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Sample records for system identification based

  1. Expert system based radionuclide identification

    International Nuclear Information System (INIS)

    Aarnio, P.A.; Ala-Heikkil, J.J.; Hakulinen, T.T.; Nikkinen, M.T.

    1998-01-01

    An expert system coupled with the gamma spectrum analysis system SAMPO has been developed for automating the qualitative identification of radionuclides as well as for determining the quantitative parameters of the spectrum components. The program is written in C-language and runs in various environments ranging from PCs to UNIX workstations. The expert system utilizes a complete gamma library with over 2600 nuclides and 80,000 lines, and a rule base of about fifty criteria including energies, relative peak intensities, genesis modes, half lives, parent-daughter relationships, etc. The rule base is furthermore extensible by the user. This is not an original contribution but a somewhat updated version of papers and reports previously published elsewhere. (author)

  2. Improved system blind identification based on second-order ...

    Indian Academy of Sciences (India)

    An improved system blind identification method based on second- order cyclostationary statistics and the properties of group delay, has been ... In the last decade, there has been considerable research on achieving blind identification.

  3. Particle identification system based on dense aerogel

    Energy Technology Data Exchange (ETDEWEB)

    Barnyakov, A.Yu. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Barnyakov, M.Yu. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State Technical University, 20, Karl Marx prospect, Novosibirsk, 630092 (Russian Federation); Beloborodov, K.I., E-mail: K.I.Beloborodov@inp.nsk.su [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State University, 2, Pirogova Street, Novosibirsk 630090 (Russian Federation); Bobrovnikov, V.S.; Buzykaev, A.R. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Danilyuk, A.F. [Boreskov Institute of Catalysis, 5, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Golubev, V.B. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State University, 2, Pirogova Street, Novosibirsk 630090 (Russian Federation); Gulevich, V.V. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Kononov, S.A.; Kravchenko, E.A. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State University, 2, Pirogova Street, Novosibirsk 630090 (Russian Federation); Onuchin, A.P.; Martin, K.A. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State Technical University, 20, Karl Marx prospect, Novosibirsk, 630092 (Russian Federation); Serednyakov, S.I. [Budker Institute of Nuclear Physics, 11, akademika Lavrentieva prospect, Novosibirsk 630090 (Russian Federation); Novosibirsk State University, 2, Pirogova Street, Novosibirsk 630090 (Russian Federation); and others

    2013-12-21

    A threshold Cherenkov counter based on dense aerogel with refraction index n=1.13 is described. This counter is used for kaon identification at momenta below 1 GeV/c in the SND detector, which takes data at the VEPP-2000 e{sup +}e{sup −} collider. The results of measurements of the counter efficiency using electrons, muons, pions, and kaons produced in e{sup +}e{sup −} annihilation are presented.

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

    Directory of Open Access Journals (Sweden)

    Shengxi Zhou

    2013-05-01

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

  5. Rule based deterioration identification and management system

    International Nuclear Information System (INIS)

    Kataoka, S.; Pavinich, W.; Lapides, M.

    1993-01-01

    Under the sponsorship of IHI and EPRI, a rule-based screening system has been developed that can be used by utility engineers to determine which deterioration mechanisms are acting on specific LWR components, and to evaluate the efficacy of an age-related deterioration management program. The screening system was developed using the rule-based shell, NEXPERT, which provides traceability to the data sources used in the logic development. The system addresses all the deterioration mechanisms of specific metals encountered in either BWRs or PWRs. Deterioration mechanisms are listed with reasons why they may occur during the design life of LWRs, considering the plant environment, manufacturing process, service history, material chemical composition, etc. of components in a specific location of a LWR. To eliminate the evaluation of inactive deterioration quickly, a tier structure is applied to the rules. The reasons why deterioration will occur are extracted automatically by backward chaining. To reduce the amount of user input, plant environmental data are stored in files as default environmental data. (author)

  6. A biometric identification system based on eigenpalm and eigenfinger features.

    Science.gov (United States)

    Ribaric, Slobodan; Fratric, Ivan

    2005-11-01

    This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

  7. A network identity authentication system based on Fingerprint identification technology

    Science.gov (United States)

    Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

    2005-10-01

    Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

  8. DNA barcode-based molecular identification system for fish species.

    Science.gov (United States)

    Kim, Sungmin; Eo, Hae-Seok; Koo, Hyeyoung; Choi, Jun-Kil; Kim, Won

    2010-12-01

    In this study, we applied DNA barcoding to identify species using short DNA sequence analysis. We examined the utility of DNA barcoding by identifying 53 Korean freshwater fish species, 233 other freshwater fish species, and 1339 saltwater fish species. We successfully developed a web-based molecular identification system for fish (MISF) using a profile hidden Markov model. MISF facilitates efficient and reliable species identification, overcoming the limitations of conventional taxonomic approaches. MISF is freely accessible at http://bioinfosys.snu.ac.kr:8080/MISF/misf.jsp .

  9. HOC Based Blind Identification of Hydroturbine Shaft Volterra System

    Directory of Open Access Journals (Sweden)

    Bing Bai

    2017-01-01

    Full Text Available In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d., zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method with genetic algorithm (GA and constituted the hybrid genetic algorithm (HGA. Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system.

  10. Developing a personal computer based expert system for radionuclide identification

    International Nuclear Information System (INIS)

    Aarnio, P.A.; Hakulinen, T.T.

    1990-01-01

    Several expert system development tools are available for personal computers today. We have used one of the LISP-based high end tools for nearly two years in developing an expert system for identification of gamma sources. The system contains a radionuclide database of 2055 nuclides and 48000 gamma transitions with a knowledge base of about sixty rules. This application combines a LISP-based inference engine with database management and relatively heavy numerical calculations performed using C-language. The most important feature needed has been the possibility to use LISP and C together with the more advanced object oriented features of the development tool. Main difficulties have been long response times and the big amount (10-16 MB) of computer memory required

  11. Sensor network based vehicle classification and license plate identification system

    Energy Technology Data Exchange (ETDEWEB)

    Frigo, Janette Rose [Los Alamos National Laboratory; Brennan, Sean M [Los Alamos National Laboratory; Rosten, Edward J [Los Alamos National Laboratory; Raby, Eric Y [Los Alamos National Laboratory; Kulathumani, Vinod K [WEST VIRGINIA UNIV.

    2009-01-01

    Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform. Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.

  12. Experimental evaluation of a modal parameter based system identification procedure

    Science.gov (United States)

    Yu, Minli; Feng, Ningsheng; Hahn, Eric J.

    2016-02-01

    Correct modelling of the foundation of a rotor bearing foundation system (RBFS) is an invaluable asset for the balancing and efficient running of turbomachinery. Numerical experiments have shown that a modal parameter based identification approach could be feasible for this purpose but there is a lack of experimental verification of the suitability of such a modal approach for even the simplest systems. In this paper the approach is tested on a simple experimental rig comprising a clamped horizontal bar with lumped masses. It is shown that apart from damping, the proposed approach can identify reasonably accurately the relevant modal parameters of the rig; and that the resulting equivalent system can predict reasonably well the frequency response of the rig. Hence, the proposed approach shows promise but further testing is required, since application to identifying the foundation of an RBFS involves the additional problem of accurately obtaining the force excitation from motion measurements.

  13. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Directory of Open Access Journals (Sweden)

    Yaacob Sazali

    2005-01-01

    Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  14. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Science.gov (United States)

    Nagarajan, R.; Sainarayanan, G.; Yaacob, Sazali; Porle, Rosalyn R.

    2005-12-01

    We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  15. Structural system identification based on variational mode decomposition

    Science.gov (United States)

    Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

    2018-03-01

    In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

  16. Parameter identification of chaos system based on unknown parameter observer

    International Nuclear Information System (INIS)

    Wang Shaoming; Luo Haigeng; Yue Chaoyuan; Liao Xiaoxin

    2008-01-01

    Parameter identification of chaos system based on unknown parameter observer is discussed generally. Based on the work of Guan et al. [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26], the design of unknown parameter observer is improved. The application of the improved approach is extended greatly. The works in some literatures [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26; J.H. Lue, S.C. Zhang, Phys. Lett. A 286 (2001) 148; X.Q. Wu, J.A. Lu, Chaos Solitons Fractals 18 (2003) 721; J. Liu, S.H. Chen, J. Xie, Chaos Solitons Fractals 19 (2004) 533] are only the special cases of our Corollaries 1 and 2. Some observers for Lue system and a new chaos system are designed to test our improved method, and simulations results demonstrate the effectiveness and feasibility of the improved approach

  17. Gain Scheduling Control based on Closed-Loop System Identification

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    the first and a second operating point is identified in closed-loop using system identification methods with open-loop properties. Next, a linear controller is designed for this linearised model, and gain scheduling control can subsequently be achieved by interpolating between each controller...

  18. 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.

  19. SUIS: An Online Graphical Signature-Based User Identification System

    OpenAIRE

    Alam, Shahid

    2016-01-01

    Humans possess a large amount of, and almost limitless, visual memory, that assists them to remember pictures far better than words. This phenomenon has recently motivated the computer security researchers' in academia and industry to design and develop graphical user identification systems (GUISs). Cognometric GUISs are more memorable than drawmetric GUISs, but takes more time to authenticate. None of the previously proposed GUISs combines the advantages of both cognometric and drawmetric sy...

  20. Portable bacterial identification system based on elastic light scatter patterns

    Directory of Open Access Journals (Sweden)

    Bae Euiwon

    2012-08-01

    Full Text Available Abstract Background Conventional diagnosis and identification of bacteria requires shipment of samples to a laboratory for genetic and biochemical analysis. This process can take days and imposes significant delay to action in situations where timely intervention can save lives and reduce associated costs. To enable faster response to an outbreak, a low-cost, small-footprint, portable microbial-identification instrument using forward scatterometry has been developed. Results This device, weighing 9 lb and measuring 12 × 6 × 10.5 in., utilizes elastic light scatter (ELS patterns to accurately capture bacterial colony characteristics and delivers the classification results via wireless access. The overall system consists of two CCD cameras, one rotational and one translational stage, and a 635-nm laser diode. Various software algorithms such as Hough transform, 2-D geometric moments, and the traveling salesman problem (TSP have been implemented to provide colony count and circularity, centering process, and minimized travel time among colonies. Conclusions Experiments were conducted with four bacteria genera using pure and mixed plate and as proof of principle a field test was conducted in four different locations where the average classification rate ranged between 95 and 100%.

  1. Neural network based system for script identification in Indian ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual ...

  2. 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.

  3. 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.

  4. Minimalist identification system based on venous map for security applications

    Science.gov (United States)

    Jacinto G., Edwar; Martínez S., Fredy; Martínez S., Fernando

    2015-07-01

    This paper proposes a technique and an algorithm used to build a device for people identification through the processing of a low resolution camera image. The infrared channel is the only information needed, sensing the blood reaction with the proper wave length, and getting a preliminary snapshot of the vascular map of the back side of the hand. The software uses this information to extract the characteristics of the user in a limited area (region of interest, ROI), unique for each user, which applicable to biometric access control devices. This kind of recognition prototypes functions are expensive, but in this case (minimalist design), the biometric equipment only used a low cost camera and the matrix of IR emitters adaptation to construct an economic and versatile prototype, without neglecting the high level of effectiveness that characterizes this kind of identification method.

  5. 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.

  6. Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model

    Directory of Open Access Journals (Sweden)

    Yazid Edwar

    2014-07-01

    Full Text Available This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA. The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.

  7. Parameter identification based synchronization for a class of chaotic systems with offset vectors

    International Nuclear Information System (INIS)

    Chen Cailian; Feng Gang; Guan Xinping

    2004-01-01

    Based on a parameter identification scheme, a novel synchronization method is presented for a class of chaotic systems with offset vectors which can be represented by the so-called T-S fuzzy model. It is shown that the slave system can synchronize the master system and the unknown parameters of the master system can be identified simultaneously. The delayed feedback technique is also developed in order to reduce the energy and time required for the identification and synchronization. Numerical simulations demonstrate the effectiveness of the proposed method

  8. White blood cells identification system based on convolutional deep neural learning networks.

    Science.gov (United States)

    Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

    2017-11-16

    White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

  9. Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification

    Directory of Open Access Journals (Sweden)

    Ayedh Alqahtani

    2016-01-01

    Full Text Available Solar photovoltaic (PV energy sources are rapidly gaining potential growth and popularity compared to conventional fossil fuel sources. As the merging of PV systems with existing power sources increases, reliable and accurate PV system identification is essential, to address the highly nonlinear change in PV system dynamic and operational characteristics. This paper deals with the identification of a PV system characteristic with a switch-mode power converter. Measured input-output data are collected from a real PV panel to be used for the identification. The data are divided into estimation and validation sets. The identification methodology is discussed. A Hammerstein-Wiener model is identified and selected due to its suitability to best capture the PV system dynamics, and results and discussion are provided to demonstrate the accuracy of the selected model structure.

  10. Frequency domain indirect identification of AMB rotor systems based on fictitious proportional feedback gain

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Hyeong Joon [Dept. of Mechanical Engineering, Soongsil University, Seoul (Korea, Republic of); Kim, Chan Jung [Dept. of Mechanical Design Engineering, Pukyong National University, Busan(Korea, Republic of)

    2016-12-15

    It is very difficult to directly identify an unstable system with uncertain dynamics from frequency domain input-output data. Hence, in these cases, closed-loop frequency responses calculated using a fictitious feedback could be more identifiable than open-loop data. This paper presents a frequency domain indirect identification of AMB rotor systems based on a Fictitious proportional feedback gain (FPFG). The closed-loop effect due to the FPFG can enhance the detectability of the system by moving the system poles, and significantly weigh the target mode in the frequency domain. The effectiveness of the proposed identification method was verified through the frequency domain identification of active magnetic bearing rotor systems.

  11. 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.

  12. Radio Frequency Identification (RFID) Based Employee Attendance Management System

    Science.gov (United States)

    Maramis, G. D. P.; Rompas, P. T. D.

    2018-02-01

    Manually recorded attendance of all the employees has produced some problems such as the data accuracy and staff performance efficiency. The objective of this research is to design and develop a software of RFID attendance system which is integrated with database system. This RFID attendance system was developed using several main components such as tags that will be used as a replacement of ID cards and a reader device that will read the information related to the employee attendance. The result of this project is a software of RFID attendance system that is integrated with the database and has a function to store the data or information of every single employee. This system has a maximum reading range of 2 cm with success probability of 1 and requires a minimum interval between readings of 2 seconds in order to achieve an optimal functionality. By using the system, the discipline attitude of the employees and also the performance of the staff will be improved instantly.

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

    OpenAIRE

    Xiaojun Liu; Youcheng Wang; Hub Hu

    2014-01-01

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

  14. System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques

    DEFF Research Database (Denmark)

    Chen, Tianshi; Andersen, Martin Skovgaard; Ljung, Lennart

    2014-01-01

    Model estimation and structure detection with short data records are two issues that receive increasing interests in System Identification. In this paper, a multiple kernel-based regularization method is proposed to handle those issues. Multiple kernels are conic combinations of fixed kernels...

  15. A network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption

    Science.gov (United States)

    Zhu, Lijuan; Liu, Jingao

    2013-07-01

    This paper describes a network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption. This protocol can provide every bank user a safe and effective way to manage his own bank account, and also can effectively prevent the hacker attacks and bank clerk crime, so that it is absolute to guarantee the legitimate rights and interests of bank users.

  16. 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.

  17. 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.

  18. Identification of chaotic memristor systems based on piecewise adaptive Legendre filters

    International Nuclear Information System (INIS)

    Zhao, Yibo; Zhang, Xiuzai; Xu, Jin; Guo, Yecai

    2015-01-01

    Memristor is a nonlinear device, which plays an important role in the design and implementation of chaotic systems. In order to be able to understand in-depth the complex nonlinear dynamic behaviors in chaotic memristor systems, modeling or identification of its nonlinear model is very important premise. This paper presents a chaotic memristor system identification method based on piecewise adaptive Legendre filters. The threshold decomposition is carried out for the input vector, and also the input signal subintervals via decomposition satisfy the convergence condition of the adaptive Legendre filters. Then the adaptive Legendre filter structure and adaptive weight update algorithm are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics.

  19. Active Vibration damping of Smart composite beams based on system identification technique

    Science.gov (United States)

    Bendine, Kouider; Satla, Zouaoui; Boukhoulda, Farouk Benallel; Nouari, Mohammed

    2018-03-01

    In the present paper, the active vibration control of a composite beam using piezoelectric actuator is investigated. The space state equation is determined using system identification technique based on the structure input output response provided by ANSYS APDL finite element package. The Linear Quadratic (LQG) control law is designed and integrated into ANSYS APDL to perform closed loop simulations. Numerical examples for different types of excitation loads are presented to test the efficiency and the accuracy of the proposed model.

  20. A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

    Directory of Open Access Journals (Sweden)

    Lun Zhai

    2014-01-01

    Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

  1. FRF based position controller design through system identification for A hydraulic cylinder

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Hyoung Kyu; Kim, Dong Hwan [Dept. of Mechanical Design and Robot Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of); Park, Jong Won [Reliability Assessment Center, Korea Institute of Machinery and Materials, Daejeon (Korea, Republic of)

    2015-11-15

    In this study, we have focused on the design of a controller and an operating program for the operation of the hydraulic actuators used in a shaker. To control the motion of the shaker accurately, the position of each hydraulic cylinder should be controlled precisely even under an uncertain environment. For this purpose, we have suggested a control algorithm using an FRF (frequency response function) based control which senses the behavior of the actuator in advance, calculates a transfer function through the system identification method, and provides the final control input. The experimental results on the performance of this system were compared with that of a simple PID control algorithm.

  2. A Comfort-Aware Energy Efficient HVAC System Based on the Subspace Identification Method

    Directory of Open Access Journals (Sweden)

    O. Tsakiridis

    2016-01-01

    Full Text Available A proactive heating method is presented aiming at reducing the energy consumption in a HVAC system while maintaining the thermal comfort of the occupants. The proposed technique fuses time predictions for the zones’ temperatures, based on a deterministic subspace identification method, and zones’ occupancy predictions, based on a mobility model, in a decision scheme that is capable of regulating the balance between the total energy consumed and the total discomfort cost. Simulation results for various occupation-mobility models demonstrate the efficiency of the proposed technique.

  3. Neural-net based unstable machine identification using individual energy functions. [Transient disturbances in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M [Institut Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D J; Pao, Yohhan [Case Western Reserve Univ., Cleveland, OH (United States)

    1991-10-01

    The identification of the mode of instability plays an essential role in generating principal energy boundary hypersurfaces. We present a new method for unstable machine identification based on the use of supervised learning neural-net technology, and the adaptive pattern recognition concept. It is shown that using individual energy functions as pattern features, appropriately trained neural-nets can retrieve the reliable characterization of the transient process including critical clearing time parameter, mode of instability and energy margins. Generalization capabilities of the neural-net processing allow for these assessments to be made independently of load levels. The results obtained from computer simulations are presented using the New England power system, as an example. (author).

  4. Parameter Identification and Synchronization of Uncertain Chaotic Systems Based on Sliding Mode Observer

    Directory of Open Access Journals (Sweden)

    Li-lian Huang

    2013-01-01

    Full Text Available The synchronization of nonlinear uncertain chaotic systems is investigated. We propose a sliding mode state observer scheme which combines the sliding mode control with observer theory and apply it into the uncertain chaotic system with unknown parameters and bounded interference. Based on Lyapunov stability theory, the constraints of synchronization and proof are given. This method not only can realize the synchronization of chaotic systems, but also identify the unknown parameters and obtain the correct parameter estimation. Otherwise, the synchronization of chaotic systems with unknown parameters and bounded external disturbances is robust by the design of the sliding surface. Finally, numerical simulations on Liu chaotic system with unknown parameters and disturbances are carried out. Simulation results show that this synchronization and parameter identification has been totally achieved and the effectiveness is verified very well.

  5. The Use of Web Based Expert System Application for Identification and Intervention of Children with Special Needs in Inclusive School

    Directory of Open Access Journals (Sweden)

    Dian Atnantomi Wiliyanto

    2017-11-01

    Full Text Available This research is conducted to determine the effectiveness of web based expert system application for identification and intervention of children with special needs in inclusive school. 40 teachers of inclusive school in Surakarta participated in this research. The result showed that: (1 web based expert system application was suitable with the needs of teachers/officers, had 50% (excellence criteria, (2 web based expert system application was worthwhile for identification of children with special needs, had 50% (excellence criteria, (3 web based expert system application was easy to use, had 52.5% (good criteria, and (4 web based expert system application had result accuracy in making decision, had 52.5% (good criteria. It shows that the use of web based expert system application is effective to be used by teachers in inclusive school in conducting identification and intervention with percentage on average was more than 50%.

  6. Physics-based mathematical models for quantum devices via experimental system identification

    Energy Technology Data Exchange (ETDEWEB)

    Schirmer, S G; Oi, D K L; Devitt, S J [Department of Applied Maths and Theoretical Physics, University of Cambridge, Wilberforce Rd, Cambridge, CB3 0WA (United Kingdom); SUPA, Department of Physics, University of Strathclyde, Glasgow G4 0NG (United Kingdom); National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430 (Japan)], E-mail: sgs29@cam.ac.uk

    2008-03-15

    We consider the task of intrinsic control system identification for quantum devices. The problem of experimental determination of subspace confinement is considered, and simple general strategies for full Hamiltonian identification and decoherence characterization of a controlled two-level system are presented.

  7. 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.

  8. System risk evolution analysis and risk critical event identification based on event sequence diagram

    International Nuclear Information System (INIS)

    Luo, Pengcheng; Hu, Yang

    2013-01-01

    During system operation, the environmental, operational and usage conditions are time-varying, which causes the fluctuations of the system state variables (SSVs). These fluctuations change the accidents’ probabilities and then result in the system risk evolution (SRE). This inherent relation makes it feasible to realize risk control by monitoring the SSVs in real time, herein, the quantitative analysis of SRE is essential. Besides, some events in the process of SRE are critical to system risk, because they act like the “demarcative points” of safety and accident, and this characteristic makes each of them a key point of risk control. Therefore, analysis of SRE and identification of risk critical events (RCEs) are remarkably meaningful to ensure the system to operate safely. In this context, an event sequence diagram (ESD) based method of SRE analysis and the related Monte Carlo solution are presented; RCE and risk sensitive variable (RSV) are defined, and the corresponding identification methods are also proposed. Finally, the proposed approaches are exemplified with an accident scenario of an aircraft getting into the icing region

  9. Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

    Science.gov (United States)

    2012-12-01

    This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

  10. A knowledge-based approach to identification and adaptation in dynamical systems control

    Science.gov (United States)

    Glass, B. J.; Wong, C. M.

    1988-01-01

    Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

  11. Immunity-based detection, identification, and evaluation of aircraft sub-system failures

    Science.gov (United States)

    Moncayo, Hever Y.

    This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also

  12. Data based identification and prediction of nonlinear and complex dynamical systems

    Science.gov (United States)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

  13. Data based identification and prediction of nonlinear and complex dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

    2016-07-12

    dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

  14. Data based identification and prediction of nonlinear and complex dynamical systems

    International Nuclear Information System (INIS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

  15. Identification for automotive systems

    CERN Document Server

    Hjalmarsson, Håkan; Re, Luigi

    2012-01-01

    Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.

  16. System Identification Based Proxy Model of a Reservoir under Water Injection

    Directory of Open Access Journals (Sweden)

    Berihun M. Negash

    2017-01-01

    Full Text Available Simulation of numerical reservoir models with thousands and millions of grid blocks may consume a significant amount of time and effort, even when high performance processors are used. In cases where the simulation runs are required for sensitivity analysis, dynamic control, and optimization, the act needs to be repeated several times by continuously changing parameters. This makes it even more time-consuming. Currently, proxy models that are based on response surface are being used to lessen the time required for running simulations during sensitivity analysis and optimization. Proxy models are lighter mathematical models that run faster and perform in place of heavier models that require large computations. Nevertheless, to acquire data for modeling and validation and develop the proxy model itself, hundreds of simulation runs are required. In this paper, a system identification based proxy model that requires only a single simulation run and a properly designed excitation signal was proposed and evaluated using a benchmark case study. The results show that, with proper design of excitation signal and proper selection of model structure, system identification based proxy models are found to be practical and efficient alternatives for mimicking the performance of numerical reservoir models. The resulting proxy models have potential applications for dynamic well control and optimization.

  17. Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mar Fuah

    2017-05-01

    Full Text Available One of the problems in the criminal case completions is that the difficulty of making decision to estimate when the settlement of the case file will be fulfilled. It is caused by the number of case files handled and detention time changing. Therefore, the fast and accurate information is needed. The research aims to develop a monitoring system tracking and tracking of scheduling rules using Rule Based Expert Systems method with 17 rules, and supported by Radio Frequency Identification technology (RFID in the form of computer applications. Based on the output of the system, an analysis is performed in the criminal case settlement process with a set of IF-THEN rules. The RFID reader read the data of case files through radio wave signals emitted by the antenna toward active-Tag attached in the criminal case file. The system is designed to monitor the tracking and tracing of RFID-based scheduling rules in realtime way that was built in the form of computer application in accordance with the system design. This study results in no failure in reading active tags by the RFID reader to detect criminal case files that had been examined. There were many case files handled in three different location, they were the constabulary, prosecutor, and judges of district court and RFID was able to identify them simultaneously. So, RFID supports the implementation of Rule Based Expert Systems very much for realtime monitoring in criminal case accomplishment.

  18. 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.

