu, Shengheng; Zhang, Nan

2016-09-24

This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT's performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated) pulse radar, SAR (Synthetic aperture radar), or ISAR (Inverse synthetic aperture radar), for improving the probability of target recognition.

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.

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)

High-accuracy user identification using EEG biometrics.

Science.gov (United States)

Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K; Ye Wang; Watanabe, Shinji; Tuzel, Oncel; Orlik, Philip

2016-08-01

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

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 ...

Offline Calibration of b-Jet Identification Efficiencies

CERN Document Server

Lowette, Steven; Heyninck, Jan; Vanlaer, Pascal

2006-01-01

A new method to calibrate b-tagging algorithms can be exploited at the LHC, due to the high energy and luminosity of the accelerator. The abundantly produced ttbar pairs can be used to isolate jet samples with a highly enriched b-jet content, on which the b-jet identification algorithms can be calibrated. Two methods are described to extract a b-enriched jet sample in ttbar events, using the semileptonic and the fully leptonic decay modes. The selection of jets is based on a likelihood ratio method. On the selected b-jet enriched jet samples the b-tagging performance is measured, taking into account the impurities of the samples. The most important contributions to the systematic uncertainties are evaluated, resulting in an estimate of the expected precision on the measurement of the b-jet identification performance. For 1 fb-1 (10 fb-1) of integrated luminosity the relative accuracy on the b-jet identification efficiency is expected to be about 6% (4%) in the barrel region and about 10% (5%) in the endcaps.

Edge detection of iris of the eye for human biometric identification system

Directory of Open Access Journals (Sweden)

Kateryna O. Tryfonova

2015-03-01

Full Text Available Method of human biometric identification by iris of the eye is considered as one of the most accurate and reliable methods of identification. Aim of the research is to solve the problem of edge detection of digital image of the human eye iris to be able to implement human biometric identification system by means of mobile device. To achieve this aim the algorithm of edge detection by Canny is considered in work. It consists of the following steps: smoothing, finding gradients, non-maximum suppression, double thresholding with hysteresis. The software implementation of the Canny algorithm is carried out for the Android mobile platform with the use of high level programming language Java.

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

Science.gov (United States)

Kucukural, Alper; Özadam, Hakan; Singh, Guramrit; Moore, Melissa J; Cenik, Can

2013-10-01

Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.

Exploration of available feature detection and identification systems and their performance on radiographs

Science.gov (United States)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

Kinematic Identification of Parallel Mechanisms by a Divide and Conquer Strategy

DEFF Research Database (Denmark)

Durango, Sebastian; Restrepo, David; Ruiz, Oscar

2010-01-01

using the inverse calibration method. The identification poses are selected optimizing the observability of the kinematic parameters from a Jacobian identification matrix. With respect to traditional identification methods the main advantages of the proposed Divide and Conquer kinematic identification...... strategy are: (i) reduction of the kinematic identification computational costs, (ii) improvement of the numerical efficiency of the kinematic identification algorithm and, (iii) improvement of the kinematic identification results. The contributions of the paper are: (i) The formalization of the inverse...... calibration method as the Divide and Conquer strategy for the kinematic identification of parallel symmetrical mechanisms and, (ii) a new kinematic identification protocol based on the Divide and Conquer strategy. As an application of the proposed kinematic identification protocol the identification...

Watermarking Algorithms for 3D NURBS Graphic Data

Directory of Open Access Journals (Sweden)

Jae Jun Lee

2004-10-01

Full Text Available Two watermarking algorithms for 3D nonuniform rational B-spline (NURBS graphic data are proposed: one is appropriate for the steganography, and the other for watermarking. Instead of directly embedding data into the parameters of NURBS, the proposed algorithms embed data into the 2D virtual images extracted by parameter sampling of 3D model. As a result, the proposed steganography algorithm can embed information into more places of the surface than the conventional algorithm, while preserving the data size of the model. Also, any existing 2D watermarking technique can be used for the watermarking of 3D NURBS surfaces. From the experiment, it is found that the algorithm for the watermarking is robust to the attacks on weights, control points, and knots. It is also found to be robust to the remodeling of NURBS models.