  19. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID

    Directory of Open Access Journals (Sweden)

    Ardhyanti Mita Nugraha Joanna

    2018-01-01

    Full Text Available Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP. This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  20. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID)

    Science.gov (United States)

    Nugraha, Joanna Ardhyanti Mita; Suryono; Suseno, dan Jatmiko Endro

    2018-02-01

    Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID) as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP). This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  1. A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

    Science.gov (United States)

    Liu, Zuolin; Xu, Jian

    2018-04-01

    In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

  2. High-Speed Target Identification System Based on the Plume’s Spectral Distribution

    Directory of Open Access Journals (Sweden)

    Wenjie Lang

    2015-01-01

    Full Text Available In order to recognize the target of high speed quickly and accurately, an identification system was designed based on analysis of the distribution characteristics of the plume spectrum. In the system, the target was aligned with visible light tracking module, and the spectral analysis of the target’s plume radiation was achieved by interference module. The distinguishing factor recognition algorithm was designed on basis of ratio of multifeature band peaks and valley mean values. Effective recognition of the high speed moving target could be achieved after partition of the active region and the influence of target motion on spectral acquisition was analyzed. In the experiment the small rocket combustion was used as the target. The spectral detection experiment was conducted at different speeds 2.0 km away from the detection system. Experimental results showed that spectral distribution had significant spectral offset in the same sampling period for the target with different speeds, but the spectral distribution was basically consistent. Through calculation of the inclusion relationship between distinguishing factor and distinction interval of the peak value and the valley value at the corresponding wave-bands, effective identification of target could be achieved.

  3. Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

    Science.gov (United States)

    Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

    2018-01-01

    Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

  4. Nonparametric identification of nonlinear dynamic systems using a synchronisation-based method

    Science.gov (United States)

    Kenderi, Gábor; Fidlin, Alexander

    2014-12-01

    The present study proposes an identification method for highly nonlinear mechanical systems that does not require a priori knowledge of the underlying nonlinearities to reconstruct arbitrary restoring force surfaces between degrees of freedom. This approach is based on the master-slave synchronisation between a dynamic model of the system as the slave and the real system as the master using measurements of the latter. As the model synchronises to the measurements, it becomes an observer of the real system. The optimal observer algorithm in a least-squares sense is given by the Kalman filter. Using the well-known state augmentation technique, the Kalman filter can be turned into a dual state and parameter estimator to identify parameters of a priori characterised nonlinearities. The paper proposes an extension of this technique towards nonparametric identification. A general system model is introduced by describing the restoring forces as bilateral spring-dampers with time-variant coefficients, which are estimated as augmented states. The estimation procedure is followed by an a posteriori statistical analysis to reconstruct noise-free restoring force characteristics using the estimated states and their estimated variances. Observability is provided using only one measured mechanical quantity per degree of freedom, which makes this approach less demanding in the number of necessary measurement signals compared with truly nonparametric solutions, which typically require displacement, velocity and acceleration signals. Additionally, due to the statistical rigour of the procedure, it successfully addresses signals corrupted by significant measurement noise. In the present paper, the method is described in detail, which is followed by numerical examples of one degree of freedom (1DoF) and 2DoF mechanical systems with strong nonlinearities of vibro-impact type to demonstrate the effectiveness of the proposed technique.

  5. Blind system identification of two-thermocouple sensor based on cross-relation method

    Science.gov (United States)

    Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

    2018-03-01

    In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

  6. Developing a taxonomic identification system of Phytophthora species based on microsatellites.

    Science.gov (United States)

    del Castillo-Múnera, Johanna; Cárdenas, Martha; Pinzón, Andrés; Castañeda, Adriana; Bernal, Adriana J; Restrepo, Silvia

    2013-01-01

    Phytophthora is the most important genus of the Oomycete plant pathogens. Nowadays, there are 117 described species in this genus, most of them being primary invaders of plant tissues. The different species are causal agents of diseases in a wide range of crops and plants in natural environments. In order to develop control strategies against Phytophthoraspecies, it is important to know the biology, ecology and evolutionary processes of these important pathogens. The aim of this study was to propose and validate a low cost identification system for Phytophthora species based on a set of polymorphic microsatellite (SSRs) markers. Thirty-three isolates representing Phytophthora infestans, Phytophthora andina, Phytophthora sojae, Phytophthora cryptogea, Phytophthora nicotianae, Phytophthora capsici and Phytophthora cinnamomi species were obtained, and 13 SSRs were selected as potentially transferable markers between these species. Amplification conditions, including annealing temperatures, were standardized for several markers. A subset of these markers amplified in all species, showing species-specific alleles. The adaptability and impact of the identification system in Colombia, an Andean agricultural country where different Phytophthora species co-exist in the same or in several hosts grown together, are discussed. Copyright © 2012 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.

  7. 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.

  8. Improved Palmprint Identification System

    Directory of Open Access Journals (Sweden)

    Harshala C. Salave

    2015-03-01

    Full Text Available Abstract Generally private information is provided by using passwords or Personal Identification Numbers which is easy to implement but it is very easily stolen or forgotten or hack. In Biometrics for individuals identification uses human physiological which are constant throughout life like palm face DNA iris etc. or behavioral characteristicswhich is not constant in life like voice signature keystroke etc.. But mostly gain more attention to palmprint identification and is becoming more popular technique using for identification and promising alternatives to the traditional password or PIN based authentication techniques. In this paper propose palmprint identification using veins on the palm and fingers. Here use fusion of techniques such as Discrete Wavelet transformDWT Canny Edge Detector Gaussian Filter Principle Component AnalysisPCA.

  9. 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

  10. Time-domain modeling for shielding effectiveness of materials against electromagnetic pulse based on system identification

    International Nuclear Information System (INIS)

    Chen, Xiang; Chen, Yong Guang; Wei, Ming; Hu, Xiao Feng

    2013-01-01

    Shielding effectiveness (SE) of materials against electromagnetic pulse (EMP) cannot be well estimated by traditional test method of SE of materials which only consider the amplitude-frequency characteristic of materials, but ignore the phase-frequency ones. In order to solve this problem, the model of SE of materials against EMP was established based on system identification (SI) method with time-domain linear cosine frequency sweep signal. The feasibility of the method in this paper was examined depending on infinite planar material and the simulation research of coaxial test method and windowed semi-anechoic box of materials. The results show that the amplitude-frequency and phase-frequency information of each frequency can be fully extracted with this method. SE of materials against strong EMP can be evaluated with time-domain low field strength (voltage) of cosine frequency sweep signal. And SE of materials against a variety EMP will be predicted by the model.

  11. Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation

    Directory of Open Access Journals (Sweden)

    Leopoldo Rodriguez Salazar

    2016-12-01

    Full Text Available This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS. The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain, was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz

  12. Study on the knowledge base system for the identification of typical target

    International Nuclear Information System (INIS)

    Qin Kai; Zhao Yingjun

    2008-01-01

    Based on the research on target knowledge base, target database, texture analysis, shape analysis, this paper proposed a new knowledge based method for typical target identification from remote sensing image. By extracting the texture characters and shape characters, joining with spatial analysis in GIS, reasoning according to the prior knowledge in the knowledge base, this method can identify and ex- tract typical target from remote sensing images. (authors)

  13. Frequency response function-based explicit framework for dynamic identification in human-structure systems

    Science.gov (United States)

    Wei, Xiaojun; Živanović, Stana

    2018-05-01

    The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

  14. Nonlinear system identification based on Takagi-Sugeno fuzzy modeling and unscented Kalman filter.

    Science.gov (United States)

    Vafamand, Navid; Arefi, Mohammad Mehdi; Khayatian, Alireza

    2018-03-01

    This paper proposes two novel Kalman-based learning algorithms for an online Takagi-Sugeno (TS) fuzzy model identification. The proposed approaches are designed based on the unscented Kalman filter (UKF) and the concept of dual estimation. Contrary to the extended Kalman filter (EKF) which utilizes derivatives of nonlinear functions, the UKF employs the unscented transformation. Consequently, non-differentiable membership functions can be considered in the structure of the TS models. This makes the proposed algorithms to be applicable for the online parameter calculation of wider classes of TS models compared to the recently published papers concerning the same issue. Furthermore, because of the great capability of the UKF in handling severe nonlinear dynamics, the proposed approaches can effectively approximate the nonlinear systems. Finally, numerical and practical examples are provided to show the advantages of the proposed approaches. Simulation results reveal the effectiveness of the proposed methods and performance improvement based on the root mean square (RMS) of the estimation error compared to the existing results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Feasibility Study on Tension Estimation Technique for Hanger Cables Using the FE Model-Based System Identification Method

    Directory of Open Access Journals (Sweden)

    Kyu-Sik Park

    2015-01-01

    Full Text Available Hanger cables in suspension bridges are partly constrained by horizontal clamps. So, existing tension estimation methods based on a single cable model are prone to higher errors as the cable gets shorter, making it more sensitive to flexural rigidity. Therefore, inverse analysis and system identification methods based on finite element models are suggested recently. In this paper, the applicability of system identification methods is investigated using the hanger cables of Gwang-An bridge. The test results show that the inverse analysis and systemic identification methods based on finite element models are more reliable than the existing string theory and linear regression method for calculating the tension in terms of natural frequency errors. However, the estimation error of tension can be varied according to the accuracy of finite element model in model based methods. In particular, the boundary conditions affect the results more profoundly when the cable gets shorter. Therefore, it is important to identify the boundary conditions through experiment if it is possible. The FE model-based tension estimation method using system identification method can take various boundary conditions into account. Also, since it is not sensitive to the number of natural frequency inputs, the availability of this system is high.

  16. A Portable, Air-Jet-Actuator-Based Device for System Identification

    Science.gov (United States)

    Staats, Wayne; Belden, Jesse; Mazumdar, Anirban; Hunter, Ian

    2010-11-01

    System identification (ID) of human and robotic limbs could help in diagnosis of ailments and aid in optimization of control parameters and future redesigns. We present a self-contained actuator, which uses the Coanda effect to rapidly switch the direction of a high speed air jet to create a binary stochastic force input to a limb for system ID. The design of the actuator is approached with the goal of creating a portable device, which could deployed on robot or human limbs for in situ identification. The viability of the device is demonstrated by performing stochastic system ID on an underdamped elastic beam system with fixed inertia and stiffness, and variable damping. The non-parametric impulse response yielded from the stochastic system ID is modeled as a second order system, and the resultant parameters are found to be in excellent agreement with those found using more traditional system ID techniques. The current design could be further miniaturized and developed as a portable, wireless, on-site multi-axis system identification system for less intrusive and more widespread use.

  17. Chaotic System Identification Based on a Fuzzy Wiener Model with Particle Swarm Optimization

    International Nuclear Information System (INIS)

    Yong, Li; Ying-Gan, Tang

    2010-01-01

    A fuzzy Wiener model is proposed to identify chaotic systems. The proposed fuzzy Wiener model consists of two parts, one is a linear dynamic subsystem and the other is a static nonlinear part, which is represented by the Takagi–Sugeno fuzzy model. Identification of chaotic systems is converted to find optimal parameters of the fuzzy Wiener model by minimizing the state error between the original chaotic system and the fuzzy Wiener model. Particle swarm optimization algorithm, a global optimizer, is used to search the optimal parameter of the fuzzy Wiener model. The proposed method can identify the parameters of the linear part and nonlinear part simultaneously. Numerical simulations for Henón and Lozi chaotic system identification show the effectiveness of the proposed method

  18. Design and Implementation of Mobile Learning System for Soldiers’ Vocational Skill Identification Based on Android

    Science.gov (United States)

    Ma, Jinqiang

    2017-09-01

    To carry out the identification of the professional skills of the soldiers is to further promote the regularization of the needs of the fire brigade, in accordance with the “public security active forces soldiers professional skills identification implementation approach” to meet the needs of candidates for mobile learning to solve the paper learning materials bring a lot of inconvenience; This article uses the Android technology to develop a set of soldiers professional skills Identification Theory learning app, the learning software based on mobile learning, learning function is perfect, you can learn to practice, to achieve the goal of learning at any time, to enhance the soldier's post ability has a good practical value.

  19. Roadway System Assessment Using Bluetooth-Based Automatic Vehicle Identification Travel Time Data

    OpenAIRE

    Day, Christopher M.; Brennan, Thomas M.; Hainen, Alexander M.; Remias, Stephen M.; Bullock, Darcy M.

    2012-01-01

    This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection systems. This includes considerations in the physical setup of the collection system as well as the interpretation of the data. An extended discussion is provided, with examples, demonstrating data techniques for converting the raw data into more concise metrics and views. Examples of statistical before-after tests are also provided. A series of case studies were ...

  20. A kernel-based approach to MIMO LPV state-space identification and application to a nonlinear process system

    NARCIS (Netherlands)

    Rizvi, S.Z.; Mohammadpour, J.; Toth, R.; Meskin, N.

    2015-01-01

    This paper first describes the development of a nonparametric identification method for linear parameter-varying (LPV) state-space models and then applies it to a nonlinear process system. The proposed method uses kernel-based least-squares support vector machines (LS-SVM). While parametric

  1. StakeMeter: value-based stakeholder identification and quantification framework for value-based software systems.

    Science.gov (United States)

    Babar, Muhammad Imran; Ghazali, Masitah; Jawawi, Dayang N A; Bin Zaheer, Kashif

    2015-01-01

    Value-based requirements engineering plays a vital role in the development of value-based software (VBS). Stakeholders are the key players in the requirements engineering process, and the selection of critical stakeholders for the VBS systems is highly desirable. Based on the stakeholder requirements, the innovative or value-based idea is realized. The quality of the VBS system is associated with the concrete set of valuable requirements, and the valuable requirements can only be obtained if all the relevant valuable stakeholders participate in the requirements elicitation phase. The existing value-based approaches focus on the design of the VBS systems. However, the focus on the valuable stakeholders and requirements is inadequate. The current stakeholder identification and quantification (SIQ) approaches are neither state-of-the-art nor systematic for the VBS systems. The existing approaches are time-consuming, complex and inconsistent which makes the initiation process difficult. Moreover, the main motivation of this research is that the existing SIQ approaches do not provide the low level implementation details for SIQ initiation and stakeholder metrics for quantification. Hence, keeping in view the existing SIQ problems, this research contributes in the form of a new SIQ framework called 'StakeMeter'. The StakeMeter framework is verified and validated through case studies. The proposed framework provides low-level implementation guidelines, attributes, metrics, quantification criteria and application procedure as compared to the other methods. The proposed framework solves the issues of stakeholder quantification or prioritization, higher time consumption, complexity, and process initiation. The framework helps in the selection of highly critical stakeholders for the VBS systems with less judgmental error.

  2. StakeMeter: value-based stakeholder identification and quantification framework for value-based software systems.

    Directory of Open Access Journals (Sweden)

    Muhammad Imran Babar

    Full Text Available Value-based requirements engineering plays a vital role in the development of value-based software (VBS. Stakeholders are the key players in the requirements engineering process, and the selection of critical stakeholders for the VBS systems is highly desirable. Based on the stakeholder requirements, the innovative or value-based idea is realized. The quality of the VBS system is associated with the concrete set of valuable requirements, and the valuable requirements can only be obtained if all the relevant valuable stakeholders participate in the requirements elicitation phase. The existing value-based approaches focus on the design of the VBS systems. However, the focus on the valuable stakeholders and requirements is inadequate. The current stakeholder identification and quantification (SIQ approaches are neither state-of-the-art nor systematic for the VBS systems. The existing approaches are time-consuming, complex and inconsistent which makes the initiation process difficult. Moreover, the main motivation of this research is that the existing SIQ approaches do not provide the low level implementation details for SIQ initiation and stakeholder metrics for quantification. Hence, keeping in view the existing SIQ problems, this research contributes in the form of a new SIQ framework called 'StakeMeter'. The StakeMeter framework is verified and validated through case studies. The proposed framework provides low-level implementation guidelines, attributes, metrics, quantification criteria and application procedure as compared to the other methods. The proposed framework solves the issues of stakeholder quantification or prioritization, higher time consumption, complexity, and process initiation. The framework helps in the selection of highly critical stakeholders for the VBS systems with less judgmental error.

  3. StakeMeter: Value-Based Stakeholder Identification and Quantification Framework for Value-Based Software Systems

    Science.gov (United States)

    Babar, Muhammad Imran; Ghazali, Masitah; Jawawi, Dayang N. A.; Zaheer, Kashif Bin

    2015-01-01

    Value-based requirements engineering plays a vital role in the development of value-based software (VBS). Stakeholders are the key players in the requirements engineering process, and the selection of critical stakeholders for the VBS systems is highly desirable. Based on the stakeholder requirements, the innovative or value-based idea is realized. The quality of the VBS system is associated with the concrete set of valuable requirements, and the valuable requirements can only be obtained if all the relevant valuable stakeholders participate in the requirements elicitation phase. The existing value-based approaches focus on the design of the VBS systems. However, the focus on the valuable stakeholders and requirements is inadequate. The current stakeholder identification and quantification (SIQ) approaches are neither state-of-the-art nor systematic for the VBS systems. The existing approaches are time-consuming, complex and inconsistent which makes the initiation process difficult. Moreover, the main motivation of this research is that the existing SIQ approaches do not provide the low level implementation details for SIQ initiation and stakeholder metrics for quantification. Hence, keeping in view the existing SIQ problems, this research contributes in the form of a new SIQ framework called ‘StakeMeter’. The StakeMeter framework is verified and validated through case studies. The proposed framework provides low-level implementation guidelines, attributes, metrics, quantification criteria and application procedure as compared to the other methods. The proposed framework solves the issues of stakeholder quantification or prioritization, higher time consumption, complexity, and process initiation. The framework helps in the selection of highly critical stakeholders for the VBS systems with less judgmental error. PMID:25799490

  4. Identification of Hidden Failures in Process Control Systems Based on the HMG Method

    DEFF Research Database (Denmark)

    Jalashgar, Atoosa

    1998-01-01

    cause the systems to become overloaded and even unstable, if they remain hidden. The method uses a particular terminology to contribute to the identification of system properties, including goals, functions, and the capabilities. All identified knowledge about the system is then represented by using...... a tailored combination of two function-oriented methods, Multilevel Flow Modelling (MFM) and Goal Tree-Success Tree (GTST). The features of the method, called Hybrid MFM-GTST, are described and demonstrated by using an example of a process control system. (C) 1998 John Wiley & Sons, Inc....

  5. Model-based identification and use of task complexity factors of human integrated systems

    International Nuclear Information System (INIS)

    Ham, Dong-Han; Park, Jinkyun; Jung, Wondea

    2012-01-01

    Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.

  6. Using systems approach to build education process based on technologies of interactive support and students identification

    Directory of Open Access Journals (Sweden)

    Alexey I. Komarov

    2017-12-01

    Full Text Available In the article systems approach to build educational complex with using IT and didactic methods is discussed. Technologies for each level of educational system are determined. Such kind of system supports interactivity and dual-identification (teaching materials – students due to systems approach offered by authors and optimizes reaching of educational goalsIn the article systems approach to build educational complex with using IT and didactic methods is discussed. Technologies for each level of educational system are determined. Such kind of system supports interactivity and dual-identification (teaching materials – students due to systems approach offered by authors and optimizes reaching of educational goals. Different combinations of technologies are possible to use depending on education form, but main idea of systematic data processing remains unchanged. One of the main contentions of this research consists in the possibility to use the learning time as criterion of student preparedness and quality of training material. Time analysis is important part of whole system which is designed to increase the efficiency of the learning process.

  7. A Robust Iris Identification System Based on Wavelet Packet Decomposition and Local Comparisons of the Extracted Signatures

    Directory of Open Access Journals (Sweden)

    Rossant Florence

    2010-01-01

    Full Text Available Abstract This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based on the fusion of local distance measures, are proposed. Performance measurements validating the proposed iris signature and demonstrating the benefit of our local-based signature comparison are provided. Moreover, an exhaustive evaluation of robustness, with regards to the acquisition conditions, attests the high performances and the reliability of our system. Tests have been conducted on two different databases, the well-known CASIA database (V3 and our ISEP database. Finally, a comparison of the performances of our system with the published ones is given and discussed.

  8. 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

  9. 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.

  10. Rule Based Expert System for Monitoring Real Time Drug Supply in Hospital Using Radio Frequency Identification Technology

    Science.gov (United States)

    Driandanu, Galih; Surarso, Bayu; Suryono

    2018-02-01

    A radio frequency identification (RFID) has obtained increasing attention with the emergence of various applications. This study aims to examine the implementation of rule based expert system supported by RFID technology into a monitoring information system of drug supply in a hospital. This research facilitates in monitoring the real time drug supply by using data sample from the hospital pharmacy. This system able to identify and count the number of drug and provide warning and report in real time. the conclusion is the rule based expert system and RFID technology can facilitate the performance in monitoring the drug supply quickly and precisely.

  11. Design of the TORCH detector: A Cherenkov based Time-of-Flight system for particle identification

    CERN Document Server

    AUTHOR|(CDS)2078663; Rademacker, Jonas

    The LHCb detector at the LHC collider has been very successfully operated over the past years, providing new and profound insights into the Standard Model, in particular through study of $b$-hadrons to achieve a better understanding of CP violation. One of the key components of LHCb is its particle identification system, comprised of two RICH detectors, which allow for high precision separation of particle species over a large momentum range. In order to retain and improve the performance of the particle identification system in light of the LHCb upgrade, the TORCH detector has been proposed to supplement the RICH system at low momentum (2-10 GeV/c). The TORCH detector provides (charged) particle identification through precision timing of particles passing through it. Assuming a known momentum from the tracking, it is possible to derive the species of a particle from the time of flight from its primary vertex. This measurement is achieved by timing and combining photons generated in a solid radiator. The geom...

  12. Identification and Damage Detection on Structural Systems

    DEFF Research Database (Denmark)

    Brincker, Rune; Kirkegaard, Poul Henning; Andersen, Palle

    1994-01-01

    A short introduction is given to system identification and damage assessment in civil engineering structures. The most commonly used FFT-based techniques for system identification are mentioned, and the Random decrement technique and parametric methods based on ARMA models are introduced. Speed...

  13. A bimodal biometric identification system

    Science.gov (United States)

    Laghari, Mohammad S.; Khuwaja, Gulzar A.

    2013-03-01

    Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

  14. Molecular-Based Identification and Detection of Salmonella in Food Production Systems: Current Perspectives.

    Science.gov (United States)

    Ricke, Steven C; Kim, Sun Ae; Shi, Zhaohao; Park, Si Hong

    2018-04-19

    Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies has greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  15. Embedded System for Biometric Identification

    OpenAIRE

    Rosli, Ahmad Nasir Che

    2010-01-01

    This chapter describes the design and implementation of an Embedded System for Biometric Identification from hardware and software perspectives. The first part of the chapter describes the idea of biometric identification. This includes the definition of

  16. Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Hyungchul Yoon

    2017-09-01

    Full Text Available Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc. are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1 estimation of an appropriate scale factor; and (2 compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

  17. Identification of eggs from different production systems based on hyperspectra and CS-SVM.

    Science.gov (United States)

    Sun, J; Cong, S L; Mao, H P; Zhou, X; Wu, X H; Zhang, X D

    2017-06-01

    1. To identify the origin of table eggs more accurately, a method based on hyperspectral imaging technology was studied. 2. The hyperspectral data of 200 samples of intensive and extensive eggs were collected. Standard normalised variables combined with a Savitzky-Golay were used to eliminate noise, then stepwise regression (SWR) was used for feature selection. Grid search algorithm (GS), genetic search algorithm (GA), particle swarm optimisation algorithm (PSO) and cuckoo search algorithm (CS) were applied by support vector machine (SVM) methods to establish an SVM identification model with the optimal parameters. The full spectrum data and the data after feature selection were the input of the model, while egg category was the output. 3. The SWR-CS-SVM model performed better than the other models, including SWR-GS-SVM, SWR-GA-SVM, SWR-PSO-SVM and others based on full spectral data. The training and test classification accuracy of the SWR-CS-SVM model were respectively 99.3% and 96%. 4. SWR-CS-SVM proved effective for identifying egg varieties and could also be useful for the non-destructive identification of other types of egg.

  18. Power system low frequency oscillation monitoring and analysis based on multi-signal online identification

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The advance in the wide-area measurement system (WAMS) is driving the power system to the trend of wide-area monitoring and control.The Prony method is usually used for low frequency oscillation online identification.However,the identified amplitude and phase information is not sufficiently used.In this paper,the amplitude is adopted to detect the occurrence of the oscillation and to obtain the mode observability of the sites.The phase is adopted to identify the oscillation generator grouping and to obtain the mode shapes.The time varying characteristics of low frequency oscillations are studied.The behaviors and the characters of low frequency oscillations are displayed by dynamic visual techniques.Demonstrations on the "11.9" low frequency oscillation of the Guizhou Power Grid substantiate the feasibility and the validation of the proposed methods.

  19. Nonlinear Damping Identification in Nonlinear Dynamic System Based on Stochastic Inverse Approach

    Directory of Open Access Journals (Sweden)

    S. L. Han

    2012-01-01

    Full Text Available The nonlinear model is crucial to prepare, supervise, and analyze mechanical system. In this paper, a new nonparametric and output-only identification procedure for nonlinear damping is studied. By introducing the concept of the stochastic state space, we formulate a stochastic inverse problem for a nonlinear damping. The solution of the stochastic inverse problem is designed as probabilistic expression via the hierarchical Bayesian formulation by considering various uncertainties such as the information insufficiency in parameter of interests or errors in measurement. The probability space is estimated using Markov chain Monte Carlo (MCMC. The applicability of the proposed method is demonstrated through numerical experiment and particular application to a realistic problem related to ship roll motion.

  20. CBDS: Constraint-based diagnostic system for malfunction identification in the nuclear power plant

    International Nuclear Information System (INIS)

    Ha, J.

    1992-01-01

    Traditional rule-based diagnostic expert systems use the experience of experts in the form of rules that associate symptoms with underlying faults. A commonly recognized failing of such systems is their narrow range of expertise and their inability to recognize problems outside this range of expertise. A model base diagnostic system isolating malfunctioning components-CBDS, the Constraint based Diagnostic System-has been developed. Since the intended behavior of a device is more predictable than unintended behaviors (faults), a model based system using the intended behavior has a potential to diagnose unexpected malfunctions by considering faults as open-quotes anything other than the intended behavior.close quotes As a knowledge base, the CBDS generates and decomposes a constraint network based on the structure and behavior model, which are represented symbolically in algebraic equations. Behaviors of generic components are organized in a component model library. Once the library is available, actual domain knowledge can be represented by declaring component types and their connections. To capture various plant knowledge, the mixed model was developed which allow the use of different parameter types in one equation by defining various operators. The CBDS uses the general idea of model based diagnosis. It detects a discrepancy between observation and prediction using constraint propagation, which carriers and accumulates the assumptions when parameter values are deduced. When measured plant parameters are asserted into a constraint network and are propagated through the network, a discrepancy will be detected if there exists any malfunctioning component. The CBDS was tested in the Recirculation Flow Control System of a BWR, and has been shown to be able to diagnose unexpected events

  1. Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing.

    Directory of Open Access Journals (Sweden)

    Chunyan Wu

    Full Text Available This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1 Distinguishing effects of BP (Back Propagation neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2 The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3 Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees.

  2. Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing.

    Science.gov (United States)

    Wu, Chunyan; Wang, Xuefeng

    2017-01-01

    This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees.

  3. Risk Identification in a Smart Monitoring System Used to Preserve Artefacts Based on Textile Materials

    Science.gov (United States)

    Diaconescu, V. D.; Scripcariu, L.; Mătăsaru, P. D.; Diaconescu, M. R.; Ignat, C. A.

    2018-06-01

    Exhibited textile-materials-based artefacts can be affected by the environmental conditions. A smart monitoring system that commands an adaptive automatic environment control system is proposed for indoor exhibition spaces containing various textile artefacts. All exhibited objects are monitored by many multi-sensor nodes containing temperature, relative humidity and light sensors. Data collected periodically from the entire sensor network is stored in a database and statistically processed in order to identify and classify the environment risk. Risk consequences are analyzed depending on the risk class and the smart system commands different control measures in order to stabilize the indoor environment conditions to the recommended values and prevent material degradation.

  4. A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification

    Directory of Open Access Journals (Sweden)

    Shousong Han

    2017-01-01

    Full Text Available The riding conditions for a high-speed tracked vehicle are quite complex. To enhance the adaptability of suspension systems to different riding conditions, a semiactive and self-adaptive hybrid control strategy based on disturbance velocity and frequency identification was proposed. A mathematical model of the semiactive, self-adaptive hybrid suspension control system, along with a performance evaluation function, was established. Based on a two-degree-of-freedom (DOF suspension system, the kinematic relations and frequency zero-crossing detection method were defined, and expressions for the disturbance velocity and disturbance frequency of the road were obtained. Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid and self-adaptive control gain (cv under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. An experimental study using a carefully designed test rig was performed under a number of typical riding conditions of tracked vehicles, and the results showed that the proposed control strategy is capable of accurately recognizing different disturbances, shifting between control modes (semiactive/self-adaptive, and scheduling the damping control gain according to the disturbance identification outcomes; hence, the proposed strategy could achieve a good trade-off between ride comfort and ride safety and efficiently increase the overall performance of the suspension under various riding conditions.

  5. Identification of Characterization Factor for Power System Oscillation Based on Multiple Synchronized Phasor Measurements

    Science.gov (United States)

    Hashiguchi, Takuhei; Watanabe, Masayuki; Matsushita, Akihiro; Mitani, Yasunori; Saeki, Osamu; Tsuji, Kiichiro; Hojo, Masahide; Ukai, Hiroyuki

    Electric power systems in Japan are composed of remote and distributed location of generators and loads mainly concentrated in large demand areas. The structures having long distance transmission tend to produce heavy power flow with increasing electric power demand. In addition, some independent power producers (IPP) and power producer and suppliers (PPS) are participating in the power generation business, which makes power system dynamics more complex. However, there was little observation as a whole power system. In this paper the authors present a global monitoring system of power system dynamics by using the synchronized phasor measurement of demand side outlets. Phasor Measurement Units (PMU) are synchronized based on the global positioning system (GPS). The purpose of this paper is to show oscillation characteristics and methods for processing original data obtained from PMU after certain power system disturbances triggered by some accidents. This analysis resulted in the observation of the lowest and the second lowest frequency mode. The derivation of eigenvalue with two degree of freedom model brings a monitoring of two oscillation modes. Signal processing based on Wavelet analysis and simulation studies to illustrate the obtained phenomena are demonstrated in detail.

  6. System Identification with Quantized Observations

    CERN Document Server

    Wang, Le Yi; Zhang, Jifeng; Zhao, Yanlong

    2010-01-01

    This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed. Providing a comprehensive coverage of quantized identification,

  7. Omega version 2.2: Rule-based deterioration identification and management system. Final report

    International Nuclear Information System (INIS)

    Kataoka, S.; Kojima, T.; Pavinich, W.A.; Andrews, J.D.

    1996-06-01

    This report presents the Omega Version 2.2 (Ωs) rule-based computer program for identifying material deteriorations in the metallic structures, systems and components of LWR nuclear power units. The basis of Us is that understanding what material deteriorations might occur as a function of service life is fundamental to: (1) the development and optimization of preventive maintenance programs, (2) ensuring that current maintenance programs recognize applicable degradations, and (3) demonstrating the adequacy of deterioration management to safety regulatory authorities. The system was developed to assist utility engineers in determining which aging degradation mechanisms are acting on specific components. Direction is also provided to extend this system to manage deterioration and evaluate the efficacy of existing age-related degradation mitigation programs. This system can provide support for justification for continued operation and license renewal. It provides traceability to the data sources used in the logic development. A tiered approach is used to quickly isolate potential age-related degradation for components in a particular location. A potential degradation mechanism is then screened by additional rules to establish its plausibility. Ωs includes a user-friendly system interface and provides default environmental data and materials in the event they are unknown to the user. Ωs produces a report, with references, that validates the elimination of a degradation mechanism from further consideration or the determination that a specific degradation mechanism is acting on a specific material. This report also describes logic for identifying deterioration caused by intrusions and inspection-based deteriorations, along with future plans to program and integrate these features with Ωs

  8. Cloth-based hybridization array system for expanded identification of the animal species origin of derived materials in feeds.

    Science.gov (United States)

    Murphy, Johanna; Armour, Jennifer; Blais, Burton W

    2007-12-01

    A cloth-based hybridization array system (CHAS) previously developed for the detection of animal species for which prohibited materials have been specified (cattle, sheep, goat, elk, and deer) has been expanded to include the detection of animal species for which there are no prohibitions (pig and horse) in Canadian and American animal feeds. Animal species were identified by amplification of mitochondrial DNA sequences by PCR and subsequent hybridization of the amplicons with an array of species-specific oligonucleotide capture probes immobilized on a polyester cloth support, followed by an immunoenzymatic assay of the bound PCR products. The CHAS permitted sensitive and specific detection of meat meals from different animal species blended in a grain-based feed and should provide a useful adjunct to microscopic examination for the identification of prohibited materials in animal feeds.

  9. A Web-based patient information system--identification of patients' information needs.

    Science.gov (United States)

    Hassling, Linda; Babic, Ankica; Lönn, Urban; Casimir-Ahn, Henrik

    2003-06-01

    Research described here was carried out to explore possibilities of creating a web-based patient information system within the areas of thoracic surgery. Data were collected to distinguish and assess the actual information needs of patients (1) prior to surgical treatment, (2) before discharge, and (3) 8 months after the hospitalization using a follow-up questionnaire. Interviews were performed with patients undergoing heart surgery. The study included material of 19 consecutive patients undergoing coronary artery bypass surgery (12) and valve replacement (7), age 35-74, 13 males and 6 females with nonacademic background. Patient satisfaction with given information was high. Analysis of the interviews held at the hospital resulted in seven different categories describing and giving a picture of the patients' information needs and apprehension of received care. The results found in this study can be used as guidance for developers in their design and development process of a health information system.

  10. Action-reaction based parameters identification and states estimation of flexible systems

    OpenAIRE

    Khalil, Islam; Kunt, Emrah Deniz; Şabanoviç, Asif; Sabanovic, Asif

    2012-01-01

    This work attempts to identify and estimate flexible system's parameters and states by a simple utilization of the Action-Reaction law of dynamical systems. Attached actuator to a dynamical system or environmental interaction imposes an action that is instantaneously followed by a dynamical system reaction. The dynamical system's reaction carries full information about the dynamical system including system parameters, dynamics and externally applied forces that arise due to system interaction...

  11. Cost Optimal System Identification Experiment Design

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning

    A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...

  12. Identification of potent orally active factor Xa inhibitors based on conjugation strategy and application of predictable fragment recommender system.

    Science.gov (United States)

    Ishihara, Tsukasa; Koga, Yuji; Iwatsuki, Yoshiyuki; Hirayama, Fukushi

    2015-01-15

    Anticoagulant agents have emerged as a promising class of therapeutic drugs for the treatment and prevention of arterial and venous thrombosis. We investigated a series of novel orally active factor Xa inhibitors designed using our previously reported conjugation strategy to boost oral anticoagulant effect. Structural optimization of anthranilamide derivative 3 as a lead compound with installation of phenolic hydroxyl group and extensive exploration of the P1 binding element led to the identification of 5-chloro-N-(5-chloro-2-pyridyl)-3-hydroxy-2-{[4-(4-methyl-1,4-diazepan-1-yl)benzoyl]amino}benzamide (33, AS1468240) as a potent factor Xa inhibitor with significant oral anticoagulant activity. We also reported a newly developed Free-Wilson-like fragment recommender system based on the integration of R-group decomposition with collaborative filtering for the structural optimization process. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Action-reaction based parameters identification and states estimation of flexible systems

    OpenAIRE

    Khalil, Islam Shoukry Mohammed; Şabanoviç, Asif; Sabanovic, Asif

    2010-01-01

    This work attempts to identify and estimate flexible system’s parameters and states by a simple utilization of the Action-Reaction law of dynamical systems. Attached actuator to a dynamical system or environmental interaction imposes an action that is instantaneously followed by a dynamical system reaction. The dynamical system’s reaction carries full information about the dynamical system including system parameters, dynamics and externally applied forces that arise due to system interaction...

  14. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles

    Science.gov (United States)

    Grymin, David J.

    . Simulations in a realistic operational environment as well as flight testing with the feedback controller demonstrate the capabilities of the approach. The TSM is also applied for system identification of an aircraft using motion capture data. In this application, time domain system identification techniques are used to identify both linear and nonlinear aerodynamic models of large-amplitude pitching motions driven by control surface deflections. The resulting models are assessed based on both their predictive capabilities as well as simulation results.

  15. Identifications and Monitoring of Power System Dynamics Based on the PMUs and Wavelet Technique

    OpenAIRE

    Samir Avdakovic; Amir Nuhanovic

    2010-01-01

    Low frequency power oscillations may be triggered by many events in the system. Most oscillations are damped by the system, but undamped oscillations can lead to system collapse. Oscillations develop as a result of rotor acceleration/deceleration following a change in active power transfer from a generator. Like the operations limits, the monitoring of power system oscillating modes is a relevant aspect of power system operation and control. Unprevented low-frequency powe...

  16. Identification and molecular epidemiology of dermatophyte isolates by repetitive-sequence-PCR-based DNA fingerprinting using the DiversiLab system in Turkey.

    Science.gov (United States)

    Koc, A Nedret; Atalay, Mustafa A; Inci, Melek; Sariguzel, Fatma M; Sav, Hafize

    2017-05-01

    Dermatophyte species, isolation and identification in clinical samples are still difficult and take a long time. The identification and molecular epidemiology of dermatophytes commonly isolated in a clinical laboratory in Turkey by repetitive sequence-based PCR (rep-PCR) were assessed by comparing the results with those of reference identification. A total of 44 dermatophytes isolated from various clinical specimens of 20 patients with superficial mycoses in Kayseri and 24 patients in Hatay were studied. The identification of dermatophyte isolates was based on the reference identification and rep-PCR using the DiversiLab System (BioMerieux). The genotyping of dermatophyte isolates from different patients was determined by rep-PCR. In the identification of dermatophyte isolates, agreement between rep-PCR and conventional methods was 87.8 % ( 36 of 41). The dermatophyte strains belonged to four clones (A -D) which were determined by the use of rep-PCR. The dermatophyte strains in Clone B, D showed identical patterns with respect to the region. In conclusion, rep-PCR appears to be useful for evaluation of the identification and clonal relationships between Trichophyton rubrum species complex and Trichophyton mentagrophytes species complex isolates. The similarity and diversity of these isolates may be assessed according to different regions by rep-PCR. © 2017 Blackwell Verlag GmbH.

  17. General hybrid projective complete dislocated synchronization with non-derivative and derivative coupling based on parameter identification in several chaotic and hyperchaotic systems

    International Nuclear Information System (INIS)

    Sun Jun-Wei; Shen Yi; Zhang Guo-Dong; Wang Yan-Feng; Cui Guang-Zhao

    2013-01-01

    According to the Lyapunov stability theorem, a new general hybrid projective complete dislocated synchronization scheme with non-derivative and derivative coupling based on parameter identification is proposed under the framework of drive-response systems. Every state variable of the response system equals the summation of the hybrid drive systems in the previous hybrid synchronization. However, every state variable of the drive system equals the summation of the hybrid response systems while evolving with time in our method. Complete synchronization, hybrid dislocated synchronization, projective synchronization, non-derivative and derivative coupling, and parameter identification are included as its special item. The Lorenz chaotic system, Rössler chaotic system, memristor chaotic oscillator system, and hyperchaotic Lü system are discussed to show the effectiveness of the proposed methods. (general)

  18. Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification

    NARCIS (Netherlands)

    Sun, L.G.

    2014-01-01

    Consensus exists that many loss-of-control (LOC) in flight accidents caused by severe aircraft damage or system failure could be prevented if flight performance could be recovered using the valid and remaining control authorities. However, the safe maneuverability of a post-failure aircraft will

  19. Architecturally Significant Requirements Identification, Classification and Change Management for Multi-tenant Cloud-Based Systems

    DEFF Research Database (Denmark)

    Chauhan, Muhammad Aufeef; Probst, Christian W.

    2017-01-01

    presented a framework for requirements classification and change management focusing on distributed Platform as a Service (PaaS) and Software as a Service (SaaS) systems as well as complex software ecosystems that are built using PaaS and SaaS, such as Tools as a Service (TaaS). We have demonstrated...

  20. Controller Reconfiguration through Terminal Connections  based on Closed-loop System Identification

    DEFF Research Database (Denmark)

    Trangbæk, K

    2009-01-01

     Often, when a controlled plant is modified, e.g. if a new sensor or  actuator becomes available, it is desirable to retain the existing  controllers and apply the new control capabilities in a gradual,  online fashion rather than decommissioning the entire existing system  and replacing it with ...

  1. A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

    Science.gov (United States)

    Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

    This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

  2. FLOOR IDENTIFICATION WITH COMMERCIAL SMARTPHONES IN WIFI-BASED INDOOR LOCALIZATION SYSTEM

    Directory of Open Access Journals (Sweden)

    H. J. Ai

    2016-06-01

    Full Text Available In this paper, we utilize novel sensors built-in commercial smart devices to propose a schema which can identify floors with high accuracy and efficiency. This schema can be divided into two modules: floor identifying and floor change detection. Floor identifying module starts at initial phase of positioning, and responsible for determining which floor the positioning start. We have estimated two methods to identify initial floor based on K-Nearest Neighbors (KNN and BP Neural Network, respectively. In order to improve performance of KNN algorithm, we proposed a novel method based on weighting signal strength, which can identify floors robust and quickly. Floor change detection module turns on after entering into continues positioning procedure. In this module, sensors (such as accelerometer and barometer of smart devices are used to determine whether the user is going up and down stairs or taking an elevator. This method has fused different kinds of sensor data and can adapt various motion pattern of users. We conduct our experiment with mobile client on Android Phone (Nexus 5 at a four-floors building with an open area between the second and third floor. The results demonstrate that our scheme can achieve an accuracy of 99% to identify floor and 97% to detecting floor changes as a whole.

  3. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

    Science.gov (United States)

    Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

    2016-07-01

    Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  4. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

    Directory of Open Access Journals (Sweden)

    Young-Jin Cha

    2016-07-01

    Full Text Available Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA, was characterized and modeled as a simplified lumped-mass beam model (SLMM, using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA. Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  5. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

    Science.gov (United States)

    Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

    2016-01-01

    Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. PMID:27376303

  6. A Phytase-Based Reporter System for Identification of Functional Secretion Signals in Bifidobacteria.

    Directory of Open Access Journals (Sweden)

    Annika Osswald

    Full Text Available Health-promoting effects have been attributed to a number of Bifidobacterium sp. strains. These effects as well as the ability to colonise the host depend on secreted proteins. Moreover, rational design of protein secretion systems bears the potential for the generation of novel probiotic bifidobacteria with improved health-promoting or therapeutic properties. To date, there is only very limited data on secretion signals of bifidobacteria available. Using in silico analysis, we demonstrate that all bifidobacteria encode the major components of Sec-dependent secretion machineries but only B. longum strains harbour Tat protein translocation systems. A reporter plasmid for secretion signals in bifidobacteria was established by fusing the coding sequence of the signal peptide of a sialidase of Bifidobacterium bifidum S17 to the phytase gene appA of E. coli. The recombinant strain showed increased phytase activity in spent culture supernatants and reduced phytase levels in crude extracts compared to the control indicating efficient phytase secretion. The reporter plasmid was used to screen seven predicted signal peptides in B. bifidum S17 and B. longum E18. The tested signal peptides differed substantially in their efficacy to mediate protein secretion in different host strains. An efficient signal peptide was used for expression and secretion of a therapeutically relevant protein in B. bifidum S17. Expression of a secreted cytosine deaminase led to a 100-fold reduced sensitivity of B. bifidum S17 to 5-fluorocytosine compared to the non-secreted cytosine deaminase suggesting efficient conversion of 5-fluorocytosine to the cytotoxic cancer drug 5-fluorouracil by cytosine deaminase occurred outside the bacterial cell. Selection of appropriate signal peptides for defined protein secretion might improve therapeutic efficacy as well as probiotic properties of bifidobacteria.

  7. A Phytase-Based Reporter System for Identification of Functional Secretion Signals in Bifidobacteria

    Science.gov (United States)

    Osswald, Annika; Westermann, Christina; Sun, Zhongke; Riedel, Christian U.

    2015-01-01

    Health-promoting effects have been attributed to a number of Bifidobacterium sp. strains. These effects as well as the ability to colonise the host depend on secreted proteins. Moreover, rational design of protein secretion systems bears the potential for the generation of novel probiotic bifidobacteria with improved health-promoting or therapeutic properties. To date, there is only very limited data on secretion signals of bifidobacteria available. Using in silico analysis, we demonstrate that all bifidobacteria encode the major components of Sec-dependent secretion machineries but only B. longum strains harbour Tat protein translocation systems. A reporter plasmid for secretion signals in bifidobacteria was established by fusing the coding sequence of the signal peptide of a sialidase of Bifidobacterium bifidum S17 to the phytase gene appA of E. coli. The recombinant strain showed increased phytase activity in spent culture supernatants and reduced phytase levels in crude extracts compared to the control indicating efficient phytase secretion. The reporter plasmid was used to screen seven predicted signal peptides in B. bifidum S17 and B. longum E18. The tested signal peptides differed substantially in their efficacy to mediate protein secretion in different host strains. An efficient signal peptide was used for expression and secretion of a therapeutically relevant protein in B. bifidum S17. Expression of a secreted cytosine deaminase led to a 100-fold reduced sensitivity of B. bifidum S17 to 5-fluorocytosine compared to the non-secreted cytosine deaminase suggesting efficient conversion of 5-fluorocytosine to the cytotoxic cancer drug 5-fluorouracil by cytosine deaminase occurred outside the bacterial cell. Selection of appropriate signal peptides for defined protein secretion might improve therapeutic efficacy as well as probiotic properties of bifidobacteria. PMID:26086721

  8. The BESIII muon identification system

    International Nuclear Information System (INIS)

    Zhang Jiawen; Qian Sen; Chen Jin; Du Zhizhen; Han Jifeng; Li Rubo; Liu Jichen; Liang Hao; Mao, Yajun; Ma Liehua; Wang Yifang; Xie Yigang; Xie Yuguang; Zhang Qingmin; Zhao Jianbing; Zhao, T.; Zhou, Yongzhao

    2010-01-01

    The muon identification system of BESIII experiment at the IHEP is described. The muon counter (MUC) is composed of resistive plate chambers (RPCs) working in self-quenching streamer mode with the gas mixture Ar/C 2 F 4 H 2 /C 4 H 10 =50/42/8. The design, the construction, the mass production and the quality control result of the detectors are described in detail. The paper also presents the performance of the bare RPCs and the superlayer modules with cosmic rays. Finally, the subsystems of MUC, including the RPC superlayer modules, the gas systems, the HV and LV system and the readout electronic system, are also presented.

  9. Model Predictive Control Based on System Re-Identification (MPC-SRI) to Control Bio-H2 Production from Biomass

    Science.gov (United States)

    Wahid, A.; Taqwallah, H. M. H.

    2018-03-01

    Compressors and a steam reformer are the important units in biohydrogen from biomass plant. The compressors are useful for achieving high-pressure operating conditions while the steam reformer is the main process to produce H2 gas. To control them, in this research used a model predictive control (MPC) expected to have better controller performance than conventional controllers. Because of the explicit model empowerment in MPC, obtaining a better model is the main objective before employing MPC. The common way to get the empirical model is through the identification system, so that obtained a first-order plus dead-time (FOPDT) model. This study has already improved that way since used the system re-identification (SRI) based on closed loop mode. Based on this method the results of the compressor pressure control and temperature control of steam reformer were that MPC based on system re-identification (MPC-SRI) has better performance than MPC without system re-identification (MPCWSRI) and the proportional-integral (PI) controller, by % improvement of 73% against MPCWSRI and 75% against the PI controller.

  10. 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.

  11. Structural system identification: Structural dynamics model validation

    Energy Technology Data Exchange (ETDEWEB)

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  12. 3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method

    Science.gov (United States)

    Huang, Xin; Yin, Chang-Chun; Cao, Xiao-Yue; Liu, Yun-He; Zhang, Bo; Cai, Jing

    2017-09-01

    The airborne electromagnetic (AEM) method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element (SE) method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell's equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic

  13. Process identification of the SCR system of coal-fired power plant for de-NOx based on historical operation data.

    Science.gov (United States)

    Li, Jian; Shi, Raoqiao; Xu, Chuanlong; Wang, Shimin

    2018-05-08

    The selective catalytic reduction (SCR) system, as one principal flue gas treatment method employed for the NO x emission control of the coal-fired power plant, is nonlinear and time-varying with great inertia and large time delay. It is difficult for the present SCR control system to achieve satisfactory performance with the traditional feedback and feedforward control strategies. Although some improved control strategies, such as the Smith predictor control and the model predictive control, have been proposed for this issue, a well-matched identification model is essentially required to realize a superior control of the SCR system. Industrial field experiment is an alternative way to identify the SCR system model in the coal-fired power plant. But it undesirably disturbs the operation system and is costly in time and manpower. In this paper, a process identification model of the SCR system is proposed and developed by applying the asymptotic method to the sufficiently excited data, selected from the original historical operation database of a 350 MW coal-fired power plant according to the condition number of the Fisher information matrix. Numerical simulations are carried out based on the practical historical operation data to evaluate the performance of the proposed model. Results show that the proposed model can efficiently achieve the process identification of the SCR system.

  14. Use of an identification system based on biometric data for patients requiring transfusions guarantees transfusion safety and traceability.

    Science.gov (United States)

    Bennardello, Francesco; Fidone, Carmelo; Cabibbo, Sergio; Calabrese, Salvatore; Garozzo, Giovanni; Cassarino, Grazia; Antolino, Agostino; Tavolino, Giuseppe; Zisa, Nuccio; Falla, Cadigia; Drago, Giuseppe; Di Stefano, Giovanna; Bonomo, Pietro

    2009-07-01

    One of the most serious risks of blood transfusions is an error in ABO blood group compatibility, which can cause a haemolytic transfusion reaction and, in the most severe cases, the death of the patient. The frequency and type of errors observed suggest that these are inevitable, in that mistakes are inherent to human nature, unless significant changes, including the use of computerised instruments, are made to procedures. In order to identify patients who are candidates for the transfusion of blood components and to guarantee the traceability of the transfusion, the Securblood system (BBS srl) was introduced. This system records the various stages of the transfusion process, the health care workers involved and any immediate transfusion reactions. The patients and staff are identified by fingerprinting or a bar code. The system was implemented within Ragusa hospital in 16 operative units (ordinary wards, day hospital, operating theatres). In the period from August 2007 to July 2008, 7282 blood components were transfused within the hospital, of which 5606 (77%) using the Securblood system. Overall, 1777 patients were transfused. In this year of experience, no transfusion errors were recorded and each blood component was transfused to the right patient. We recorded 33 blocks of the terminals (involving 0.6% of the transfused blood components) which required the intervention of staff from the Service of Immunohaematology and Transfusion Medicine (SIMT). Most of the blocks were due to procedural errors. The Securblood system guarantees complete traceability of the transfusion process outside the SIMT and eliminates the possibility of mistaken identification of patients or blood components. The use of fingerprinting to identify health care staff (nurses and doctors) and patients obliges the staff to carry out the identification procedures directly in the presence of the patient and guarantees the presence of the doctor at the start of the transfusion.