Comparative analysis of different weight matrices in subspace system identification for structural health monitoring

Science.gov (United States)

Shokravi, H.; Bakhary, NH

2017-11-01

Subspace System Identification (SSI) is considered as one of the most reliable tools for identification of system parameters. Performance of a SSI scheme is considerably affected by the structure of the associated identification algorithm. Weight matrix is a variable in SSI that is used to reduce the dimensionality of the state-space equation. Generally one of the weight matrices of Principle Component (PC), Unweighted Principle Component (UPC) and Canonical Variate Analysis (CVA) are used in the structure of a SSI algorithm. An increasing number of studies in the field of structural health monitoring are using SSI for damage identification. However, studies that evaluate the performance of the weight matrices particularly in association with accuracy, noise resistance, and time complexity properties are very limited. In this study, the accuracy, noise-robustness, and time-efficiency of the weight matrices are compared using different qualitative and quantitative metrics. Three evaluation metrics of pole analysis, fit values and elapsed time are used in the assessment process. A numerical model of a mass-spring-dashpot and operational data is used in this research paper. It is observed that the principal components obtained using PC algorithms are more robust against noise uncertainty and give more stable results for the pole distribution. Furthermore, higher estimation accuracy is achieved using UPC algorithm. CVA had the worst performance for pole analysis and time efficiency analysis. The superior performance of the UPC algorithm in the elapsed time is attributed to using unit weight matrices. The obtained results demonstrated that the process of reducing dimensionality in CVA and PC has not enhanced the time efficiency but yield an improved modal identification in PC.

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.

Multiangle Implementation of Atmospheric Correction (MAIAC): 2. Aerosol Algorithm

Science.gov (United States)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kahn, R.; Korkin, S.; Remer, L.; Levy, R.; Reid, J. S.

2011-01-01

An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 micron) and shortwave infrared (2.1 micron) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Energy Technology Data Exchange (ETDEWEB)

Sirunyan, Albert M; et al.

2017-12-19

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\\mathrm{t}\\overline{\\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

Science.gov (United States)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

Set-Membership Proportionate Affine Projection Algorithms

Directory of Open Access Journals (Sweden)

Stefan Werner

2007-01-01

Full Text Available Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. In this paper, the idea of proportionate adaptation is combined with the framework of set-membership filtering (SMF in an attempt to derive novel computationally efficient algorithms. The resulting algorithms attain an attractive faster converge for both situations of sparse and dispersive channels while decreasing the average computational complexity due to the data discerning feature of the SMF approach. In addition, we propose a rule that allows us to automatically adjust the number of past data pairs employed in the update. This leads to a set-membership proportionate affine projection algorithm (SM-PAPA having a variable data-reuse factor allowing a significant reduction in the overall complexity when compared with a fixed data-reuse factor. Reduced-complexity implementations of the proposed algorithms are also considered that reduce the dimensions of the matrix inversions involved in the update. Simulations show good results in terms of reduced number of updates, speed of convergence, and final mean-squared error.

State Estimation-based Transmission line parameter identification

Directory of Open Access Journals (Sweden)

Fredy Andrés Olarte Dussán

2010-01-01

Full Text Available This article presents two state-estimation-based algorithms for identifying transmission line parameters. The identification technique used simultaneous state-parameter estimation on an artificial power system composed of several copies of the same transmission line, using measurements at different points in time. The first algorithm used active and reactive power measurements at both ends of the line. The second method used synchronised phasor voltage and current measurements at both ends. The algorithms were tested in simulated conditions on the 30-node IEEE test system. All line parameters for this system were estimated with errors below 1%.

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

Directory of Open Access Journals (Sweden)

Gys Albertus Marthinus Meiring

2015-12-01

Full Text Available In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

Radioisotope Identification Of Shielded And Masked SNM RDD Materials

International Nuclear Information System (INIS)

Salaymeh, S.; Jeffcoat, R.

2010-01-01

Sonar and speech techniques have been investigated to improve functionality and enable handheld and other man-portable, mobile, and portal systems to positively detect and identify illicit nuclear materials, with minimal data and with minimal false positives and false negatives. RadSonar isotope detection and identification is an algorithm development project funded by NA-22 and employing the resources of Savannah River National Laboratory and three University Laboratories (JHU-APL, UT-ARL, and UW-APL). Algorithms have been developed that improve the probability of detection and decrease the number of false positives and negatives. Two algorithms have been developed and tested. The first algorithm uses support vector machine (SVM) classifiers to determine the most prevalent nuclide(s) in a spectrum. It then uses a constrained weighted least squares fit to estimate and remove the contribution of these nuclide(s) to the spectrum, iterating classification and fitting until there is nothing of significance left. If any Special Nuclear Materials (SNMs) were detected in this process, a second tier of more stringent classifiers are used to make the final SNM alert decision. The second algorithm is looking at identifying existing feature sets that would be relevant in the radioisotope identification context. The underlying philosophy here is to identify parallels between the physics and/or the structures present in the data for the two applications (speech analysis and gamma spectroscopy). The expectation is that similar approaches may work in both cases. The mel-frequency cepstral representation of spectra is widely used in speech, particularly for two reasons: approximation of the response of the human ear, and simplicity of channel effect separation (in this context, a 'channel' is a method of signal transport that affects the signal, examples being vocal tract shape, room echoes, and microphone response). Measured and simulated gamma-ray spectra from a hand