  15. Mastering system identification in 100 exercises

    CERN Document Server

    Schoukens, J; Rolain, Yves

    2012-01-01

    "This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource"--

  16. Early Engagement of Safety and Mission Assurance Expertise Using Systems Engineering Tools: A Risk-Based Approach to Early Identification of Safety and Assurance Requirements

    Science.gov (United States)

    Darpel, Scott; Beckman, Sean

    2016-01-01

    Decades of systems engineering practice have demonstrated that the earlier the identification of requirements occurs, the lower the chance that costly redesigns will needed later in the project life cycle. A better understanding of all requirements can also improve the likelihood of a design's success. Significant effort has been put into developing tools and practices that facilitate requirements determination, including those that are part of the model-based systems engineering (MBSE) paradigm. These efforts have yielded improvements in requirements definition, but have thus far focused on a design's performance needs. The identification of safety & mission assurance (S&MA) related requirements, in comparison, can occur after preliminary designs are already established, yielding forced redesigns. Engaging S&MA expertise at an earlier stage, facilitated by the use of MBSE tools, and focused on actual project risk, can yield the same type of design life cycle improvements that have been realized in technical and performance requirements.

  17. Fieldable Nuclear Material Identification System

    International Nuclear Information System (INIS)

    Radle, James E.; Archer, Daniel E.; Carter, Robert J.; Mullens, James Allen; Mihalczo, John T.; Britton, Charles L. Jr.; Lind, Randall F.; Wright, Michael C.

    2010-01-01

    The Fieldable Nuclear Material Identification System (FNMIS), funded by the NA-241 Office of Dismantlement and Transparency, provides information to determine the material attributes and identity of heavily shielded nuclear objects. This information will provide future treaty participants with verifiable information required by the treaty regime. The neutron interrogation technology uses a combination of information from induced fission neutron radiation and transmitted neutron imaging information to provide high confidence that the shielded item is consistent with the host's declaration. The combination of material identification information and the shape and configuration of the item are very difficult to spoof. When used at various points in the warhead dismantlement sequence, the information complimented by tags and seals can be used to track subassembly and piece part information as the disassembly occurs. The neutron transmission imaging has been developed during the last seven years and the signature analysis over the last several decades. The FNMIS is the culmination of the effort to put the technology in a usable configuration for potential treaty verification purposes.

  18. 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

  19. Trends and progress in system identification

    CERN Document Server

    Eykhoff, Pieter

    1981-01-01

    Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the """"classical"""" methods and time series estimation; application of least squares and related techniques for the e

  20. An Indicator Based Assessment Methodology Proposal for the Identification of Domestic Systemically Important Banks within the Turkish Banking Sector

    OpenAIRE

    Ozge ULKUTAS SACCI; Guven SAYILGAN

    2014-01-01

    This study aims to identify domestic systemically important banks (D-SIB) operating within the Turkish Banking Sector. In this regard, adopting an indicator based assessment methodology together with the cluster analysis application, banks in the sample are classified in terms of their degree of systemic importance by using publicly available year-end data of 2012. The study has shown that a total of 7 banks with the highest systemic importance clustered away from the remaining 21 banks in th...

  1. Direct blood culturing on solid medium outperforms an automated continuously monitored broth-based blood culture system in terms of time to identification and susceptibility testing

    Directory of Open Access Journals (Sweden)

    E.A. Idelevich

    2016-03-01

    Full Text Available Pathogen identification and antimicrobial susceptibility testing (AST should be available as soon as possible for patients with bloodstream infections. We investigated whether a lysis-centrifugation (LC blood culture (BC method, combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS identification and Vitek 2 AST, provides a time advantage in comparison with the currently used automated broth-based BC system. Seven bacterial reference strains were added each to 10 mL human blood in final concentrations of 100, 10 and 1 CFU/mL. Inoculated blood was added to the Isolator 10 tube and centrifuged at 3000 g for 30 min, then 1.5 mL sediment was distributed onto five 150-mm agar plates. Growth was observed hourly and microcolonies were subjected to MALDI-TOF MS and Vitek 2 as soon as possible. For comparison, seeded blood was introduced into an aerobic BC bottle and incubated in the BACTEC 9240 automated BC system. For all species/concentration combinations except one, successful identification and Vitek 2 inoculation were achieved even before growth detection by BACTEC. The fastest identification and inoculation for AST were achieved with Escherichia coli in concentrations of 100 CFU/mL and 10 CFU/mL (after 7 h each, while BACTEC flagged respective samples positive after 9.5 h and 10 h. Use of the LC-BC method allows skipping of incubation in automated BC systems and, used in combination with rapid diagnostics from microcolonies, provides a considerable advantage in time to result. This suggests that the usefulness of direct BC on solid medium should be re-evaluated in the era of rapid microbiology.

  2. Compressive power spectrum sensing for vibration-based output-only system identification of structural systems in the presence of noise

    Science.gov (United States)

    Tau Siesakul, Bamrung; Gkoktsi, Kyriaki; Giaralis, Agathoklis

    2015-05-01

    Motivated by the need to reduce monetary and energy consumption costs of wireless sensor networks in undertaking output-only/operational modal analysis of engineering structures, this paper considers a multi-coset analog-toinformation converter for structural system identification from acceleration response signals of white noise excited linear damped structures sampled at sub-Nyquist rates. The underlying natural frequencies, peak gains in the frequency domain, and critical damping ratios of the vibrating structures are estimated directly from the sub-Nyquist measurements and, therefore, the computationally demanding signal reconstruction step is by-passed. This is accomplished by first employing a power spectrum blind sampling (PSBS) technique for multi-band wide sense stationary stochastic processes in conjunction with deterministic non-uniform multi-coset sampling patterns derived from solving a weighted least square optimization problem. Next, modal properties are derived by the standard frequency domain peak picking algorithm. Special attention is focused on assessing the potential of the adopted PSBS technique, which poses no sparsity requirements to the sensed signals, to derive accurate estimates of modal structural system properties from noisy sub- Nyquist measurements. To this aim, sub-Nyquist sampled acceleration response signals corrupted by various levels of additive white noise pertaining to a benchmark space truss structure with closely spaced natural frequencies are obtained within an efficient Monte Carlo simulation-based framework. Accurate estimates of natural frequencies and reasonable estimates of local peak spectral ordinates and critical damping ratios are derived from measurements sampled at about 70% below the Nyquist rate and for SNR as low as 0db demonstrating that the adopted approach enjoys noise immunity.

  3. PWL approximation of nonlinear dynamical systems, part II: identification issues

    International Nuclear Information System (INIS)

    De Feo, O; Storace, M

    2005-01-01

    This paper and its companion address the problem of the approximation/identification of nonlinear dynamical systems depending on parameters, with a view to their circuit implementation. The proposed method is based on a piecewise-linear approximation technique. In particular, this paper describes a black-box identification method based on state space reconstruction and PWL approximation, and applies it to some particularly significant dynamical systems (two topological normal forms and the Colpitts oscillator)

  4. Hazard identification based on plant functional modelling

    International Nuclear Information System (INIS)

    Rasmussen, B.; Whetton, C.

    1993-10-01

    A major objective of the present work is to provide means for representing a process plant as a socio-technical system, so as to allow hazard identification at a high level. The method includes technical, human and organisational aspects and is intended to be used for plant level hazard identification so as to identify critical areas and the need for further analysis using existing methods. The first part of the method is the preparation of a plant functional model where a set of plant functions link together hardware, software, operations, work organisation and other safety related aspects of the plant. The basic principle of the functional modelling is that any aspect of the plant can be represented by an object (in the sense that this term is used in computer science) based upon an Intent (or goal); associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. The Methods and Constraints can themselves be treated as objects and decomposed into lower-level Intents (hence the procedure is known as functional decomposition) so giving rise to a hierarchical, object-oriented structure. The plant level hazard identification is carried out on the plant functional model using the Concept Hazard Analysis method. In this, the user will be supported by checklists and keywords and the analysis is structured by pre-defined worksheets. The preparation of the plant functional model and the performance of the hazard identification can be carried out manually or with computer support. (au) (4 tabs., 10 ills., 7 refs.)

  5. IDENTIFICATION OF ACTIVE BACTERIAL COMMUNITIES IN A MODEL DRINKING WATER BIOFILM SYSTEM USING 16S RRNA-BASED CLONE LIBRARIES

    Science.gov (United States)

    Recent phylogenetic studies have used DNA as the target molecule for the development of environmental 16S rDNA clone libraries. As DNA may persist in the environment, DNA-based libraries cannot be used to identify metabolically active bacteria in water systems. In this study, a...

  6. An Improved Global Harmony Search Algorithm for the Identification of Nonlinear Discrete-Time Systems Based on Volterra Filter Modeling

    Directory of Open Access Journals (Sweden)

    Zongyan Li

    2016-01-01

    Full Text Available This paper describes an improved global harmony search (IGHS algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.

  7. System-based identification of toxicity pathways associated with multi-walled carbon nanotube-induced pathological responses

    Energy Technology Data Exchange (ETDEWEB)

    Snyder-Talkington, Brandi N. [Pathology and Physiology Research Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Dymacek, Julian [Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506-6070 (United States); Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300 (United States); Porter, Dale W.; Wolfarth, Michael G.; Mercer, Robert R. [Pathology and Physiology Research Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Pacurari, Maricica [Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300 (United States); Denvir, James [Department of Biochemistry and Microbiology, Marshall University, Huntington, WV 25755 (United States); Castranova, Vincent [Pathology and Physiology Research Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Qian, Yong, E-mail: yaq2@cdc.gov [Pathology and Physiology Research Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Guo, Nancy L., E-mail: lguo@hsc.wvu.edu [Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300 (United States)

    2013-10-15

    The fibrous shape and biopersistence of multi-walled carbon nanotubes (MWCNT) have raised concern over their potential toxicity after pulmonary exposure. As in vivo exposure to MWCNT produced a transient inflammatory and progressive fibrotic response, this study sought to identify significant biological processes associated with lung inflammation and fibrosis pathology data, based upon whole genome mRNA expression, bronchoaveolar lavage scores, and morphometric analysis from C57BL/6J mice exposed by pharyngeal aspiration to 0, 10, 20, 40, or 80 μg MWCNT at 1, 7, 28, or 56 days post-exposure. Using a novel computational model employing non-negative matrix factorization and Monte Carlo Markov Chain simulation, significant biological processes with expression similar to MWCNT-induced lung inflammation and fibrosis pathology data in mice were identified. A subset of genes in these processes was determined to be functionally related to either fibrosis or inflammation by Ingenuity Pathway Analysis and was used to determine potential significant signaling cascades. Two genes determined to be functionally related to inflammation and fibrosis, vascular endothelial growth factor A (vegfa) and C-C motif chemokine 2 (ccl2), were confirmed by in vitro studies of mRNA and protein expression in small airway epithelial cells exposed to MWCNT as concordant with in vivo expression. This study identified that the novel computational model was sufficient to determine biological processes strongly associated with the pathology of lung inflammation and fibrosis and could identify potential toxicity signaling pathways and mechanisms of MWCNT exposure which could be used for future animal studies to support human risk assessment and intervention efforts. - Highlights: • A novel computational model identified toxicity pathways matching in vivo pathology. • Systematic identification of MWCNT-induced biological processes in mouse lungs • MWCNT-induced functional networks of lung

  8. System-based identification of toxicity pathways associated with multi-walled carbon nanotube-induced pathological responses

    International Nuclear Information System (INIS)

    Snyder-Talkington, Brandi N.; Dymacek, Julian; Porter, Dale W.; Wolfarth, Michael G.; Mercer, Robert R.; Pacurari, Maricica; Denvir, James; Castranova, Vincent; Qian, Yong; Guo, Nancy L.

    2013-01-01

    The fibrous shape and biopersistence of multi-walled carbon nanotubes (MWCNT) have raised concern over their potential toxicity after pulmonary exposure. As in vivo exposure to MWCNT produced a transient inflammatory and progressive fibrotic response, this study sought to identify significant biological processes associated with lung inflammation and fibrosis pathology data, based upon whole genome mRNA expression, bronchoaveolar lavage scores, and morphometric analysis from C57BL/6J mice exposed by pharyngeal aspiration to 0, 10, 20, 40, or 80 μg MWCNT at 1, 7, 28, or 56 days post-exposure. Using a novel computational model employing non-negative matrix factorization and Monte Carlo Markov Chain simulation, significant biological processes with expression similar to MWCNT-induced lung inflammation and fibrosis pathology data in mice were identified. A subset of genes in these processes was determined to be functionally related to either fibrosis or inflammation by Ingenuity Pathway Analysis and was used to determine potential significant signaling cascades. Two genes determined to be functionally related to inflammation and fibrosis, vascular endothelial growth factor A (vegfa) and C-C motif chemokine 2 (ccl2), were confirmed by in vitro studies of mRNA and protein expression in small airway epithelial cells exposed to MWCNT as concordant with in vivo expression. This study identified that the novel computational model was sufficient to determine biological processes strongly associated with the pathology of lung inflammation and fibrosis and could identify potential toxicity signaling pathways and mechanisms of MWCNT exposure which could be used for future animal studies to support human risk assessment and intervention efforts. - Highlights: • A novel computational model identified toxicity pathways matching in vivo pathology. • Systematic identification of MWCNT-induced biological processes in mouse lungs • MWCNT-induced functional networks of lung

  9. LPV system identification using series expansion models

    NARCIS (Netherlands)

    Toth, R.; Heuberger, P.S.C.; Hof, Van den P.M.J.; Santos, dos P.L.; Perdicoúlis, T.P.A.; Novara, C.; Ramos, J.A.; Rivera, D.E.

    2011-01-01

    This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. Written by world renowned researchers, the book contains twelve chapters, focusing on the most recent LPV identification methods for both discrete-time and continuous-time models, using different

  10. Search-based model identification of smart-structure damage

    Science.gov (United States)

    Glass, B. J.; Macalou, A.

    1991-01-01

    This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

  11. Distribution network topology identification based on synchrophasor

    Directory of Open Access Journals (Sweden)

    Stefania Conti

    2018-03-01

    Full Text Available A distribution system upgrade moving towards Smart Grid implementation is necessary to face the proliferation of distributed generators and electric vehicles, in order to satisfy the increasing demand for high quality, efficient, secure, reliable energy supply. This perspective requires taking into account system vulnerability to cyber attacks. An effective attack could destroy stored information about network structure, historical data and so on. Countermeasures and network applications could be made impracticable since most of them are based on the knowledge of network topology. Usually, the location of each link between nodes in a network is known. Therefore, the methods used for topology identification determine if a link is open or closed. When no information on the location of the network links is available, these methods become totally unfeasible. This paper presents a method to identify the network topology using only nodal measures obtained by means of phasor measurement units.

  12. Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

    Science.gov (United States)

    Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

    2016-08-04

    Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

  13. Electro-optical fuel pin identification system

    International Nuclear Information System (INIS)

    Kirchner, T.L.

    1978-09-01

    A prototype Electro-Optical Fuel Pin Identification System referred to as the Fuel Pin Identification System (FPIS) has been developed by the Hanford Engineering Development Laboratory (HEDL) in support of the Fast Flux Test Facility (FFTF) presently under construction at HEDL. The system is designed to remotely read an alpha-numeric identification number that is roll stamped on the top of the fuel pin end cap. The prototype FPIS consists of four major subassemblies: optical read head, digital compression electronics, video display, and line printer

  14. On System Identification of Wind Turbines

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Perisic, Nevena; Pedersen, B.J.

    Recently several methods have been proposed for the system identification of wind turbines which can be considered as a linear time-varying system due to the operating conditions. For the identification of linear wind turbine models, either black-box or grey-box identification can be used....... The operational model analysis (OMA) methodology can provide accurate estimates of the natural frequencies, damping ratios and mode shapes of the systems as long as the measurements have a low noise to signal ratio. However, in order to take information about the wind turbine into account a grey...

  15. The ontological model and the hybrid expert system for products and processes quality identification involving the approach based on system analysis and quality function deployment

    Directory of Open Access Journals (Sweden)

    Dmitriev Aleksandr

    2016-01-01

    Full Text Available Discussed model of quality of identification has improved mathematical tools and allows you to use a variety of additional information. The proposed robust method is a matrix MTQFD (Matrix Technique Quality Function Deployment allows you to determine not only the priorities but also the assessment of the target values of the product characteristics and process parameters, with the possible use of the information on the negative relationship. Designed ontological model, method and model of expert system versatile and can be used to identify the quality of services.

  16. Access control and personal identification systems

    CERN Document Server

    Bowers, Dan M

    1988-01-01

    Access Control and Personal Identification Systems provides an education in the field of access control and personal identification systems, which is essential in selecting the appropriate equipment, dealing intelligently with vendors in purchases of the equipment, and integrating the equipment into a total effective system. Access control devices and systems comprise an important part of almost every security system, but are seldom the sole source of security. In order for the goals of the total system to be met, the other portions of the security system must also be well planned and executed

  17. Chemical detection, identification, and analysis system

    International Nuclear Information System (INIS)

    Morel, R.S.; Gonzales, D.; Mniszewski, S.

    1990-01-01

    The chemical detection, identification, and analysis system (CDIAS) has three major goals. The first is to display safety information regarding chemical environment before personnel entry. The second is to archive personnel exposure to the environment. Third, the system assists users in identifying the stage of a chemical process in progress and suggests safety precautions associated with that process. In addition to these major goals, the system must be sufficiently compact to provide transportability, and it must be extremely simple to use in order to keep user interaction at a minimum. The system created to meet these goals includes several pieces of hardware and the integration of four software packages. The hardware consists of a low-oxygen, carbon monoxide, explosives, and hydrogen sulfide detector; an ion mobility spectrometer for airborne vapor detection; and a COMPAQ 386/20 portable computer. The software modules are a graphics kernel, an expert system shell, a data-base management system, and an interface management system. A supervisory module developed using the interface management system coordinates the interaction of the other software components. The system determines the safety of the environment using conventional data acquisition and analysis techniques. The low-oxygen, carbon monoxide, hydrogen sulfide, explosives, and vapor detectors are monitored for hazardous levels, and warnings are issued accordingly

  18. System identification and structural health monitoring of bridge structures

    OpenAIRE

    Islami, Kleidi

    2013-01-01

    This research study addresses two issues for the identification of structural characteristics of civil infrastructure systems. The first one is related to the problem of dynamic system identification, by means of experimental and operational modal analysis, applied to a large variety of bridge structures. Based on time and frequency domain techniques and mainly with output-only acceleration, velocity or strain data, modal parameters have been estimated for suspension bridges, masonry arch bri...

  19. Research of Uncertainty Reasoning in Pineapple Disease Identification System

    Science.gov (United States)

    Liu, Liqun; Fan, Haifeng

    In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

  20. 2012 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2012 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  1. 2014 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2014 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  2. 2009 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2009 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  3. 2010 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2010 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  4. 2011 United States Automatic Identification System Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2011 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

  5. CEAI: CCM based Email Authorship Identification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah

    2013-01-01

    In this paper we present a model for email authorship identification (EAI) by employing a Cluster-based Classification (CCM) technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature-set to include some...... more interesting and effective features for email authorship identification (e.g. the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell). We also included Info Gain feature selection based...... reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM)-based models, as well as the models proposed by Iqbal et al. [1, 2]. The proposed model attains an accuracy rate of 94% for 10...

  6. Multi-level RF identification system

    Science.gov (United States)

    Steele, Kerry D.; Anderson, Gordon A.; Gilbert, Ronald W.

    2004-07-20

    A radio frequency identification system having a radio frequency transceiver for generating a continuous wave RF interrogation signal that impinges upon an RF identification tag. An oscillation circuit in the RF identification tag modulates the interrogation signal with a subcarrier of a predetermined frequency and modulates the frequency-modulated signal back to the transmitting interrogator. The interrogator recovers and analyzes the subcarrier signal and determines its frequency. The interrogator generates an output indicative of the frequency of the subcarrier frequency, thereby identifying the responding RFID tag as one of a "class" of RFID tags configured to respond with a subcarrier signal of a predetermined frequency.

  7. FPGA Implementation for GMM-Based Speaker Identification

    Directory of Open Access Journals (Sweden)

    Phaklen EhKan

    2011-01-01

    Full Text Available In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors such as Mel-Frequency Cepstral Coefficients (MFCCs from the speech signal. A well-known statistical modelling process, the Gaussian Mixture Model (GMM, then models the distribution of each speaker's MFCCs in a multidimensional acoustic space. The GMM-based speaker identification system has features that make it promising for hardware acceleration. This paper describes the hardware implementation for classification of a text-independent GMM-based speaker identification system. The aim was to produce a system that can perform simultaneous identification of large numbers of voice streams in real time. This has important potential applications in security and in automated call centre applications. A speedup factor of ninety was achieved compared to a software implementation on a standard PC.

  8. Identification of active Plasmodium falciparum calpain to establish screening system for Pf-calpain-based drug development

    Directory of Open Access Journals (Sweden)

    Soh Byoung

    2013-02-01

    Full Text Available Abstract Background With the increasing resistance of malaria parasites to available drugs, there is an urgent demand to develop new anti-malarial drugs. Calpain inhibitor, ALLN, is proposed to inhibit parasite proliferation by suppressing haemoglobin degradation. This provides Plasmodium calpain as a potential target for drug development. Pf-calpain, a cysteine protease of Plasmodium falciparum, belongs to calpain-7 family, which is an atypical calpain not harboring Ca2+-binding regulatory motifs. In this present study, in order to establish the screening system for Pf-calpain specific inhibitors, the active form of Pf-calpain was first identified. Methods Recombinant Pf-calpain including catalytic subdomain IIa (rPfcal-IIa was heterologously expressed and purified. Enzymatic activity was determined by both fluorogenic substrate assay and gelatin zymography. Molecular homology modeling was carried out to address the activation mode of Pf-calpain in the aspect of structural moiety. Results Based on the measurement of enzymatic activity and protease inhibitor assay, it was found that the active form of Pf-calpain only contains the catalytic subdomain IIa, suggesting that Pf-calpain may function as a monomeric form. The sequence prediction indicates that the catalytic subdomain IIa contains all amino acid residues necessary for catalytic triad (Cys-His-Asn formation. Molecular modeling suggests that the Pf-calpain subdomain IIa makes an active site, holding the catalytic triad residues in their appropriate orientation for catalysis. The mutation analysis further supports that those amino acid residues are functional and have enzymatic activity. Conclusion The identified active form of Pf-calpain could be utilized to establish high-throughput screening system for Pf-calpain inhibitors. Due to its unique monomeric structural property, Pf-calpain could be served as a novel anti-malarial drug target, which has a high specificity for malaria parasite

  9. System Identification A Frequency Domain Approach

    CERN Document Server

    Pintelon, Rik

    2012-01-01

    System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identi

  10. Performance of an optical identification and interrogation system

    Science.gov (United States)

    Venugopalan, A.; Ghosh, A. K.; Verma, P.; Cheng, S.

    2008-04-01

    A free space optics based identification and interrogation system has been designed. The applications of the proposed system lie primarily in areas which require a secure means of mutual identification and information exchange between optical readers and tags. Conventional RFIDs raise issues regarding security threats, electromagnetic interference and health safety. The security of RF-ID chips is low due to the wide spatial spread of radio waves. Malicious nodes can read data being transmitted on the network, if they are in the receiving range. The proposed system provides an alternative which utilizes the narrow paraxial beams of lasers and an RSA-based authentication scheme. These provide enhanced security to communication between a tag and the base station or reader. The optical reader can also perform remote identification and the tag can be read from a far off distance, given line of sight. The free space optical identification and interrogation system can be used for inventory management, security systems at airports, port security, communication with high security systems, etc. to name a few. The proposed system was implemented with low-cost, off-the-shelf components and its performance in terms of throughput and bit error rate has been measured and analyzed. The range of operation with a bit-error-rate lower than 10-9 was measured to be about 4.5 m. The security of the system is based on the strengths of the RSA encryption scheme implemented using more than 1024 bits.

  11. 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...

  12. Comparison of System Identification Methods using Ambient Bridge Test Data

    DEFF Research Database (Denmark)

    Andersen, P.; Brincker, Rune; Peeters, B.

    1999-01-01

    In this paper the performance of four different system identification methods is compared using operational data obtained from an ambient vibration test of the Swiss Z24 highway bridge. The four methods are the frequency domain based peak-picking methods, the polyreference LSCE method, the stocha......In this paper the performance of four different system identification methods is compared using operational data obtained from an ambient vibration test of the Swiss Z24 highway bridge. The four methods are the frequency domain based peak-picking methods, the polyreference LSCE method...

  13. MAC, A System for Automatically IPR Identification, Collection and Distribution

    Science.gov (United States)

    Serrão, Carlos

    Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

  14. Combined state and parameter identification of nonlinear structural dynamical systems based on Rao-Blackwellization and Markov chain Monte Carlo simulations

    Science.gov (United States)

    Abhinav, S.; Manohar, C. S.

    2018-03-01

    The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.

  15. System Identification of Mistuned Bladed Disks from Traveling Wave Response Measurements

    Science.gov (United States)

    Feiner, D. M.; Griffin, J. H.; Jones, K. W.; Kenyon, J. A.; Mehmed, O.; Kurkov, A. P.

    2003-01-01

    A new approach to modal analysis is presented. By applying this technique to bladed disk system identification methods, one can determine the mistuning in a rotor based on its response to a traveling wave excitation. This allows system identification to be performed under rotating conditions, and thus expands the applicability of existing mistuning identification techniques from integrally bladed rotors to conventional bladed disks.

  16. Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: animal experiments and proof of concept

    International Nuclear Information System (INIS)

    Geoffrey Chase, J; Starfinger, Christina; Hann, Christopher E; Lambermont, Bernard; Ghuysen, Alexandre; Kolh, Philippe; Dauby, Pierre C; Desaive, Thomas; Shaw, Geoffrey M

    2011-01-01

    A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis—a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases. The main goal of this study is to prove the concept of using only measurements from one side of the heart (right) in a 'minimal' data set to identify an effective patient-specific model that can capture key clinical trends in endotoxic shock. This research extends existing methods to a reduced and minimal data set requiring only a single catheter and reducing the risk of infection and other complications—a very common, typical situation in critical care patients, particularly after cardiac surgery. The extended methods and assumptions that found it are developed and presented in a case study for the patient-specific parameter identification of pig-specific parameters in an animal model of induced endotoxic shock. This case study is used to define the impact of this minimal data set on the quality and accuracy of the model application for monitoring, detecting and diagnosing septic shock. Six anesthetized healthy pigs weighing 20–30 kg received a 0.5 mg kg −1 endotoxin infusion over a period of 30 min from T0 to T30. For this research, only right heart measurements were obtained. Errors for the identified model are within 8% when the model is identified from data, re-simulated and then compared to the experimentally measured data, including measurements not used in the

  17. Optimized Experiment Design for Marine Systems Identification

    DEFF Research Database (Denmark)

    Blanke, M.; Knudsen, Morten

    1999-01-01

    Simulation of maneuvring and design of motion controls for marine systems require non-linear mathematical models, which often have more than one-hundred parameters. Model identification is hence an extremely difficult task. This paper discusses experiment design for marine systems identification...... and proposes a sensitivity approach to solve the practical experiment design problem. The applicability of the sensitivity approach is demonstrated on a large non-linear model of surge, sway, roll and yaw of a ship. The use of the method is illustrated for a container-ship where both model and full-scale tests...

  18. Bounding approaches to system identification

    CERN Document Server

    Norton, John; Piet-Lahanier, Hélène; Walter, Éric

    1996-01-01

    In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

  19. Gait Correlation Analysis Based Human Identification

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

    Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.

  20. Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury.

    Science.gov (United States)

    Herasevich, V; Yilmaz, M; Khan, H; Chute, C G; Gajic, O

    2007-10-11

    Early detection of specific critical care syndromes, such as sepsis or acute lung injury (ALI)is essential for timely implementation of evidence based therapies. Using a near-real time copy of the electronic medical records ("ICU data mart") we developed and validated custom electronic alert (ALI"sniffer") in a cohort of 485 critically ill medical patients. Compared with the gold standard of prospective screening, ALI "sniffer" demonstrated good sensitivity, 93% (95% CI 90 to 95) and specificity, 90% (95% CI 87 to 92). It is not known if the bedside implementation of ALI "sniffer" will improve the adherence to evidence-based therapies and outcome of patients with ALI.

  1. System identification with information theoretic criteria

    NARCIS (Netherlands)

    A.A. Stoorvogel; J.H. van Schuppen (Jan)

    1995-01-01

    textabstractAttention is focused in this paper on the approximation problem of system identification with information theoretic criteria. For a class of problems it is shown that the criterion of mutual information rate is identical to the criterion of exponential-of-quadratic cost and to

  2. 78 FR 58785 - Unique Device Identification System

    Science.gov (United States)

    2013-09-24

    ... the UDI system because they are controlled in the supply chain by the kit rather than by constituent... reduce existing obstacles to the adequate identification of medical devices used in the United States. By... stated, ``We support FDA's objective to substantially reduce existing obstacles to the adequate...

  3. Autonomous system for pathogen detection and identification

    International Nuclear Information System (INIS)

    Belgrader, P.; Benett, W.; Langlois, R.; Long, G.; Mariella, R.; Milanovich, F.; Miles, R.; Nelson, W.; Venkateswaran, K.

    1998-01-01

    This purpose of this project is to build a prototype instrument that will, running unattended, detect, identify, and quantify BW agents. In order to accomplish this, we have chosen to start with the world s leading, proven, assays for pathogens: surface-molecular recognition assays, such as antibody-based assays, implemented on a high-performance, identification (ID)-capable flow cytometer, and the polymerase chain reaction (PCR) for nucleic-acid based assays. With these assays, we must integrate the capability to: l collect samples from aerosols, water, or surfaces; l perform sample preparation prior to the assays; l incubate the prepared samples, if necessary, for a period of time; l transport the prepared, incubated samples to the assays; l perform the assays; l interpret and report the results of the assays. Issues such as reliability, sensitivity and accuracy, quantity of consumables, maintenance schedule, etc. must be addressed satisfactorily to the end user. The highest possible sensitivity and specificity of the assay must be combined with no false alarms. Today, we have assays that can, in under 30 minutes, detect and identify stimulants for BW agents at concentrations of a few hundred colony-forming units per ml of solution. If the bio-aerosol sampler of this system collects 1000 Ymin and concentrates the respirable particles into 1 ml of solution with 70% processing efficiency over a period of 5 minutes, then this translates to a detection/ID capability of under 0.1 agent-containing particle/liter of air

  4. 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...

  5. System Identification Methods for Aircraft Flight Control Development and Validation

    Science.gov (United States)

    1995-10-01

    System-identification methods compose a mathematical model, or series of models, : from measurements of inputs and outputs of dynamic systems. This paper : discusses the use of frequency-domain system-identification methods for the : development and ...

  6. Collaborative evaluation of the Abbott yeast identification system.

    OpenAIRE

    Cooper, B H; Prowant, S; Alexander, B; Brunson, D H

    1984-01-01

    The Abbott yeast identification system (Abbott Laboratories, Diagnostics Division, Irving, Tex.) is a 24-h, instrumental method for identifying medically important yeasts, based on matrix analysis of 19 biochemical reactions and the germ tube test. The system was evaluated in two clinical laboratories by using 179 coded isolates, which included a high percentage of the less frequently encountered species. Based upon results with these coded isolates and from previously obtained laboratory dat...

  7. Component codification and identification systems

    International Nuclear Information System (INIS)

    Pannenbaecker, K.

    1977-01-01

    The lecture covers the codification in power stations during the erection phase and commercial operation phase. A diagram gives a survey. There are three basic-codifications for application; 1) Kraftwerk-Kennzeichen-System (KKS) for marking each component in orientated systems, for marking electrical orientated positions in cubicals, switch gears etc. and for marking rooms in buildings; 2) Ordnungssystem (OS) for cost calculation and ordering; 3) Unterlagenarten-Schluessel (UAS) for letters, reports etc. and for documentation. The OS is developed on the principle of cost account number and is therefore close to the organization of each supplier and his special form of design and constrution. KKS has only to mark hardware. Therefore all German owners, consultants, authorities and suppliers develop KKS together and conform to it in DIN 407119. (ORU) [de

  8. Verification of a GIS-based system for identification of potential hydro power plant sites in Uganda

    OpenAIRE

    Gimbo, Florence

    2015-01-01

    Hydropower makes and is expected to continue to make a significant contribution to meeting the electricity demand in many countries. The information on hydropower potential is many places is often incomplete. A GIS based tool is under development is expected to help in quickly identifying possible hydropower plant locations over a large area in a short time. This study is aimed at evaluating how well this GIS tool is able to estimate the hydropower potential from the runoff maps and terrain/e...

  9. System Identification and Verification of Rotorcraft UAVs

    Science.gov (United States)

    Carlton, Zachary M.

    The task of a controls engineer is to design and implement control logic. To complete this task, it helps tremendously to have an accurate model of the system to be controlled. Obtaining a very accurate system model is not a trivial one, as much time and money is usually associated with the development of such a model. A typical physics based approach can require hundreds of hours of flight time. In an iterative process the model is tuned in such a way that it accurately models the physical system's response. This process becomes even more complicated for unstable and highly non-linear systems such as the dynamics of rotorcraft. An alternate approach to solving this problem is to extract an accurate model by analyzing the frequency response of the system. This process involves recording the system's responses for a frequency range of input excitations. From this data, an accurate system model can then be deduced. Furthermore, it has been shown that with use of the software package CIFER® (Comprehensive Identification from FrEquency Responses), this process can both greatly reduce the cost of modeling a dynamic system and produce very accurate results. The topic of this thesis is to apply CIFER® to a quadcopter to extract a system model for the flight condition of hover. The quadcopter itself is comprised of off-the-shelf components with a Pixhack flight controller board running open source Ardupilot controller logic. In this thesis, both the closed and open loop systems are identified. The model is next compared to dissimilar flight data and verified in the time domain. Additionally, the ESC (Electronic Speed Controller) motor/rotor subsystem, which is comprised of all the vehicle's actuators, is also identified. This process required the development of a test bench environment, which included a GUI (Graphical User Interface), data pre and post processing, as well as the augmentation of the flight controller source code. This augmentation of code allowed for

  10. Chemical shift-based identification of monosaccharide spin-systems with NMR spectroscopy to complement untargeted glycomics.

    Science.gov (United States)

    Klukowski, Piotr; Schubert, Mario

    2018-06-15

    A better understanding of oligosaccharides and their wide-ranging functions in almost every aspect of biology and medicine promises to uncover hidden layers of biology and will support the development of better therapies. Elucidating the chemical structure of an unknown oligosaccharide is still a challenge. Efficient tools are required for non-targeted glycomics. Chemical shifts are a rich source of information about the topology and configuration of biomolecules, whose potential is however not fully explored for oligosaccharides. We hypothesize that the chemical shifts of each monosaccharide are unique for each saccharide type with a certain linkage pattern, so that correlated data measured by NMR spectroscopy can be used to identify the chemical nature of a carbohydrate. We present here an efficient search algorithm, GlycoNMRSearch, that matches either a subset or the entire set of chemical shifts of an unidentified monosaccharide spin system to all spin systems in an NMR database. The search output is much more precise than earlier search functions and highly similar matches suggest the chemical structure of the spin system within the oligosaccharide. Thus searching for connected chemical shift correlations within all electronically available NMR data of oligosaccharides is a very efficient way of identifying the chemical structure of unknown oligosaccharides. With an improved database in the future, GlycoNMRSearch will be even more efficient deducing chemical structures of oligosaccharides and there is a high chance that it becomes an indispensable technique for glycomics. The search algorithm presented here, together with a graphical user interface, is available at http://glyconmrsearch.santos.pwr.edu.pl. Supplementary data are available at Bioinformatics online.

  11. Naïve Bayes Approach for Expert System Design of Children Skin Identification Based on Android

    Science.gov (United States)

    Hartatik; Purnomo, A.; Hartono, R.; Munawaroh, H.

    2018-03-01

    The development of technology gives some benefits to each person that we can use it properly and correctly. Technology has helped humans in every way. Such as the excess task of an expert in providing information or answers to a problem. Thus problem that often occurs is skin disease that affecting on child. That because the skin of children still vulnerable to the environment. The application was developed using the naïve Bayes algorithm. Through this application, users can consult with a system like an expert to know the symptoms that occur to the child and find the correct treatment to solve the problems.

  12. LPV Identification of a Heat Distribution System

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon

    2010-01-01

    This paper deals with incremental system identification of district heating systems to improve control performance. As long as various parameters, e.g. valve settings, are kept fixed, the dynamics of district heating systems can be approximated well by linear models; however, the dynamics change ....... The approach is tested on a laboratory setup emulating a district heating system, where local controllers regulate pumps connected to a common supply. Experiments show that cross-couplings in the system can indeed be identified in closed-loop operation....

  13. System identification: a frequency domain approach

    National Research Council Canada - National Science Library

    Pintelon, R; Schoukens, J

    2001-01-01

    ... in the Identification Process 17 1.4.1 Collect Information about the System 17 1.4.2 Select a Model Structure to Represent the System 17 1.4.3 Match the Selected Model Structure to the Measurements 19 1.4.4 Validate the Selected Model 19 1.4.5 Conclusion 19 A Statistical Approach to the Estimation Problem 1.5.1 Least Squares Estimation 20 1.5.2 Weighted Least Squar...

  14. Prediction-error identification of LPV systems : present and beyond

    NARCIS (Netherlands)

    Toth, R.; Heuberger, P.S.C.; Hof, Van den P.M.J.; Mohammadpour, J.; Scherer, C. W.

    2012-01-01

    The proposed chapter aims at presenting a unified framework of prediction-error based identification of LPV systems using freshly developed theoretical results. Recently, these methods have got a considerable attention as they have certain advantages in terms of computational complexity, optimality

  15. Friction ridge skin - Automated Fingerprint Identification System (AFIS)

    NARCIS (Netherlands)

    Meuwly, Didier

    2013-01-01

    This contribution describes the development and the forensic use of automated fingerprint identification systems (AFISs). AFISs were initially developed in order to overcome the limitations of the paper-based fingerprint collections, by digitizing the ten-print cards in computerized databases and to

  16. Searching methods for biometric identification systems: Fundamental limits

    NARCIS (Netherlands)

    Willems, F.M.J.

    2009-01-01

    We study two-stage search procedures for biometric identification systems in an information-theoretical setting. Our main conclusion is that clustering based on vector-quantization achieves the optimum trade-off between the number of clusters (cluster rate) and the number of individuals within a

  17. Development of an Automatic Identification System Autonomous Positioning System

    Directory of Open Access Journals (Sweden)

    Qing Hu

    2015-11-01

    Full Text Available In order to overcome the vulnerability of the global navigation satellite system (GNSS and provide robust position, navigation and time (PNT information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS is presented in the paper. The principle of the AIS autonomous positioning system (AAPS is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China. Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts.

  18. A grass molecular identification system for forensic botany: a critical evaluation of the strengths and limitations.

    Science.gov (United States)

    Ward, Jodie; Gilmore, Simon R; Robertson, James; Peakall, Rod

    2009-11-01

    Plant material is frequently encountered in criminal investigations but often overlooked as potential evidence. We designed a DNA-based molecular identification system for 100 Australian grasses that consisted of a series of polymerase chain reaction assays that enabled the progressive identification of grasses to different taxonomic levels. The identification system was based on DNA sequence variation at four chloroplast and two mitochondrial loci. Seventeen informative indels and 68 single-nucleotide polymorphisms were utilized as molecular markers for subfamily to species-level identification. To identify an unknown sample to subfamily level required a minimum of four markers or nine markers for species identification. The accuracy of the system was confirmed by blind tests. We have demonstrated "proof of concept" of a molecular identification system for trace botanical samples. Our evaluation suggests that the adoption of a system that combines this approach with DNA sequencing could assist the morphological identification of grasses found as forensic evidence.

  19. Identification of general linear mechanical systems

    Science.gov (United States)

    Sirlin, S. W.; Longman, R. W.; Juang, J. N.

    1983-01-01

    Previous work in identification theory has been concerned with the general first order time derivative form. Linear mechanical systems, a large and important class, naturally have a second order form. This paper utilizes this additional structural information for the purpose of identification. A realization is obtained from input-output data, and then knowledge of the system input, output, and inertia matrices is used to determine a set of linear equations whereby we identify the remaining unknown system matrices. Necessary and sufficient conditions on the number, type and placement of sensors and actuators are given which guarantee identificability, and less stringent conditions are given which guarantee generic identifiability. Both a priori identifiability and a posteriori identifiability are considered, i.e., identifiability being insured prior to obtaining data, and identifiability being assured with a given data set.

  20. Identification system by eye retinal pattern

    International Nuclear Information System (INIS)

    Sunagawa, Takahisa; Shibata, Susumu

    1987-01-01

    Identification system by eye retinal pattern is introduced from the view-point of history of R and D, measurement, apparatus, evaluation tests, safety and application. According to our evaluation tests, enrolling time is approximately less than 1 min, verification time is a few seconds and false accept rate is 0 %. Evaluation tests at Sandia National Laboratories in USA show the comparison data of false accept rates such as 0 % for eye retinal pattern, 10.5 % for finger-print, 5.8 % for signature dynamics and 17.7 % for speaker voice. The identification system by eye retinal pattern has only three applications in Japan, but there has been a number of experience in USA. This fact suggests that the system will become an important means for physical protections not only in nuclear field but also in other industrial fields in Japan. (author)

  1. Neural System Prediction and Identification Challenge

    Directory of Open Access Journals (Sweden)

    Ioannis eVlachos

    2013-12-01

    Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  2. Neural system prediction and identification challenge.

    Science.gov (United States)

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  3. Music Identification System Using MPEG-7 Audio Signature Descriptors

    Science.gov (United States)

    You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

    2013-01-01

    This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

  4. Printed Identification Key or Web-Based Identification Guide: An Effective Tool for Species Identification?

    Directory of Open Access Journals (Sweden)

    Thomas Edison E. dela Cruz

    2012-09-01

    Full Text Available Species identification is often done with the aid of traditional dichotomous keys. This printed material is based on one’s decision between two alternatives, which is followed by another pair of alternatives until the final species name is reached. With the advent of internet technology, the use of an online database offers an updatable and accumulative approach to species identification. It can also be accessed anytime, and this is very useful for fast-changing groups of organisms. In this paper, we report the preference of sophomore Bachelor of Science (B.Sc. in Microbiology students to two identification guides as a tool in taxonomy. We wish to test our hypothesis that today’s students will prefer to use web-based ID guides over printed dichotomous keys. We also describe how these printed dichotomous key and web-based ID guides were used by the students as one of their laboratory activities in the course Biology of Algae and Fungi.  

  5. Performance metrics for the evaluation of hyperspectral chemical identification systems

    Science.gov (United States)

    Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

    2016-02-01

    Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

  6. Vortex Tube Modeling Using the System Identification Method

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jaeyoung; Jeong, Jiwoong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Im, Seokyeon [Tongmyong Univ., Busan (Korea, Republic of)

    2017-05-15

    In this study, vortex tube system model is developed to predict the temperature of the hot and the cold sides. The vortex tube model is developed based on the system identification method, and the model utilized in this work to design the vortex tube is ARX type (Auto-Regressive with eXtra inputs). The derived polynomial model is validated against experimental data to verify the overall model accuracy. It is also shown that the derived model passes the stability test. It is confirmed that the derived model closely mimics the physical behavior of the vortex tube from both the static and dynamic numerical experiments by changing the angles of the low-temperature side throttle valve, clearly showing temperature separation. These results imply that the system identification based modeling can be a promising approach for the prediction of complex physical systems, including the vortex tube.

  7. Evaluation of hand hygiene compliance and associated factors with a radio-frequency-identification-based real-time continuous automated monitoring system.

    Science.gov (United States)

    Dufour, J-C; Reynier, P; Boudjema, S; Soto Aladro, A; Giorgi, R; Brouqui, P

    2017-04-01

    Hand hygiene is a major means for preventing healthcare-associated infections. One critical point in understanding poor compliance is the lack of relevant markers used to monitor practices systematically. This study analysed hand hygiene compliance and associated factors with a radio-frequency-identification-based real-time continuous automated monitoring system in an infectious disease ward with 17 single bedrooms. Healthcare workers (HCWs) were tracked while performing routine care over 171 days. A multi-level multi-variate logistics model was used for data analysis. The main outcome measures were hand disinfection before entering the bedroom (outside use) and before entering the patient care zone, defined as the zone surrounding the patient's bed (inside/bedside use). Variables analysed included HCWs' characteristics and behaviour, patients, room layouts, path chains and duration of HCWs' paths. In total, 4629 paths with initial hand hygiene opportunities when entering the patient care zone were selected, of which 763 (16.5%), 285 (6.1%) and 3581 (77.4%) were associated with outside use, inside/bedside use and no use, respectively. Hand hygiene is caregiver-dependent. The shorter the duration of the HCW's path, the worse the bedside hand hygiene. Bedside hand hygiene is improved when one or two extra HCWs are present in the room. Hand hygiene compliance at the bedside, as analysed using the continuous monitoring system, depended upon the HCW's occupation and personal behaviour, number of HCWs, time spent in the room and (potentially) dispenser location. Meal tray distribution was a possible factor in the case of failure to disinfect hands. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  8. Microbial System for Identification of Antibiotic Residues in Milk

    OpenAIRE

    Nagel, Orlando Guillermo; Molina Pons, Mª Pilar; Althaus, Rafael Lisandro

    2011-01-01

    [EN] The aim of this study was to evaluate the ResScreen (R) microbiological system for the identification of antibiotic residues in milk. This microbiological system consists of two methods, the BT (betalactams and tetracyclines) and BS (betalactams and sulfamides) bioassays, containing spores of G. stearothermophilus subsp. calidolactis, culture media and indicators (acid-base and redox). The detection limits of 29 antimicrobial agents were calculated using a logistic regression model. ...

  9. Incremental Closed-loop Identification of Linear Parameter Varying Systems

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2011-01-01

    , closed-loop system identification is more difficult than open-loop identification. In this paper we prove that the so-called Hansen Scheme, a technique known from linear time-invariant systems theory for transforming closed-loop system identification problems into open-loop-like problems, can be extended...

  10. Ontology-based specification, identification and analysis of perioperative risks.

    Science.gov (United States)

    Uciteli, Alexandr; Neumann, Juliane; Tahar, Kais; Saleh, Kutaiba; Stucke, Stephan; Faulbrück-Röhr, Sebastian; Kaeding, André; Specht, Martin; Schmidt, Tobias; Neumuth, Thomas; Besting, Andreas; Stegemann, Dominik; Portheine, Frank; Herre, Heinrich

    2017-09-06

    Medical personnel in hospitals often works under great physical and mental strain. In medical decision-making, errors can never be completely ruled out. Several studies have shown that between 50 and 60% of adverse events could have been avoided through better organization, more attention or more effective security procedures. Critical situations especially arise during interdisciplinary collaboration and the use of complex medical technology, for example during surgical interventions and in perioperative settings (the period of time before, during and after surgical intervention). In this paper, we present an ontology and an ontology-based software system, which can identify risks across medical processes and supports the avoidance of errors in particular in the perioperative setting. We developed a practicable definition of the risk notion, which is easily understandable by the medical staff and is usable for the software tools. Based on this definition, we developed a Risk Identification Ontology (RIO) and used it for the specification and the identification of perioperative risks. An agent system was developed, which gathers risk-relevant data during the whole perioperative treatment process from various sources and provides it for risk identification and analysis in a centralized fashion. The results of such an analysis are provided to the medical personnel in form of context-sensitive hints and alerts. For the identification of the ontologically specified risks, we developed an ontology-based software module, called Ontology-based Risk Detector (OntoRiDe). About 20 risks relating to cochlear implantation (CI) have already been implemented. Comprehensive testing has indicated the correctness of the data acquisition, risk identification and analysis components, as well as the web-based visualization of results.

  11. Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT

    Directory of Open Access Journals (Sweden)

    Niko Nevaranta

    2015-07-01

    Full Text Available A proper system identification method is of great importance in the process of acquiring an analytical model that adequately represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach for system diagnostics, the frequency domain identification techniques have primarily been considered for offline commissioning purposes. This paper addresses issues in the online frequency domain identification of a flexible two-mass mechanical system with varying dynamics, and a particular attention is paid to detect the changes in the system dynamics. An online identification method is presented that is based on a recursive Kalman filter configured to perform like a discrete Fourier transform (DFT at a selected set of frequencies. The experimental online identification results are compared with the corresponding values obtained from the offline-identified frequency responses. The results show an acceptable agreement and demonstrate the feasibility of the proposed identification method.

  12. Music Identification System Using MPEG-7 Audio Signature Descriptors

    Directory of Open Access Journals (Sweden)

    Shingchern D. You

    2013-01-01

    Full Text Available This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system’s database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control.

  13. 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.

  14. 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.

  15. Identification problems in linear transformation system

    International Nuclear Information System (INIS)

    Delforge, Jacques.

    1975-01-01

    An attempt was made to solve the theoretical and numerical difficulties involved in the identification problem relative to the linear part of P. Delattre's theory of transformation systems. The theoretical difficulties are due to the very important problem of the uniqueness of the solution, which must be demonstrated in order to justify the value of the solution found. Simple criteria have been found when measurements are possible on all the equivalence classes, but the problem remains imperfectly solved when certain evolution curves are unknown. The numerical difficulties are of two kinds: a slow convergence of iterative methods and a strong repercussion of numerical and experimental errors on the solution. In the former case a fast convergence was obtained by transformation of the parametric space, while in the latter it was possible, from sensitivity functions, to estimate the errors, to define and measure the conditioning of the identification problem then to minimize this conditioning as a function of the experimental conditions [fr

  16. Televison assessment and identification system for the plutonium protection system

    International Nuclear Information System (INIS)

    Greenwoll, D.A.

    1979-02-01

    This report covers the selection, description, and use of the components comprising the Television Assessment and Identification System in the Hanford Plutonium Protection System. This work was sponsored by the Department of Energy/Office of Safeguards and Security (DOE/OSS) as part of the overall Sandia Fixed Facility Physical Protection Program

  17. Challenges in parameter identification of large structural dynamic systems

    International Nuclear Information System (INIS)

    Koh, C.G.

    2001-01-01

    In theory, it is possible to determine the parameters of a structural or mechanical system by subjecting it to some dynamic excitation and measuring the response. Considerable research has been carried out in this subject area known as the system identification over the past two decades. Nevertheless, the challenges associated with numerical convergence are still formidable when the system is large in terms of the number of degrees of freedom and number of unknowns. While many methods work for small systems, the convergence becomes difficult, if not impossible, for large systems. In this keynote lecture, both classical and non-classical system identification methods for dynamic testing and vibration-based inspection are discussed. For classical methods, the extended Kalman filter (EKF) approach is used. On this basis, a substructural identification method has been developed as a strategy to deal with large structural systems. This is achieved by reducing the problem size, thereby significantly improving the numerical convergence and efficiency. Two versions of this method are presented each with its own merits. A numerical example of frame structure with 20 unknown parameters is illustrated. For non-classical methods, the Genetic Algorithm (GA) is shown to be applicable with relative ease due to its 'forward analysis' nature. The computational time is, however, still enormous for large structural systems due to the combinatorial explosion problem. A model GA method has been developed to address this problem and tested with considerable success on a relatively large system of 50 degrees of freedom, accounting for input and output noise effects. An advantages of this GA-based identification method is that the objective function can be defined in response measured. Numerical studies show that the method is relatively robust, as it does in response measured. Numerical studies show that the method is relatively robust, as it dos not require good initial guess and the

  18. Broad spectrum microarray for fingerprint-based bacterial species identification

    Directory of Open Access Journals (Sweden)

    Frey Jürg E

    2010-02-01

    Full Text Available Abstract Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups.