On multiple crack identification by ultrasonic scanning

Science.gov (United States)

Brigante, M.; Sumbatyan, M. A.

2018-04-01

The present work develops an approach which reduces operator equations arising in the engineering problems to the problem of minimizing the discrepancy functional. For this minimization, an algorithm of random global search is proposed, which is allied to some genetic algorithms. The efficiency of the method is demonstrated by the solving problem of simultaneous identification of several linear cracks forming an array in an elastic medium by using the circular Ultrasonic scanning.

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

Energy Technology Data Exchange (ETDEWEB)

Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)

2013-12-15

Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

International Nuclear Information System (INIS)

Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José

2013-01-01

Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed

Fast simulated annealing inversion of surface waves on pavement using phase-velocity spectra

Science.gov (United States)

Ryden, N.; Park, C.B.

2006-01-01

The conventional inversion of surface waves depends on modal identification of measured dispersion curves, which can be ambiguous. It is possible to avoid mode-number identification and extraction by inverting the complete phase-velocity spectrum obtained from a multichannel record. We use the fast simulated annealing (FSA) global search algorithm to minimize the difference between the measured phase-velocity spectrum and that calculated from a theoretical layer model, including the field setup geometry. Results show that this algorithm can help one avoid getting trapped in local minima while searching for the best-matching layer model. The entire procedure is demonstrated on synthetic and field data for asphalt pavement. The viscoelastic properties of the top asphalt layer are taken into account, and the inverted asphalt stiffness as a function of frequency compares well with laboratory tests on core samples. The thickness and shear-wave velocity of the deeper embedded layers are resolved within 10% deviation from those values measured separately during pavement construction. The proposed method may be equally applicable to normal soil site investigation and in the field of ultrasonic testing of materials. ?? 2006 Society of Exploration Geophysicists.

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.

Identification of physical models

DEFF Research Database (Denmark)

Melgaard, Henrik

1994-01-01

of the model with the available prior knowledge. The methods for identification of physical models have been applied in two different case studies. One case is the identification of thermal dynamics of building components. The work is related to a CEC research project called PASSYS (Passive Solar Components......The problem of identification of physical models is considered within the frame of stochastic differential equations. Methods for estimation of parameters of these continuous time models based on descrete time measurements are discussed. The important algorithms of a computer program for ML or MAP...... design of experiments, which is for instance the design of an input signal that are optimal according to a criterion based on the information provided by the experiment. Also model validation is discussed. An important verification of a physical model is to compare the physical characteristics...

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)

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)

Comparison Study of Subspace Identification Methods Applied to Flexible Structures

Science.gov (United States)

Abdelghani, M.; Verhaegen, M.; Van Overschee, P.; De Moor, B.

1998-09-01

In the past few years, various time domain methods for identifying dynamic models of mechanical structures from modal experimental data have appeared. Much attention has been given recently to so-called subspace methods for identifying state space models. This paper presents a detailed comparison study of these subspace identification methods: the eigensystem realisation algorithm with observer/Kalman filter Markov parameters computed from input/output data (ERA/OM), the robust version of the numerical algorithm for subspace system identification (N4SID), and a refined version of the past outputs scheme of the multiple-output error state space (MOESP) family of algorithms. The comparison is performed by simulating experimental data using the five mode reduced model of the NASA Mini-Mast structure. The general conclusion is that for the case of white noise excitations as well as coloured noise excitations, the N4SID/MOESP algorithms perform equally well but give better results (improved transfer function estimates, improved estimates of the output) compared to the ERA/OM algorithm. The key computational step in the three algorithms is the approximation of the extended observability matrix of the system to be identified, for N4SID/MOESP, or of the observer for the system to be identified, for the ERA/OM. Furthermore, the three algorithms only require the specification of one dimensioning parameter.

A tunable algorithm for collective decision-making.

Science.gov (United States)

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.