  19. Biometric identification based on novel frequency domain facial asymmetry measures

    Science.gov (United States)

    Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

    2005-03-01

    In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.

  20. Performance of PC-based charged particle multi-channel spectrometer utilising particle identification

    International Nuclear Information System (INIS)

    Palla, G.; Sziklai, J.; Trajber, Cs.

    1993-12-01

    A collaterally expandable charged particle spectrometer based on PC control and particle identification is described. A typical system configuration consisting of two channels are used to test the system performance. (author) 7 refs.; 5 figs

  1. Upport vector machines for nonlinear kernel ARMA system identification.

    Science.gov (United States)

    Martínez-Ramón, Manel; Rojo-Alvarez, José Luis; Camps-Valls, Gustavo; Muñioz-Marí, Jordi; Navia-Vázquez, Angel; Soria-Olivas, Emilio; Figueiras-Vidal, Aníbal R

    2006-11-01

    Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA2K) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based system identification nonlinear models is presented, based on the use of composite Mercer's kernels. This general class can improve model flexibility by emphasizing the input-output cross information (SVM-ARMA4K), which leads to straightforward and natural combinations of implicit and explicit ARMA models (SVR-ARMA2K and SVR-ARMA4K). Capabilities of these different SVM-based system identification schemes are illustrated with two benchmark problems.

  2. 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%.

  3. Automated dental identification system: An aid to forensic odontology

    Directory of Open Access Journals (Sweden)

    Parvathi Devi

    2011-01-01

    Full Text Available Automated dental identification system is computer-aided software for the postmortem identification of deceased individuals based on dental characteristics specifically radiographs. This system is receiving increased attention because of the large number of victims encountered in the mass disasters and it is 90% more time saving and accurate than the conventional radiographic methods. This technique is based on the intensity of the overall region of tooth image and therefore it does not necessitate the presence of sharp boundary between the teeth. It provides automated search and matching capabilities for digitized radiographs and photographic dental images and compares the teeth present in multiple digitized dental records in order to access their similarity. This paper highlights the functionality of its components and techniques used in realizing these components.

  4. System Identification, Environmental Modelling, and Control System Design

    CERN Document Server

    Garnier, Hugues

    2012-01-01

    System Identification, Environmetric Modelling, and Control Systems Design is dedicated to Professor Peter Young on the occasion of his seventieth birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume is comprised of a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as ...

  5. Nuclear reactors transients identification and classification system

    International Nuclear Information System (INIS)

    Bianchi, Paulo Henrique

    2008-01-01

    This work describes the study and test of a system capable to identify and classify transients in thermo-hydraulic systems, using a neural network technique of the self-organizing maps (SOM) type, with the objective of implanting it on the new generations of nuclear reactors. The technique developed in this work consists on the use of multiple networks to do the classification and identification of the transient states, being each network a specialist at one respective transient of the system, that compete with each other using the quantization error, that is a measure given by this type of neural network. This technique showed very promising characteristics that allow the development of new functionalities in future projects. One of these characteristics consists on the potential of each network, besides responding what transient is in course, could give additional information about that transient. (author)

  6. Asymptotic inference in system identification for the atom maser.

    Science.gov (United States)

    Catana, Catalin; van Horssen, Merlijn; Guta, Madalin

    2012-11-28

    System identification is closely related to control theory and plays an increasing role in quantum engineering. In the quantum set-up, system identification is usually equated to process tomography, i.e. estimating a channel by probing it repeatedly with different input states. However, for quantum dynamical systems such as quantum Markov processes, it is more natural to consider the estimation based on continuous measurements of the output, with a given input that may be stationary. We address this problem using asymptotic statistics tools, for the specific example of estimating the Rabi frequency of an atom maser. We compute the Fisher information of different measurement processes as well as the quantum Fisher information of the atom maser, and establish the local asymptotic normality of these statistical models. The statistical notions can be expressed in terms of spectral properties of certain deformed Markov generators, and the connection to large deviations is briefly discussed.

  7. Reduced Complexity Volterra Models for Nonlinear System Identification

    Directory of Open Access Journals (Sweden)

    Hacıoğlu Rıfat

    2001-01-01

    Full Text Available A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter′s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a Fixed Pole Expansion Technique (FPET within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed in the paper.

  8. Automatic Identification System (AIS) Transmit Testing in Louisville Phase 2

    Science.gov (United States)

    2014-08-01

    Firewall Louisville QM 65.206.28.x NAIS Site Controller PC RS232 Serial cable TV32 Computer Cmd Center Serial splitter SAAB R40 AIS Base Station...172.17.14.6 Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary serial connection...Automatic Identification System ( AIS ) Transmit Testing in Louisville Phase 2 Distribution Statement A: Approved for public release

  9. Nuclear material enrichment identification method based on cross-correlation and high order spectra

    International Nuclear Information System (INIS)

    Yang Fan; Wei Biao; Feng Peng; Mi Deling; Ren Yong

    2013-01-01

    In order to enhance the sensitivity of nuclear material identification system (NMIS) against the change of nuclear material enrichment, the principle of high order statistic feature is introduced and applied to traditional NMIS. We present a new enrichment identification method based on cross-correlation and high order spectrum algorithm. By applying the identification method to NMIS, the 3D graphs with nuclear material character are presented and can be used as new signatures to identify the enrichment of nuclear materials. The simulation result shows that the identification method could suppress the background noises, electronic system noises, and improve the sensitivity against enrichment change to exponential order with no system structure modification. (authors)

  10. Identification of Nonlinear Dynamic Systems Possessing Some Non-linearities

    Directory of Open Access Journals (Sweden)

    Y. N. Pavlov

    2015-01-01

    Full Text Available The subject of this work is the problem of identification of nonlinear dynamic systems based on the experimental data obtained by applying test signals to the system. The goal is to determinate coefficients of differential equations of systems by experimental frequency hodographs and separate similar, but different, in essence, forces: dissipative forces with the square of the first derivative in the motion equations and dissipative force from the action of dry friction. There was a proposal to use the harmonic linearization method to approximate each of the nonlinearity of "quadratic friction" and "dry friction" by linear friction with the appropriate harmonic linearization coefficient.Assume that a frequency transfer function of the identified system has a known form. Assume as well that there are disturbances while obtaining frequency characteristics of the realworld system. As a result, the points of experimentally obtained hodograph move randomly. Searching for solution of the identification problem was in the hodograph class, specified by the system model, which has the form of the frequency transfer function the same as the form of the frequency transfer function of the system identified. Minimizing a proximity criterion (measure of the experimentally obtained system hodograph and the system hodograph model for all the experimental points described and previously published by one of the authors allowed searching for the unknown coefficients of the frequenc ransfer function of the system model. The paper shows the possibility to identify a nonlinear dynamic system with multiple nonlinearities, obtained on the experimental samples of the frequency system hodograph. The proposed algorithm allows to select the nonlinearity of the type "quadratic friction" and "dry friction", i.e. also in the case where the nonlinearity is dependent on the same dynamic parameter, in particular, on the derivative of the system output value. For the dynamic

  11. Cattle identification based in biometric features of the muzzle

    OpenAIRE

    Monteiro, Marta; Cadavez, Vasco; Monteiro, Fernando C.

    2015-01-01

    Cattle identification has been a serious problem for breeding association. Muzzle pattern or nose print has the same characteristic with the human fingerprint which is the most popular biometric marker. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle images using Speed-up Robust Features matching. The matching refinement technique based on the mat...

  12. Developing a Speaker Identification System for the DARPA RATS Project

    DEFF Research Database (Denmark)

    Plchot, O; Matsoukas, S; Matejka, P

    2013-01-01

    This paper describes the speaker identification (SID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. ...... such as CFCCs out-perform MFCC front-ends on noisy audio, and (c) fusion of multiple systems provides 24% relative improvement in EER compared to the single best system when using a novel SVM-based fusion algorithm that uses side information such as gender, language, and channel id....

  13. Predictor-based multivariable closed-loop system identification of the EXTRAP T2R reversed field pinch external plasma response

    Energy Technology Data Exchange (ETDEWEB)

    Olofsson, K Erik J; Brunsell, Per R; Drake, James R [Fusion Plasma Physics, School of Electrical Engineering, Royal Institute of Technology (KTH Stockholm), Sweden (Association EURATOM-VR) (Sweden); Rojas, Cristian R; Hjalmarsson, Haakan, E-mail: erik.olofsson@ee.kth.se [Automatic Control, School of Electrical Engineering, KTH Stockholm (Sweden)

    2011-08-15

    The usage of computationally feasible overparametrized and nonregularized system identification signal processing methods is assessed for automated determination of the full reversed-field pinch external plasma response spectrum for the experiment EXTRAP T2R. No assumptions on the geometry of eigenmodes are imposed. The attempted approach consists of high-order autoregressive exogenous estimation followed by Markov block coefficient construction and Hankel matrix singular value decomposition. It is seen that the obtained 'black-box' state-space models indeed can be compared with the commonplace ideal magnetohydrodynamics (MHD) resistive thin-shell model in cylindrical geometry. It is possible to directly map the most unstable autodetected empirical system pole to the corresponding theoretical resistive shell MHD eigenmode.

  14. Predictor-based multivariable closed-loop system identification of the EXTRAP T2R reversed field pinch external plasma response

    Science.gov (United States)

    Olofsson, K. Erik J.; Brunsell, Per R.; Rojas, Cristian R.; Drake, James R.; Hjalmarsson, Håkan

    2011-08-01

    The usage of computationally feasible overparametrized and nonregularized system identification signal processing methods is assessed for automated determination of the full reversed-field pinch external plasma response spectrum for the experiment EXTRAP T2R. No assumptions on the geometry of eigenmodes are imposed. The attempted approach consists of high-order autoregressive exogenous estimation followed by Markov block coefficient construction and Hankel matrix singular value decomposition. It is seen that the obtained 'black-box' state-space models indeed can be compared with the commonplace ideal magnetohydrodynamics (MHD) resistive thin-shell model in cylindrical geometry. It is possible to directly map the most unstable autodetected empirical system pole to the corresponding theoretical resistive shell MHD eigenmode.

  15. System identification to characterize human use of ethanol based on generative point-process models of video games with ethanol rewards.

    Science.gov (United States)

    Ozil, Ipek; Plawecki, Martin H; Doerschuk, Peter C; O'Connor, Sean J

    2011-01-01

    The influence of family history and genetics on the risk for the development of abuse or dependence is a major theme in alcoholism research. Recent research have used endophenotypes and behavioral paradigms to help detect further genetic contributions to this disease. Electronic tasks, essentially video games, which provide alcohol as a reward in controlled environments and with specified exposures have been developed to explore some of the behavioral and subjective characteristics of individuals with or at risk for alcohol substance use disorders. A generative model (containing parameters with unknown values) of a simple game involving a progressive work paradigm is described along with the associated point process signal processing that allows system identification of the model. The system is demonstrated on human subject data. The same human subject completing the task under different circumstances, e.g., with larger and smaller alcohol reward values, is assigned different parameter values. Potential meanings of the different parameter values are described.

  16. A physiologically based nonhomogeneous Poisson counter model of visual identification.

    Science.gov (United States)

    Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus; Kyllingsbæk, Søren

    2018-04-30

    A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

    Directory of Open Access Journals (Sweden)

    Zongze Wu

    2015-08-01

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

  18. Evaluation of the utility of a glycemic pattern identification system.

    Science.gov (United States)

    Otto, Erik A; Tannan, Vinay

    2014-07-01

    With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes. To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows. Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification. The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control. © 2014 Diabetes Technology Society.

  19. Applications of radio frequency identification systems in the mining industry

    Energy Technology Data Exchange (ETDEWEB)

    Hind, D J [Davis Derby Ltd., Derby (United Kingdom)

    1994-01-01

    Radio Frequency Identification Systems (RFID) are one of the automatic data capture technologies taking over from bar codes and magnetic swipe cards in many applications involving automatic hands free operation in arduous environments. RFID systems are based on the use of miniature radio transponders carrying encoded electronic data that is used to uniquely identify the identity of transponders. The paper reviews the types of system available and compares the various techniques involved in the different systems. The various types of transponder are described including the latest state of the art passive read/write high performance types. The problems involved in designing and certifying a system for use in hazardous areas are described, with particular reference to the problems of inadvertent detonator ignition by radio systems. Applications of RFID systems in the mining industry are described, covering applications both on the surface and underground. 1 ref., 10 figs.

  20. Synthesis and operation of an FFT-decoupled fixed-order reversed-field pinch plasma control system based on identification data

    Energy Technology Data Exchange (ETDEWEB)

    Olofsson, K Erik J; Brunsell, Per R; Drake, James R [School of Electrical Engineering, Royal Institute of Technology (KTH), Association EURATOM-VR, Stockholm (Sweden); Witrant, Emmanuel, E-mail: erik.olofsson@ee.kth.s [Control Systems Department, UJF/GIPSA-lab, INPG/UJF Grenoble University (France)

    2010-10-15

    Recent developments and applications of system identification methods for the reversed-field pinch (RFP) machine EXTRAP T2R have yielded plasma response parameters for decoupled dynamics. These data sets are fundamental for a real-time implementable fast Fourier transform (FFT) decoupled discrete-time fixed-order strongly stabilizing synthesis as described in this work. Robustness is assessed over the data set by bootstrap calculation of the sensitivity transfer function worst-case H{sub {infinity}}-gain distribution. Output tracking and magnetohydrodynamic mode m = 1 tracking are considered in the same framework simply as two distinct weighted traces of a performance channel output-covariance matrix as derived from the closed-loop discrete-time Lyapunov equation. The behaviour of the resulting multivariable controller is investigated with dedicated T2R experiments.

  1. Thermal Signature Identification System (TheSIS)

    Science.gov (United States)

    Merritt, Scott; Bean, Brian

    2015-01-01

    We characterize both nonlinear and high order linear responses of fiber-optic and optoelectronic components using spread spectrum temperature cycling methods. This Thermal Signature Identification System (TheSIS) provides much more detail than conventional narrowband or quasi-static temperature profiling methods. This detail allows us to match components more thoroughly, detect subtle reversible shifts in performance, and investigate the cause of instabilities or irreversible changes. In particular, we create parameterized models of athermal fiber Bragg gratings (FBGs), delay line interferometers (DLIs), and distributed feedback (DFB) lasers, then subject the alternative models to selection via the Akaike Information Criterion (AIC). Detailed pairing of components, e.g. FBGs, is accomplished by means of weighted distance metrics or norms, rather than on the basis of a single parameter, such as center wavelength.

  2. Time-Delay System Identification Using Genetic Algorithm

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Seested, Glen Thane

    2013-01-01

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

  3. Model Updating Nonlinear System Identification Toolbox, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology (ZONA) proposes to develop an enhanced model updating nonlinear system identification (MUNSID) methodology that utilizes flight data with...

  4. 75 FR 25137 - Changes to Standard Numbering System, Vessel Identification System, and Boating Accident Report...

    Science.gov (United States)

    2010-05-07

    ...-2003-14963] RIN 1625-AB45 Changes to Standard Numbering System, Vessel Identification System, and... System (SNS), the Vessel Identification System (VIS), and casualty reporting; require validation of... Standard Numbering System U.S.C. United States Code VIS Vessel Identification System III. Background Coast...

  5. IDENTIFICATION SYSTEM, TRACKING AND SUPPORT FOR VESSELS ON RIVERS

    Directory of Open Access Journals (Sweden)

    SAMOILESCU Gheorghe

    2015-05-01

    Full Text Available According to the program COMPRIS (Consortium Operational Management Platform River Information Services, AIS (Automatic Identification System, RIS (River Information Services have compiled a reference model based on the perspective of navigation on the river with related information services. This paper presents a tracking and monitoring surveillance system necessary for assistance of each ship sailing in an area of interest. It shows the operating principle of the composition and role of each equipment. Transferring data to traffic monitoring authority is part of this work.

  6. Writer identification system for Ethiopic handwriting | Demoze | Zede ...

    African Journals Online (AJOL)

    Writer identification is a popular and ongoing research area having a wide variety of applications in banking, criminal justice system, access control, determining the authenticity of handwritten mails, etc. In this paper, an off-line text independent Ethiopic writer identification system has been proposed. The system uses 50 ...

  7. Modeling and identification of induction micromachines in microelectromechanical systems applications

    Energy Technology Data Exchange (ETDEWEB)

    Lyshevski, S.E. [Purdue University at Indianapolis (United States). Dept. of Electrical and Computer Engineering

    2002-11-01

    Microelectromechanical systems (MEMS), which integrate motion microstructures, radiating energy microdevices, controlling and signal processing integrated circuits (ICs), are widely used. Rotational and translational electromagnetic based micromachines are used in MEMS as actuators and sensors. Brushless high performance micromachines are the preferable choice in different MEMS applications, and therefore, synchronous and induction micromachines are the best candidates. Affordability, good performance characteristics (efficiency, controllability, robustness, reliability, power and torque densities etc.) and expanded operating envelopes result in a strong interest in the application of induction micromachines. In addition, induction micromachines can be easily fabricated using surface micromachining and high aspect ratio fabrication technologies. Thus, it is anticipated that induction micromachines, controlled using different control algorithms implemented using ICs, will be widely used in MEMS. Controllers can be implemented using specifically designed ICs to attain superior performance, maximize efficiency and controllability, minimize losses and electromagnetic interference, reduce noise and vibration, etc. In order to design controllers, the induction micromachine must be modeled, and its mathematical model parameters must be identified. Using microelectromechanics, nonlinear mathematical models are derived. This paper illustrates the application of nonlinear identification methods as applied to identify the unknown parameters of three phase induction micromachines. Two identification methods are studied. In particular, nonlinear error mapping technique and least squares identification are researched. Analytical and numerical results, as well as practical capabilities and effectiveness, are illustrated, identifying the unknown parameters of a three phase brushless induction micromotor. Experimental results fully support the identification methods. (author)

  8. 3D ear identification based on sparse representation.

    Directory of Open Access Journals (Sweden)

    Lin Zhang

    Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

  9. Identification of MIMO systems with sparse transfer function coefficients

    Science.gov (United States)

    Qiu, Wanzhi; Saleem, Syed Khusro; Skafidas, Efstratios

    2012-12-01

    We study the problem of estimating transfer functions of multivariable (multiple-input multiple-output--MIMO) systems with sparse coefficients. We note that subspace identification methods are powerful and convenient tools in dealing with MIMO systems since they neither require nonlinear optimization nor impose any canonical form on the systems. However, subspace-based methods are inefficient for systems with sparse transfer function coefficients since they work on state space models. We propose a two-step algorithm where the first step identifies the system order using the subspace principle in a state space format, while the second step estimates coefficients of the transfer functions via L1-norm convex optimization. The proposed algorithm retains good features of subspace methods with improved noise-robustness for sparse systems.

  10. Decoupling Identification for Serial Two-Link Two-Inertia System

    Science.gov (United States)

    Oaki, Junji; Adachi, Shuichi

    The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.

  11. Cavity parameters identification for TESLA control system development

    Energy Technology Data Exchange (ETDEWEB)

    Czarski, T.; Pozniak, K.T.; Romaniuk, R.S. [Warsaw Univ. of Technology (Poland). ELHEP Lab., ISE; Simrock, S. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2005-07-01

    The control system modeling for the TESLA - TeV-Energy Superconducting Linear Accelerator project has been developed for the efficient stabilization of the pulsed, accelerating EM field of the resonator. The cavity parameters identification is an essential task for the comprehensive control algorithm. The TESLA cavity simulator has been successfully implemented by applying very high speed FPGA - Field Programmable Gate Array technology. The electromechanical model of the cavity resonator includes the basic features - Lorentz force detuning and beam loading. The parameters identification bases on the electrical model of the cavity. The model is represented by the state space equation for the envelope of the cavity voltage driven by the current generator and the beam loading. For a given model structure, the over-determined matrix equation is created covering the long enough measurement range with the solution according to the least squares method. A low degree polynomial approximation is applied to estimate the time-varying cavity detuning during the pulse. The measurement channel distortion is considered, leading to the external cavity model seen by the controller. The comprehensive algorithm of the cavity parameters identification has been implemented in the Matlab system with different modes of the operation. Some experimental results have been presented for different cavity operational conditions. The following considerations have lead to the synthesis of the efficient algorithm for the cavity control system predicted for the potential FPGA technology implementation. (orig.)

  12. Cavity parameters identification for TESLA control system development

    International Nuclear Information System (INIS)

    Czarski, T.; Pozniak, K.T.; Romaniuk, R.S.

    2005-01-01

    The control system modeling for the TESLA - TeV-Energy Superconducting Linear Accelerator project has been developed for the efficient stabilization of the pulsed, accelerating EM field of the resonator. The cavity parameters identification is an essential task for the comprehensive control algorithm. The TESLA cavity simulator has been successfully implemented by applying very high speed FPGA - Field Programmable Gate Array technology. The electromechanical model of the cavity resonator includes the basic features - Lorentz force detuning and beam loading. The parameters identification bases on the electrical model of the cavity. The model is represented by the state space equation for the envelope of the cavity voltage driven by the current generator and the beam loading. For a given model structure, the over-determined matrix equation is created covering the long enough measurement range with the solution according to the least squares method. A low degree polynomial approximation is applied to estimate the time-varying cavity detuning during the pulse. The measurement channel distortion is considered, leading to the external cavity model seen by the controller. The comprehensive algorithm of the cavity parameters identification has been implemented in the Matlab system with different modes of the operation. Some experimental results have been presented for different cavity operational conditions. The following considerations have lead to the synthesis of the efficient algorithm for the cavity control system predicted for the potential FPGA technology implementation. (orig.)

  13. Lightweight autonomous chemical identification system (LACIS)

    Science.gov (United States)

    Lozos, George; Lin, Hai; Burch, Timothy

    2012-06-01

    Smiths Detection and Intelligent Optical Systems have developed prototypes for the Lightweight Autonomous Chemical Identification System (LACIS) for the US Department of Homeland Security. LACIS is to be a handheld detection system for Chemical Warfare Agents (CWAs) and Toxic Industrial Chemicals (TICs). LACIS is designed to have a low limit of detection and rapid response time for use by emergency responders and could allow determination of areas having dangerous concentration levels and if protective garments will be required. Procedures for protection of responders from hazardous materials incidents require the use of protective equipment until such time as the hazard can be assessed. Such accurate analysis can accelerate operations and increase effectiveness. LACIS is to be an improved point detector employing novel CBRNE detection modalities that includes a militaryproven ruggedized ion mobility spectrometer (IMS) with an array of electro-resistive sensors to extend the range of chemical threats detected in a single device. It uses a novel sensor data fusion and threat classification architecture to interpret the independent sensor responses and provide robust detection at low levels in complex backgrounds with minimal false alarms. The performance of LACIS prototypes have been characterized in independent third party laboratory tests at the Battelle Memorial Institute (BMI, Columbus, OH) and indoor and outdoor field tests at the Nevada National Security Site (NNSS). LACIS prototypes will be entering operational assessment by key government emergency response groups to determine its capabilities versus requirements.

  14. Dynamic mode decomposition for compressive system identification

    Science.gov (United States)

    Bai, Zhe; Kaiser, Eurika; Proctor, Joshua L.; Kutz, J. Nathan; Brunton, Steven L.

    2017-11-01

    Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data. In this work, we integrate and unify two recent innovations that extend DMD to systems with actuation and systems with heavily subsampled measurements. When combined, these methods yield a novel framework for compressive system identification, where it is possible to identify a low-order model from limited input-output data and reconstruct the associated full-state dynamic modes with compressed sensing, providing interpretability of the state of the reduced-order model. When full-state data is available, it is possible to dramatically accelerate downstream computations by first compressing the data. We demonstrate this unified framework on simulated data of fluid flow past a pitching airfoil, investigating the effects of sensor noise, different types of measurements (e.g., point sensors, Gaussian random projections, etc.), compression ratios, and different choices of actuation (e.g., localized, broadband, etc.). This example provides a challenging and realistic test-case for the proposed method, and results indicate that the dominant coherent structures and dynamics are well characterized even with heavily subsampled data.

  15. Practical Modeling and Comprehensive System Identification of a BLDC Motor

    Directory of Open Access Journals (Sweden)

    Changle Xiang

    2015-01-01

    Full Text Available The aim of this paper is to outline all the steps in a rigorous and simple procedure for system identification of BLDC motor. A practical mathematical model for identification is derived. Frequency domain identification techniques and time domain estimation method are combined to obtain the unknown parameters. The methods in time domain are founded on the least squares approximation method and a disturbance observer. Only the availability of experimental data for rotor speed and armature current are required for identification. The proposed identification method is systematically investigated, and the final identified model is validated by experimental results performed on a typical BLDC motor in UAV.

  16. Biometric identification based on feature fusion with PCA and SVM

    Science.gov (United States)

    Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

    2018-04-01

    Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

  17. Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

    Science.gov (United States)

    Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

    2012-01-01

    The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

  18. Robust uncertainty evaluation for system identification on distributed wireless platforms

    Science.gov (United States)

    Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

    2016-04-01

    data from a progressive damage action on a prestressed concrete bridge. References [1] E. Carden and P. Fanning. Vibration based condition monitoring: a review. Structural Health Monitoring, 3(4):355-377, 2004. [2] M. Döhler and L. Mevel. Efficient multi-order uncertainty computation for stochastic subspace identification. Mechanical Systems and Signal Processing, 38(2):346-366, 2013. [3] M.Döhler, L. Mevel. Modular subspace-based system identification from multi-setup measurements. IEEE Transactions on Automatic Control, 57(11):2951-2956, 2012. [4] M. Döhler, X.-B. Lam, and L. Mevel. Uncertainty quantification for modal parameters from stochastic subspace identification on multi-setup measurements. MechanicalSystems and Signal Processing, 36(2):562-581, 2013. [5] A Crinière, J Dumoulin, L Mevel, G Andrade-Barosso, M Simonin. The Cloud2SM Project.European Geosciences Union General Assembly (EGU2015), Apr 2015, Vienne, Austria. 2015.

  19. The electronic identification, signature and security of information systems

    Directory of Open Access Journals (Sweden)

    Horovèák Pavel

    2002-12-01

    Full Text Available The contribution deals with the actual methods and technologies of information and communication systems security. It introduces the overview of electronic identification elements such as static password, dynamic password and single sign-on. Into this category belong also biometric and dynamic characteristics of verified person. Widespread is authentication based on identification elements ownership, such as various cards and authentication calculators. In the next part is specified a definition and characterization of electronic signature, its basic functions and certificate categories. Practical utilization of electronic signature consists of electronic signature acquirement, signature of outgoing email message, receiving of electronic signature and verification of electronic signature. The use of electronic signature is continuously growing and in connection with legislation development it exercises in all resorts.

  20. Identification of Parameters in Active Magnetic Bearing Systems

    DEFF Research Database (Denmark)

    Lauridsen, Jonas Skjødt; Voigt, Andreas Jauernik; Mandrup-Poulsen, Christian

    2016-01-01

    A method for identifying uncertain parameters in Active Magnetic Bearing (AMB) based rotordynamic systems is introduced and adapted for experimental application. The Closed Loop Identification (CLI) method is utilised to estimate the current/force factors Ki and the displacement/force factors Ks...... as well as a time constant Τe for a first order approxima-tion of unknown actuator dynamics. To assess the precision with which CLI method can be employed to estimate AMBparameters the factors Ki, estimated using the CLI method, is compared to Ki factors attained through a Static Loading(SL) method....... The CLI method and SL method produce similar results, indicating that the CLI method is able to performclosed loop identification of uncertain AMB parameters....

  1. Line impedance estimation using model based identification technique

    DEFF Research Database (Denmark)

    Ciobotaru, Mihai; Agelidis, Vassilios; Teodorescu, Remus

    2011-01-01

    The estimation of the line impedance can be used by the control of numerous grid-connected systems, such as active filters, islanding detection techniques, non-linear current controllers, detection of the on/off grid operation mode. Therefore, estimating the line impedance can add extra functions...... into the operation of the grid-connected power converters. This paper describes a quasi passive method for estimating the line impedance of the distribution electricity network. The method uses the model based identification technique to obtain the resistive and inductive parts of the line impedance. The quasi...

  2. Process identification method based on the Z transformation

    International Nuclear Information System (INIS)

    Zwingelstein, G.

    1968-01-01

    A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [fr

  3. Synchrophasor-Based Online Coherency Identification in Voltage Stability Assessment

    Directory of Open Access Journals (Sweden)

    ADEWOLE, A. C.

    2015-11-01

    Full Text Available This paper presents and investigates a new measurement-based approach in the identification of coherent groups in load buses and synchronous generators for voltage stability assessment application in large interconnected power systems. A hybrid Calinski-Harabasz criterion and k-means clustering algorithm is developed for the determination of the cluster groups in the system. The proposed method is successfully validated by using the New England 39-bus test system. Also, the performance of the voltage stability assessment algorithm using wide area synchrophasor measurements from the key synchronous generator in each respective cluster was tested online for the prediction of the system's margin to voltage collapse using a testbed comprising of a Programmable Logic Controller (PLC in a hardware-in-the-loop configuration with the Real-Time Digital Simulator (RTDS and Phasor Measurement Units (PMUs.

  4. Secret-key and identification rates for biometric identification systems with protected templates

    NARCIS (Netherlands)

    Ignatenko, T.; Willems, F.M.J.

    2010-01-01

    In this paper we consider secret generation in biometric identification systems with protected templates. This problem is closely related to the study of the bio metric identification capacity [Willems et al., 2003] and [O’Sullivan and Sclmmid, 2002] and the common randomness generation scheme

  5. Identification of Species in Tripterygium (Celastraceae) Based on DNA Barcoding.

    Science.gov (United States)

    Zhang, Xiaomei; Li, Na; Yao, Yuanyuan; Liang, Xuming; Qu, Xianyou; Liu, Xiang; Zhu, Yingjie; Yang, Dajian; Sun, Wei

    2016-11-01

    Species of genus Tripterygium (Celastraceae) have attracted much attention owing to their excellent effect on treating autoimmune and inflammatory diseases. However, due to high market demand causing overexploitation, natural populations of genus Tripterygium have rapidly declined. Tripterygium medicinal materials are mainly collected from the wild, making the quality of medicinal materials unstable. Additionally, identification of herbal materials from Tripterygium species and their adulterants is difficult based on morphological characters. Therefore, an accurate, convenient, and stability method is urgently needed. In this wok, we developed a DNA barcoding technique to distinguish T. wilfordii HOOK. f., T. hypoglaucum (LÉVL.) HUTCH, and T. regelii SPRAGUE et TAKEDA and their adulterants based on four uniform and standard DNA regions (internal transcribed spacer 2 (ITS2), matK, rbcL, and psbA-trnH). DNA was extracted from 26 locations of fresh leaves. Phylogenetic tree was constructed with Neighbor-Joining (NJ) method, while barcoding gap was analyzed to assess identification efficiency. Compared with the other DNA barcodes applied individually or in combination, ITS2+psbA-trnH was demonstrated as the optimal barcode. T. hypoglaucum and T. wilfordii can be considered as conspecific, while T. regelii was recognized as a separate species. Furthermore, identification of commercial Tripterygium samples was conducted using BLAST against GenBank and Species Identification System for Traditional Chinese Medicine. Our results indicated that DNA barcoding is a convenient, effective, and stability method to identify and distinguish Tripterygium and its adulterants, and could be applied as the quality control for Tripterygium medicinal preparations and monitoring of the medicinal herb trade in markets.

  6. Identification of fractional order systems using modulating functions method

    KAUST Repository

    Liu, Dayan

    2013-06-01

    The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.

  7. Subspace identification of distributed clusters of homogeneous systems

    NARCIS (Netherlands)

    Yu, C.; Verhaegen, M.H.G.

    2017-01-01

    This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single

  8. Improving substructure identification accuracy of shear structures using virtual control system

    Science.gov (United States)

    Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

    2018-02-01

    Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

  9. Personal identification based on blood vessels of retinal fundus images

    Science.gov (United States)

    Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

    2008-03-01

    Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

  10. Speaker gender identification based on majority vote classifiers

    Science.gov (United States)

    Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

    2017-03-01

    Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

  11. Development of a model using the MATLAB System identification toolbox to estimate (222)Rn equilibrium factor from CR-39 based passive measurements.

    Science.gov (United States)

    Abo-Elmagd, M; Sadek, A M

    2014-12-01

    Can and Bare method is a widely used passive method for measuring the equilibrium factor F through the determination of the track density ratio between bare (D) and filtered (Do) detectors. The dimensions of the used diffusion chamber are altering the deposition ratios of Po-isotopes on the chamber walls as well as the ratios of the existing alpha emitters in air. Then the measured filtered track density and therefore the resultant equilibrium factor is changed according to the diffusion chamber dimensions. For this reason, high uncertainty was expected in the measured F using different diffusion chambers. In the present work, F is derived as a function of both track density ratio (D/Do) and the dimensions of the used diffusion chambers (its volume to the total internal surface area; V/A). The accuracy of the derived formula was verified using the black-box modeling technique via the MATLAB System identification toolbox. The results show that the uncertainty of the calculated F by using the derived formula of F (D/Do, V/A) is only 5%. The obtained uncertainty ensures the quality of the derived function to calculate F using diffusion chambers with wide range of dimensions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Fingermark evidence evaluation based on automated fingerprint identification system matching scores: the effect of different types of conditioning on likelihood ratios.

    Science.gov (United States)

    Alberink, Ivo; de Jongh, Arent; Rodriguez, Crystal

    2014-01-01

    In recent studies, the evidential value of the similarity of minutiae configurations of fingermarks and fingerprints, for example expressed by automated fingerprint identification systems (AFIS), is determined by likelihood ratios (LRs). The paper explores whether there is an effect on LRs if conditioning takes place on specified fingers, fingerprints, or fingermarks under competing hypotheses: In addition, an approach is explored where conditioning is asymmetric. Comparisons between fingerprints and simulated fingermarks with eight minutiae are performed to produce similarity score distributions for each type of conditioning, given a fixed AFIS matching algorithm. Both similarity scores and LRs are significantly different if the conditioning changes. Given a common-source scenario, "LRs" resulting from asymmetric conditioning are on average higher. The difference may reach a factor of 2000. As conditioning on a suspect's finger(print) is labor-intensive and requires a cooperating suspect, it is recommended to just condition on the number of minutiae in the fingermark. © 2013 American Academy of Forensic Sciences.

  13. Activity-Based Costing Systems for Higher Education.

    Science.gov (United States)

    Day, Dennis H.

    1993-01-01

    Examines traditional costing models utilized in higher education and pinpoints shortcomings related to proper identification of costs. Describes activity-based costing systems as a superior alternative for cost identification, measurement, and allocation. (MLF)

  14. DIRC, a new type of particle identification system For BABAR

    International Nuclear Information System (INIS)

    Schwiening, J.

    1997-12-01

    The DIRC, a new type of Cherenkov imaging device, has been selected as the primary particle identification system for the BABAR detector at the asymmetric B-factory, PEP-II. It is based on total internal reflection and uses long, rectangular bars made from synthetic fused silica as Cherenkov radiators and light guides. In this paper, the principles of the DIRC ring imaging Cherenkov technique are explained and results from the prototype program are presented. The studies of the optical properties and radiation hardness of the quartz radiators are described, followed by a discussion of the detector design

  15. Reduction in specimen labeling errors after implementation of a positive patient identification system in phlebotomy.

    Science.gov (United States)

    Morrison, Aileen P; Tanasijevic, Milenko J; Goonan, Ellen M; Lobo, Margaret M; Bates, Michael M; Lipsitz, Stuart R; Bates, David W; Melanson, Stacy E F

    2010-06-01

    Ensuring accurate patient identification is central to preventing medical errors, but it can be challenging. We implemented a bar code-based positive patient identification system for use in inpatient phlebotomy. A before-after design was used to evaluate the impact of the identification system on the frequency of mislabeled and unlabeled samples reported in our laboratory. Labeling errors fell from 5.45 in 10,000 before implementation to 3.2 in 10,000 afterward (P = .0013). An estimated 108 mislabeling events were prevented by the identification system in 1 year. Furthermore, a workflow step requiring manual preprinting of labels, which was accompanied by potential labeling errors in about one quarter of blood "draws," was removed as a result of the new system. After implementation, a higher percentage of patients reported having their wristband checked before phlebotomy. Bar code technology significantly reduced the rate of specimen identification errors.

  16. The Automated System for Identification of License Plates of Cars

    Directory of Open Access Journals (Sweden)

    FRATAVCHAN, V.

    2008-04-01

    Full Text Available The paper focuses on the automated traffic rule control system. It examines the basic scheme of the system, basic constituents, principles of constituent interactions, search methods of moving objects, localization, and identification of the license plate.

  17. Optical Automatic Car Identification (OACI) : Volume 1. Advanced System Specification.

    Science.gov (United States)

    1978-12-01

    A performance specification is provided in this report for an Optical Automatic Car Identification (OACI) scanner system which features 6% improved readability over existing industry scanner systems. It also includes the analysis and rationale which ...

  18. Nonlinear dynamical system identification using unscented Kalman filter

    Science.gov (United States)

    Rehman, M. Javvad ur; Dass, Sarat Chandra; Asirvadam, Vijanth Sagayan

    2016-11-01

    Kalman Filter is the most suitable choice for linear state space and Gaussian error distribution from decades. In general practical systems are not linear and Gaussian so these assumptions give inconsistent results. System Identification for nonlinear dynamical systems is a difficult task to perform. Usually, Extended Kalman Filter (EKF) is used to deal with non-linearity in which Jacobian method is used for linearizing the system dynamics, But it has been observed that in highly non-linear environment performance of EKF is poor. Unscented Kalman Filter (UKF) is proposed here as a better option because instead of analytical linearization of state space, UKF performs statistical linearization by using sigma point calculated from deterministic samples. Formation of the posterior distribution is based on the propagation of mean and covariance through sigma points.

  19. System Identification of Flight Mechanical Characteristics

    OpenAIRE

    Larsson, Roger

    2013-01-01

    With the demand for more advanced fighter aircraft, relying on relaxed stability or even unstable flight mechanical characteristics to gain flight performance, more focus has been put on model-based system engineering to help with the design work. The flight control system design is one important part that relies on this modeling. Therefore it has become more important to develop flight mechanical models that are highly accurate in the whole flight envelop. For today’s newly developed fighter...

  20. Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

    Science.gov (United States)

    Geng, Xiangyi; Lu, Shizeng; Jiang, Mingshun; Sui, Qingmei; Lv, Shanshan; Xiao, Hang; Jia, Yuxi; Jia, Lei

    2018-06-01

    A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

  1. Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

    Science.gov (United States)

    Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

    2018-03-01

    Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

  2. Application of identification techniques to remote manipulator system flight data

    Science.gov (United States)

    Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

    1983-01-01

    This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

  3. Identification of Coupled Map Lattice Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xie

    2016-01-01

    Full Text Available A novel approach for the parameter identification of coupled map lattice (CML based on compressed sensing is presented in this paper. We establish a meaningful connection between these two seemingly unrelated study topics and identify the weighted parameters using the relevant recovery algorithms in compressed sensing. Specifically, we first transform the parameter identification problem of CML into the sparse recovery problem of underdetermined linear system. In fact, compressed sensing provides a feasible method to solve underdetermined linear system if the sensing matrix satisfies some suitable conditions, such as restricted isometry property (RIP and mutual coherence. Then we give a low bound on the mutual coherence of the coefficient matrix generated by the observed values of CML and also prove that it satisfies the RIP from a theoretical point of view. If the weighted vector of each element is sparse in the CML system, our proposed approach can recover all the weighted parameters using only about M samplings, which is far less than the number of the lattice elements N. Another important and significant advantage is that if the observed data are contaminated with some types of noises, our approach is still effective. In the simulations, we mainly show the effects of coupling parameter and noise on the recovery rate.

  4. Evolution of the US Coast Guard's oil identification system

    International Nuclear Information System (INIS)

    Hendrick, M.S.; Reilly, T.R.

    1993-01-01

    The U.S. Coast Guard, tasked with the development of open-quotes procedures and techniques to be employed in identifying ... oil and hazardous substances . . . open-quotes by the 1972 Federal Water Pollution Control Act (FWPCA), developed the Oil Identification System (OIS). The OIS was based on four analytical laboratory techniques: infrared (IR) and fluorescence (FL) spectroscopy, gas chromatography (GC), and thin- layer chromatography (TLC). A Central Oil Identification Laboratory (COIL) began operation in 1977, and field laboratories (FOILS) using two of the techniques (FL and TLC) were established in many Marine Safety Offices to screen possible sources. Development of the OIS was documented in two formal reports, in 1974 and 1977. The current implementation of the OIS at COIL is still based on a multimethod approach, but it incorporates today's state-of-the-art technology and responds to the current needs of the Coast Guard. One pervasive force for change has been the affordability of computers. The rapid development of computerized instruments has resulted in improvements in the performance, ruggedness, and prices of analytical laboratory equipment. All the instruments in the authors' laboratory at the present time are interfaced to or have internal computerized data-handling systems. Fourier-transform infrared spectrometers (FTIR) have replaced older mechanically scanning, dispersive IR instruments. High-performance liquid chromatography (HPLC) has replaced TLC completely. A gas chromatography/mass spectrometer (GC/MS), a room-size research tool in 1977, sits on a benchtop in the laboratory today, and a standard method for oil identification is being developed for this technique. Laboratory strategies are now based on finding the most efficient use of resources, as rapid response times are not necessary in all cases. It may also be possible in the near future to resume field testing

  5. Automatic Identification System modular receiver for academic purposes

    Science.gov (United States)

    Cabrera, F.; Molina, N.; Tichavska, M.; Araña, V.

    2016-07-01

    The Automatic Identification System (AIS) standard is encompassed within the Global Maritime Distress and Safety System (GMDSS), in force since 1999. The GMDSS is a set of procedures, equipment, and communication protocols designed with the aim of increasing the safety of sea crossings, facilitating navigation, and the rescue of vessels in danger. The use of this system not only is increasingly attractive to security issues but also potentially creates intelligence products throughout the added-value information that this network can transmit from ships on real time (identification, position, course, speed, dimensions, flag, among others). Within the marine electronics market, commercial receivers implement this standard and allow users to access vessel-broadcasted information if in the range of coverage. In addition to satellite services, users may request actionable information from private or public AIS terrestrial networks where real-time feed or historical data can be accessed from its nodes. This paper describes the configuration of an AIS receiver based on a modular design. This modular design facilitates the evaluation of specific modules and also a better understanding of the standard and the possibility of changing hardware modules to improve the performance of the prototype. Thus, the aim of this paper is to describe the system's specifications, its main hardware components, and to present educational didactics on the setup and use of a modular and terrestrial AIS receiver. The latter is for academic purposes and in undergraduate studies such as electrical engineering, telecommunications, and maritime studies.

  6. Entropy based file type identification and partitioning

    Science.gov (United States)

    2017-06-01

    energy spectrum,” Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, pp. 288–293, 2016...ABBREVIATIONS AES Advanced Encryption Standard ANN Artificial Neural Network ASCII American Standard Code for Information Interchange CWT...the identification of file types and file partitioning. This approach has applications in cybersecurity as it allows for a quick determination of

  7. Development of a model using the MATLAB System identification toolbox to estimate 222Rn equilibrium factor from CR-39 based passive measurements

    International Nuclear Information System (INIS)

    Abo-Elmagd, M.; Sadek, A.M.

    2014-01-01

    Can and Bare method is a widely used passive method for measuring the equilibrium factor F through the determination of the track density ratio between bare (D) and filtered (D o ) detectors. The dimensions of the used diffusion chamber are altering the deposition ratios of Po-isotopes on the chamber walls as well as the ratios of the existing alpha emitters in air. Then the measured filtered track density and therefore the resultant equilibrium factor is changed according to the diffusion chamber dimensions. For this reason, high uncertainty was expected in the measured F using different diffusion chambers. In the present work, F is derived as a function of both track density ratio (D/D o ) and the dimensions of the used diffusion chambers (its volume to the total internal surface area; V/A). The accuracy of the derived formula was verified using the black-box modeling technique via the MATLAB System identification toolbox. The results show that the uncertainty of the calculated F by using the derived formula of F (D/D o , V/A) is only 5%. The obtained uncertainty ensures the quality of the derived function to calculate F using diffusion chambers with wide range of dimensions. - Highlights: • The manuscript is aimed to develop the Can and Bare method for measuring the equilibrium factor F. • A new formula F (D/D o , V/A) is obtained taking the dimension of the used cup (V/A) into consideration. • The accuracy of the derived formula was verified using the black-box modeling technique via the MATLAB. • The derived function covers the range of the widely used diffusion chambers (r ≤ 3.5 cm and h ≤ 10 cm). • The reproducibility of F estimated using this model is quite good (5% deviation) for different 8 cups

  8. Intelligent system for accident identification in NPP

    International Nuclear Information System (INIS)

    Hernandez, J.L.

    1998-01-01

    Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre-operational Probabilistic safety Assessment and the Thermal hydraulic Safety Analysis of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

  9. Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

    Science.gov (United States)

    Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

    2017-01-01

    Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

  10. Parameter estimation techniques for LTP system identification

    Science.gov (United States)

    Nofrarias Serra, Miquel

    LISA Pathfinder (LPF) is the precursor mission of LISA (Laser Interferometer Space Antenna) and the first step towards gravitational waves detection in space. The main instrument onboard the mission is the LTP (LISA Technology Package) whose scientific goal is to test LISA's drag-free control loop by reaching a differential acceleration noise level between two masses in √ geodesic motion of 3 × 10-14 ms-2 / Hz in the milliHertz band. The mission is not only challenging in terms of technology readiness but also in terms of data analysis. As with any gravitational wave detector, attaining the instrument performance goals will require an extensive noise hunting campaign to measure all contributions with high accuracy. But, opposite to on-ground experiments, LTP characterisation will be only possible by setting parameters via telecommands and getting a selected amount of information through the available telemetry downlink. These two conditions, high accuracy and high reliability, are the main restrictions that the LTP data analysis must overcome. A dedicated object oriented Matlab Toolbox (LTPDA) has been set up by the LTP analysis team for this purpose. Among the different toolbox methods, an essential part for the mission are the parameter estimation tools that will be used for system identification during operations: Linear Least Squares, Non-linear Least Squares and Monte Carlo Markov Chain methods have been implemented as LTPDA methods. The data analysis team has been testing those methods with a series of mock data exercises with the following objectives: to cross-check parameter estimation methods and compare the achievable accuracy for each of them, and to develop the best strategies to describe the physics underlying a complex controlled experiment as the LTP. In this contribution we describe how these methods were tested with simulated LTP-like data to recover the parameters of the model and we report on the latest results of these mock data exercises.

  11. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

    Directory of Open Access Journals (Sweden)

    Tae-Hyoung Kim

    2017-01-01

    Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

  12. Identification of protective actions to reduce the vulnerability of safety-critical systems to malevolent acts: A sensitivity-based decision-making approach

    International Nuclear Information System (INIS)

    Wang, Tai-Ran; Pedroni, Nicola; Zio, Enrico

    2016-01-01

    A classification model based on the Majority Rule Sorting method has been previously proposed by the authors to evaluate the vulnerability of safety-critical systems (e.g., nuclear power plants) with respect to malevolent intentional acts. In this paper, we consider a classification model previously proposed by the authors based on the Majority Rule Sorting method to evaluate the vulnerability of safety-critical systems (e.g., nuclear power plants) with respect to malevolent intentional acts. The model is here used as the basis for solving an inverse classification problem aimed at determining a set of protective actions to reduce the level of vulnerability of the safety-critical system under consideration. To guide the choice of the set of protective actions, sensitivity indicators are originally introduced as measures of the variation in the vulnerability class that a safety-critical system is expected to undergo after the application of a given set of protective actions. These indicators form the basis of an algorithm to rank different combinations of actions according to their effectiveness in reducing the safety-critical systems vulnerability. Results obtained using these indicators are presented with regard to the application of: (i) one identified action at a time, (ii) all identified actions at the same time or (iii) a random combination of identified actions. The results are presented with reference to a fictitious example considering nuclear power plants as the safety-critical systems object of the analysis. - Highlights: • We use a hierarchical framework to represent the vulnerability. • We use an empirical classification model to evaluate vulnerability. • Sensitivity indicators are introduced to rank protective actions. • Constraints (e.g., budget limitations) are accounted for. • Method is applied to fictitious Nuclear Power Plants.

  13. Encryption and validation of multiple signals for optical identification systems

    Energy Technology Data Exchange (ETDEWEB)

    Perez-Cabre, E [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Millan, M S [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Javidi, B [University of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, CT 06269 Storrs (United States)

    2007-07-15

    Multifactor encryption-authentication technique reinforces optical security by allowing the simultaneous A N D-verification of more than one primary image. Instead of basing the identification on a unique signature or piece of information, our goal is to authenticate a given person, object, vehicle by the simultaneous recognition of several factors. Some of them are intrinsic to the person and object or vehicle under control. Other factors, act as keys of the authentication step. Such a system is proposed for situations such as the access control to restricted areas, where the demand of security is high. The multifactor identification method involves double random-phase encoding, fully phase-based encryption and a combined nonlinear joint transform correlator and a classical 4f-correlator for simultaneous recognition and authentication of multiple images. The encoded signal fulfils the general requirements of invisible content, extreme difficulty in counterfeiting and real-time automatic verification. Four reference double-phase encoded images are compared with the retrieved input images obtained in situ from the person or the vehicle whose authentication is wanted and from a database. A recognition step based on the correlation between the signatures and the stored references determines the authentication or rejection of the person and object under surveillance.

  14. Encryption and validation of multiple signals for optical identification systems

    International Nuclear Information System (INIS)

    Perez-Cabre, E; Millan, M S; Javidi, B

    2007-01-01

    Multifactor encryption-authentication technique reinforces optical security by allowing the simultaneous A N D-verification of more than one primary image. Instead of basing the identification on a unique signature or piece of information, our goal is to authenticate a given person, object, vehicle by the simultaneous recognition of several factors. Some of them are intrinsic to the person and object or vehicle under control. Other factors, act as keys of the authentication step. Such a system is proposed for situations such as the access control to restricted areas, where the demand of security is high. The multifactor identification method involves double random-phase encoding, fully phase-based encryption and a combined nonlinear joint transform correlator and a classical 4f-correlator for simultaneous recognition and authentication of multiple images. The encoded signal fulfils the general requirements of invisible content, extreme difficulty in counterfeiting and real-time automatic verification. Four reference double-phase encoded images are compared with the retrieved input images obtained in situ from the person or the vehicle whose authentication is wanted and from a database. A recognition step based on the correlation between the signatures and the stored references determines the authentication or rejection of the person and object under surveillance

  15. An overview of modal-based damage identification methods

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, C.R.; Doebling, S.W. [Los Alamos National Lab., NM (United States). Engineering Analysis Group

    1997-09-01

    This paper provides an overview of methods that examine changes in measured vibration response to detect, locate, and characterize damage in structural and mechanical systems. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is first provided. The methods are then categorized according to various criteria such as the level of damage detection provided, model-based vs. non-model-based methods and linear vs. nonlinear methods. This overview is limited to methods that can be adapted to a wide range of structures (i.e., are not dependent on a particular assumed model form for the system such as beam-bending behavior and methods and that are not based on updating finite element models). Next, the methods are described in general terms including difficulties associated with their implementation and their fidelity. Past, current and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of modal-based damage identification.

  16. System Identification of a Non-Uniformly Sampled Multi-Rate System in Aluminium Electrolysis Cells

    Directory of Open Access Journals (Sweden)

    Håkon Viumdal

    2014-07-01

    Full Text Available Standard system identification algorithms are usually designed to generate mathematical models with equidistant sampling instants, that are equal for both input variables and output variables. Unfortunately, real industrial data sets are often disrupted by missing samples, variations of sampling rates in the different variables (also known as multi-rate systems, and intermittent measurements. In industries with varying events based maintenance or manual operational measures, intermittent measurements are performed leading to uneven sampling rates. Such is the case with aluminium smelters, where in addition the materials fed into the cell create even more irregularity in sampling. Both measurements and feeding are mostly manually controlled. A simplified simulation of the metal level in an aluminium electrolysis cell is performed based on mass balance considerations. System identification methods based on Prediction Error Methods (PEM such as Ordinary Least Squares (OLS, and the sub-space method combined Deterministic and Stochastic system identification and Realization (DSR, and its variants are applied to the model of a single electrolysis cell as found in the aluminium smelters. Aliasing phenomena due to large sampling intervals can be crucial in avoiding unsuitable models, but with knowledge about the system dynamics, it is easier to optimize the sampling performance, and hence achieve successful models. The results based on the simulation studies of molten aluminium height in the cells using the various algorithms give results which tally well with the synthetic data sets used. System identification on a smaller data set from a real plant is also implemented in this work. Finally, some concrete suggestions are made for using these models in the smelters.

  17. New methodology for a person identification system

    Indian Academy of Sciences (India)

    Abstract. Reliable person identification is a key factor for any safety measure. Unlike other biometrics such as the palm, retina, gait, face and fingerprints, the characteristic of the iris is stable in a person's lifetime. Iris patterns are chaotically distributed and well suited for recognizing persons throughout their lifetime with.

  18. SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

    Directory of Open Access Journals (Sweden)

    Matthew C. McClure

    2018-03-01

    Full Text Available A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS, they can validate the wrong parent at ≤1% misconcordance rate levels, indicating that more SNP are needed if a more accurate pedigree is required. With rapidly increasing numbers of cattle being genotyped in Ireland that represent 61 B. taurus breeds from a wide range of farm types: beef/dairy, AI/pedigree/commercial, purebred/crossbred, and large to small herd size the Irish Cattle Breeding Federation (ICBF analyzed different SNP densities to determine that at a minimum ≥500 SNP are needed to consistently predict only one set of parents at a ≤1% misconcordance rate. For parentage validation and prediction ICBF uses 800 SNP (ICBF800 selected based on SNP clustering quality, ISAG200 inclusion, call rate (CR, and minor allele frequency (MAF in the Irish cattle population. Large datasets require sample and SNP quality control (QC. Most publications only deal with SNP QC via CR, MAF, parent-progeny conflicts, and Hardy-Weinberg deviation, but not sample QC. We report here parentage, SNP QC, and a genomic sample QC pipelines to deal with the unique challenges of >1 million genotypes from a national herd such as SNP genotype errors from mis-tagging of animals, lab errors, farm errors, and multiple other issues that can arise. We divide the pipeline into two parts: a Genotype QC and an Animal QC pipeline. The Genotype QC identifies samples with low call rate, missing or mixed genotype classes (no BB genotype or ABTG alleles present, and low genotype frequencies. The Animal QC handles situations where the genotype might not belong to the listed individual by identifying: >1 non

  19. Modeling of Biometric Identification System Using the Colored Petri Nets

    Science.gov (United States)

    Petrosyan, G. R.; Ter-Vardanyan, L. A.; Gaboutchian, A. V.

    2015-05-01

    In this paper we present a model of biometric identification system transformed into Petri Nets. Petri Nets, as a graphical and mathematical tool, provide a uniform environment for modelling, formal analysis, and design of discrete event systems. The main objective of this paper is to introduce the fundamental concepts of Petri Nets to the researchers and practitioners, both from identification systems, who are involved in the work in the areas of modelling and analysis of biometric identification types of systems, as well as those who may potentially be involved in these areas. In addition, the paper introduces high-level Petri Nets, as Colored Petri Nets (CPN). In this paper the model of Colored Petri Net describes the identification process much simpler.

  20. Model Updating Nonlinear System Identification Toolbox, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology proposes to develop an enhanced model updating nonlinear system identification (MUNSID) methodology by adopting the flight data with state-of-the-art...

  1. A study on switched linear system identification using game ...

    African Journals Online (AJOL)

    A study on switched linear system identification using game-theoretic strategies and neural computing. ... This study deals with application of game-theoretic strategies and neural computing to switched linear ... AJOL African Journals Online.

  2. Compressive System Identification in the Linear Time-Invariant framework

    KAUST Repository

    Toth, Roland; Sanandaji, Borhan M.; Poolla, Kameshwar; Vincent, Tyrone L.

    2011-01-01

    Selection of an efficient model parametrization (model order, delay, etc.) has crucial importance in parametric system identification. It navigates a trade-off between representation capabilities of the model (structural bias) and effects of over-parametrization

  3. Advanced 3D Object Identification System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Optra will build an Advanced 3D Object Identification System utilizing three or more high resolution imagers spaced around a launch platform. Data from each imager...

  4. Applications of radio frequency identification systems in the mining industry

    Energy Technology Data Exchange (ETDEWEB)

    Hind, D J [Davis Derby Ltd., Derby (United Kingdom)

    1995-07-01

    Radio Frequency Identification Systems (RFID) are one of the automatic data capture technologies taking over from bar codes and magnetic swipe cards in many applications involving automatic hands free operation in arduous environments. RFID systems are based on the use of miniature radio transponders carrying encoded electronic data that is used to uniquely identify the identity of transponders. This paper reviews the types of system available and compares the various techniques involved in the different systems. The various types of transponder are described including the latest state of the art passive read/write high performance types. A review of the history of RFID systems in the mining industry is also given in the paper. The problems involved in designing and certifying a system for use in hazardous areas are also described, with particular reference to the problems of inadvertent detonator ignition by radio systems. Applications of RFID systems in the mining industry are described in considerable detail, covering applications both on the surface and underground. 1 ref., 12 figs., 1 tab.

  5. Frequency Response Function Based Damage Identification for Aerospace Structures

    Science.gov (United States)

    Oliver, Joseph Acton

    Structural health monitoring technologies continue to be pursued for aerospace structures in the interests of increased safety and, when combined with health prognosis, efficiency in life-cycle management. The current dissertation develops and validates damage identification technology as a critical component for structural health monitoring of aerospace structures and, in particular, composite unmanned aerial vehicles. The primary innovation is a statistical least-squares damage identification algorithm based in concepts of parameter estimation and model update. The algorithm uses frequency response function based residual force vectors derived from distributed vibration measurements to update a structural finite element model through statistically weighted least-squares minimization producing location and quantification of the damage, estimation uncertainty, and an updated model. Advantages compared to other approaches include robust applicability to systems which are heavily damped, large, and noisy, with a relatively low number of distributed measurement points compared to the number of analytical degrees-of-freedom of an associated analytical structural model (e.g., modal finite element model). Motivation, research objectives, and a dissertation summary are discussed in Chapter 1 followed by a literature review in Chapter 2. Chapter 3 gives background theory and the damage identification algorithm derivation followed by a study of fundamental algorithm behavior on a two degree-of-freedom mass-spring system with generalized damping. Chapter 4 investigates the impact of noise then successfully proves the algorithm against competing methods using an analytical eight degree-of-freedom mass-spring system with non-proportional structural damping. Chapter 5 extends use of the algorithm to finite element models, including solutions for numerical issues, approaches for modeling damping approximately in reduced coordinates, and analytical validation using a composite

  6. Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

    Directory of Open Access Journals (Sweden)

    Xiaoming Xi

    2013-07-01

    Full Text Available Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT, which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

  7. Simulation and Domain Identification of Sea Ice Thermodynamic System

    Directory of Open Access Journals (Sweden)

    Bing Tan

    2012-01-01

    Full Text Available Based on the measured data and characteristics of sea ice temperature distribution in space and time, this study is intended to consider a parabolic partial differential equation of the thermodynamic field of sea ice (coupled by snow, ice, and sea water layers with a time-dependent domain and its parameter identification problem. An optimal model with state constraints is presented with the thicknesses of snow and sea ice as parametric variables and the deviation between the calculated and measured sea ice temperatures as the performance criterion. The unique existence of the weak solution of the thermodynamic system is proved. The properties of the identification problem and the existence of the optimal parameter are discussed, and the one-order necessary condition is derived. Finally, based on the nonoverlapping domain decomposition method and semi-implicit difference scheme, an optimization algorithm is proposed for the numerical simulation. Results show that the simulated temperature of sea ice fit well with the measured data, and the better fit is corresponding to the deeper sea ice.

  8. Study of Biometric Identification Method Based on Naked Footprint

    Directory of Open Access Journals (Sweden)

    Raji Rafiu King

    2013-10-01

    Full Text Available The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow (GVF) snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi: 10.12777/ijse.5.2.29-35 How to cite this article: King

  9. System identification of the Arabidopsis plant circadian system

    Science.gov (United States)

    Foo, Mathias; Somers, David E.; Kim, Pan-Jun

    2015-02-01

    The circadian system generates an endogenous oscillatory rhythm that governs the daily activities of organisms in nature. It offers adaptive advantages to organisms through a coordination of their biological functions with the optimal time of day. In this paper, a model of the circadian system in the plant Arabidopsis (species thaliana) is built by using system identification techniques. Prior knowledge about the physical interactions of the genes and the proteins in the plant circadian system is incorporated in the model building exercise. The model is built by using primarily experimentally-verified direct interactions between the genes and the proteins with the available data on mRNA and protein abundances from the circadian system. Our analysis reveals a great performance of the model in predicting the dynamics of the plant circadian system through the effect of diverse internal and external perturbations (gene knockouts and day-length changes). Furthermore, we found that the circadian oscillatory rhythm is robust and does not vary much with the biochemical parameters except those of a light-sensitive protein P and a transcription factor TOC1. In other words, the circadian rhythmic profile is largely a consequence of the network's architecture rather than its particular parameters. Our work suggests that the current experimental knowledge of the gene-to-protein interactions in the plant Arabidopsis, without considering any additional hypothetical interactions, seems to suffice for system-level modeling of the circadian system of this plant and to present an exemplary platform for the control of network dynamics in complex living organisms.

  10. Closed-loop System Identification with New Sensors

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2008-01-01

    This paper deals with system identification of new system dynamics revealed by online introduction of new sensors in existing multi-variable linear control systems. The so-called "Hansen Scheme" utilises the dual Youla-Kucera parameterisation of all systems stabilised by a given linear controller...... to transform closed-loop system identification problems into open-loop-like problems. We show that this scheme can be formally extended to accomodate extra sensors in a nice way. The approach is illustrated on a simple simulation example....

  11. Jet identification based on probability calculations using Bayes' theorem

    International Nuclear Information System (INIS)

    Jacobsson, C.; Joensson, L.; Lindgren, G.; Nyberg-Werther, M.

    1994-11-01

    The problem of identifying jets at LEP and HERA has been studied. Identification using jet energies and fragmentation properties was treated separately in order to investigate the degree of quark-gluon separation that can be achieved by either of these approaches. In the case of the fragmentation-based identification, a neural network was used, and a test of the dependence on the jet production process and the fragmentation model was done. Instead of working with the separation variables directly, these have been used to calculate probabilities of having a specific type of jet, according to Bayes' theorem. This offers a direct interpretation of the performance of the jet identification and provides a simple means of combining the results of the energy- and fragmentation-based identifications. (orig.)

  12. A physiologically based nonhomogeneous Poisson counter model of visual identification

    DEFF Research Database (Denmark)

    Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus

    2018-01-01

    A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are ......A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects...... that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model...

  13. Eye movement identification based on accumulated time feature

    Science.gov (United States)

    Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

    2017-06-01

    Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

  14. Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

    Science.gov (United States)

    Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

    2017-02-01

    We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

  15. Bioimpedance-based identification of malnutrition using fuzzy logic

    International Nuclear Information System (INIS)

    Wieskotten, S; Isermann, R; Heinke, S; Wabel, P; Moissl, U; Becker, J; Pirlich, M; Keymling, M

    2008-01-01

    Protein-energy malnutrition reduces the quality of life, lengthens the time in hospital and dramatically increases mortality. Currently there is no simple and objective method available for assessing nutritional status and identifying malnutrition. The aim of this work is to develop a novel assistance system that supports the physician in the assessment of the nutritional status. Therefore, three subject groups were investigated: the first group consisted of 688 healthy subjects. Two additional groups consisted of 707 patients: 94 patients with primary diseases that are known to cause malnutrition, and 613 patients from a hospital admission screening. In all subjects bioimpedance spectroscopy measurements were performed, and the body composition was calculated. Additionally, in all patients the nutritional status was assessed by the subjective global assessment score. These data are used for the development and validation of the assistance system. The basic idea of the system is that nutritional status is reflected by body composition. Hence, features of the nutritional status, based on the body composition, are determined and compared with reference ranges, derived from healthy subjects' data. The differences are evaluated by a fuzzy logic system or a decision tree in order to identify malnourished patients. The novel assistance system allows the identification of malnourished patients, and it can be applied for screening and monitoring of the nutritional status of hospital patients

  16. A portable system for nuclear, chemical agent, and explosives identification

    International Nuclear Information System (INIS)

    Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.; Caffrey, A.J.

    2001-01-01

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electromechanically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine a prompt-gamma neutron-activation analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

  17. A Portable System for Nuclear, Chemical Agent and Explosives Identification

    International Nuclear Information System (INIS)

    Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Caffrey, A.J.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.

    2000-01-01

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electrochemically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine an active neutron interrogation and analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

  18. A portable air jet actuator device for mechanical system identification

    Science.gov (United States)

    Belden, Jesse; Staats, Wayne L.; Mazumdar, Anirban; Hunter, Ian W.

    2011-03-01

    System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon—the Coandă effect—is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use.

  19. Applications of radio frequency identification systems in the mining industry

    Energy Technology Data Exchange (ETDEWEB)

    Hind, D [Davis Derby Limited (United Kingdom)

    1994-12-31

    The paper describes the application of Radio Frequency Identification (RFID) systems in the mining industry for both surface and underground mines. The history of the RFID system, types available, the transponder, and the various techniques used are described and compared. The design and certification of a system for use in a hazardous area are described, noting the hazard of inadvertent detonator ignition. 2 refs.

  20. Online identification of continuous bimodal and trimodal piecewise affine systems

    NARCIS (Netherlands)

    Le, Q.T.; van den Boom, A.J.J.; Baldi, S.; Rantzer, Anders; Bagterp Jørgensen, John; Stoustrup, Jakob

    2016-01-01

    This paper investigates the identification of continuous piecewise affine systems in state space form with jointly unknown partition and subsystem matrices. The partition of the system is generated by the so-called centers. By representing continuous piecewise affine systems in the max-form and

  1. Elastic tunneling identification through crossings, anti-crossings and splitting of states in the complex electronic current of systems based on mesoscopic molecules

    Science.gov (United States)

    López, Luis I. A.; Mendoza, Michel; Ujevic, Sebastian

    2013-09-01

    We have systematically studied the conductance σ( E,B) and the electronic current line shapes J( V ex ) through complex mesoscopic molecules in an elastic resonant tunneling regime. The studied systems are based on GaAs/AlGaAs hetero-structures, with several discrete states in each coupled mesoscopic molecule. The molecules were formed using different wells and barrier widths. These systems allow effective couplings and uncouplings that lead to elastic processes as a function of the electronic potential V ex and magnetic field B. In this situation, the J( V ex ) and σ( E, B) curves exhibit a sequence of peaks of difficult interpretation, in which crossings and anti-crossings (a splitting if it is generated in the resonance condition) of states contribute in a way that they cannot be easily identified. Performing a systematic analysis of the evolution of these states (before the resonance condition), we were able to determine the origin of these current peaks. We have found that the coupling of states (anti-crossing) around the resonance region can be identified as a broad mirrored- D line shape in the J( V ex ) curves. The mirrored- D line shape peaks can be clearly differentiated from the neighboring peaks because the last ones follow a very defined increasing sequence in their intensities and widths. Also, this behavior (fingerprint) can be used to identify possible splitting of states in the J( V ex ). The splittings that are generated between states with different quantum numbers (quantum numbers associated to the individual well) follow an unexpected opposite behavior when compared with those generated between states with the same quantum numbers (quasi-miniband). All these results are also observed in the conductance σ( E, B) associated with complex mesoscopic molecules based on a two-dimensional electron gas.

  2. A simple data base for identification of risk profiles

    Energy Technology Data Exchange (ETDEWEB)

    Munganahalli, D.

    1996-12-31

    Sedco Forex is a drilling contractor that operates approximately 80 rigs on land and offshore worldwide. The HSE management system developed by Sedco Forex is an effort to prevent accidents and minimize losses. An integral part of the HSE management system is establishing risk profiles and thereby minimizing risk and reducing loss exposures. Risk profiles are established based on accident reports, potential accident reports and other risk identification reports (RIR) like the Du Pont STOP system. A rig could fill in as many as 30 accident reports, 30 potential accident reports and 500 STOP cards each year. Statistics are important for an HSE management system, since they are indicators of success or failure of HSE systems. It is however difficult to establish risk profiles based on statistical information, unless tools are available at the rig site to aid with the analysis. Risk profiles are then used to identify important areas in the operation that may require specific attention to minimize the loss exposure. Programs to address the loss exposure can then be identified and implemented with either a local or corporate approach. In January 1995, Sedco Forex implemented a uniform HSE Database on all the rigs worldwide. In one year companywide, the HSE database would contain information on approximately 500 accident and potential accident reports, and 10,000 STOP cards. This paper demonstrates the salient features of the database and describes how it has helped in establishing key risk profiles. It also shows a recent example of how risk profiles have been established at the corporate level and used to identify the key contributing factors to hands and finger injuries. Based on this information, a campaign was launched to minimize the frequency of occurrence and associated loss attributed to hands and fingers accidents.

  3. CEAI: CCM-based email authorship identification model

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani

    2013-11-01

    Full Text Available In this paper we present a model for email authorship identification (EAI by employing a Cluster-based Classification (CCM technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature set to include some more interesting and effective features for email authorship identification (e.g., the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell. We also included Info Gain feature selection based content features. It is observed that the use of such features in the authorship identification process has a positive impact on the accuracy of the authorship identification task. We performed experiments to justify our arguments and compared the results with other base line models. Experimental results reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM-based models, as well as the models proposed by Iqbal et al. (2010, 2013 [1,2]. The proposed model attains an accuracy rate of 94% for 10 authors, 89% for 25 authors, and 81% for 50 authors, respectively on Enron dataset, while 89.5% accuracy has been achieved on authors’ constructed real email dataset. The results on Enron dataset have been achieved on quite a large number of authors as compared to the models proposed by Iqbal et al. [1,2].

  4. 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

  5. Identification of System Parameters by the Random Decrement Technique

    DEFF Research Database (Denmark)

    Brincker, Rune; Kirkegaard, Poul Henning; Rytter, Anders

    1991-01-01

    -Walker equations and finally, least-square fitting of the theoretical correlation function. The results are compared to the results of fitting an Auto Regressive Moving Average (ARMA) model directly to the system output from a single-degree-of-freedom system loaded by white noise.......The aim of this paper is to investigate and illustrate the possibilities of using correlation functions estimated by the Random Decrement Technique as a basis for parameter identification. A two-stage system identification system is used: first, the correlation functions are estimated by the Random...... Decrement Technique, and then the system parameters are identified from the correlation function estimates. Three different techniques are used in the parameter identification process: a simple non-parametric method, estimation of an Auto Regressive (AR) model by solving an overdetermined set of Yule...

  6. 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.

  7. System identification of timber masonry walls using shaking table test

    Science.gov (United States)

    Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

    2017-04-01

    Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

  8. 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.

  9. Compressive System Identification in the Linear Time-Invariant framework

    KAUST Repository

    Toth, Roland

    2011-12-01

    Selection of an efficient model parametrization (model order, delay, etc.) has crucial importance in parametric system identification. It navigates a trade-off between representation capabilities of the model (structural bias) and effects of over-parametrization (variance increase of the estimates). There exists many approaches to this widely studied problem in terms of statistical regularization methods and information criteria. In this paper, an alternative ℓ 1 regularization scheme is proposed for estimation of sparse linear-regression models based on recent results in compressive sensing. It is shown that the proposed scheme provides consistent estimation of sparse models in terms of the so-called oracle property, it is computationally attractive for large-scale over-parameterized models and it is applicable in case of small data sets, i.e., underdetermined estimation problems. The performance of the approach w.r.t. other regularization schemes is demonstrated in an extensive Monte Carlo study. © 2011 IEEE.

  10. Probabilistic structural damage identification based on vibration data

    International Nuclear Information System (INIS)

    Hao, H.; Xia, Y.

    2001-01-01

    Vibration-based methods are being rapidly developed and applied to detect structural damage in civil, mechanical and aerospace engineering communities in the last two decades. But uncertainties existing in the structural model and measured vibration data might lead to unreliable results. This paper will present some recent research results to tackle the above mentioned uncertainty problems. By assuming each of the FE model parameters and measured vibration data as a normally distributed random variable, a probabilistic damage detection procedure is developed based on perturbation method and validated by Monte Carlo simulation technique. With this technique, the damage probability of each structural element can be determined. The method developed has been verified by applying it to identify the damages of laboratory tested structures. It was proven that, as compared to the deterministic damage identification method, the present method can not only reduce the possibility of false identification, but also give the identification results in terms of probability. which is deemed more realistic and practical in detecting possible damages in a structure. It has also been found that the modal data included in damage identification analysis have a great influence on the identification results. With a sensitivity study, an optimal measurement set for damage detection is determined. This set includes the optimal measurement locations and the most appropriate modes that should be used in the damage identification analysis. Numerical results indicated that if the optimal set determined in a pre-analysis is used in the damage detection better results will be achieved. (author)

  11. 基于激光传感器的智能车路径识别系统设计%The Design of Intelligent Vehicle Path Identification System Based on Laser Sensor

    Institute of Scientific and Technical Information of China (English)

    罗强; 徐文城; 刘尧

    2012-01-01

    The self - tracking intelligent vehicle path identification system is achieved in this paper. The system is based on laser sensors. The hardware and algorithm of the system is designed in this paper. The capability of Previem and Immunity of the Intelligent Vehicle is improved. Experiment shows that this system is much more stable and accurate, can make the Intelligent Vehicle run steadily by 2. 7m/s . By using the system, we have a better result in the race.%实现了一种自主式循迹智能车路径识别系统,设计了基于激光传感器的路径识别系统的硬件和控制算法,提高了光电式智能车的前瞻和抗干扰能力.实践表明,具有较高的稳定性和准确性,可使智能车以2.7 m/s的平均速度稳定运行,已在竞赛中取得了良好的成绩.

  12. Improved Stochastic Subspace System Identification for Structural Health Monitoring

    Science.gov (United States)

    Chang, Chia-Ming; Loh, Chin-Hsiung

    2015-07-01

    Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes. The stochastic subspace system identification has been recognized as a power tool which can present a structure in the modal coordinates. To obtain qualitative identified data, this tool needs to spend computational expense on a large set of measurements. In study, a stochastic system identification framework is proposed to improve the efficiency and quality of the conventional stochastic subspace system identification. This framework includes 1) measured signal processing, 2) efficient space projection, 3) system order selection, and 4) modal property derivation. The measured signal processing employs the singular spectrum analysis algorithm to lower the noise components as well as to present a data set in a reduced dimension. The subspace is subsequently derived from the data set presented in a delayed coordinate. With the proposed order selection criteria, the number of structural modes is determined, resulting in the modal properties. This system identification framework is applied to a real-world bridge for exploring the feasibility in real-time applications. The results show that this improved system identification method significantly decreases computational time, while qualitative modal parameters are still attained.

  13. Crack identification for rotating machines based on a nonlinear approach

    Science.gov (United States)

    Cavalini, A. A., Jr.; Sanches, L.; Bachschmid, N.; Steffen, V., Jr.

    2016-10-01

    In a previous contribution, a crack identification methodology based on a nonlinear approach was proposed. The technique uses external applied diagnostic forces at certain frequencies attaining combinational resonances, together with a pseudo-random optimization code, known as Differential Evolution, in order to characterize the signatures of the crack in the spectral responses of the flexible rotor. The conditions under which combinational resonances appear were determined by using the method of multiple scales. In real conditions, the breathing phenomenon arises from the stress and strain distribution on the cross-sectional area of the crack. This mechanism behavior follows the static and dynamic loads acting on the rotor. Therefore, the breathing crack can be simulated according to the Mayes' model, in which the crack transition from fully opened to fully closed is described by a cosine function. However, many contributions try to represent the crack behavior by machining a small notch on the shaft instead of the fatigue process. In this paper, the open and breathing crack models are compared regarding their dynamic behavior and the efficiency of the proposed identification technique. The additional flexibility introduced by the crack is calculated by using the linear fracture mechanics theory (LFM). The open crack model is based on LFM and the breathing crack model corresponds to the Mayes' model, which combines LFM with a given breathing mechanism. For illustration purposes, a rotor composed by a horizontal flexible shaft, two rigid discs, and two self-aligning ball bearings is used to compose a finite element model of the system. Then, numerical simulation is performed to determine the dynamic behavior of the rotor. Finally, the results of the inverse problem conveyed show that the methodology is a reliable tool that is able to estimate satisfactorily the location and depth of the crack.

  14. Parameters identification and adaptive full state hybrid projective synchronization of chaotic (hyper-chaotic) systems

    International Nuclear Information System (INIS)

    Hu Manfeng; Xu Zhenyuan; Zhang Rong; Hu Aihua

    2007-01-01

    Based on the active control idea and the invariance principle of differential equations, a general scheme of adaptive full state hybrid projective synchronization (FSHPS) and parameters identification of a class of chaotic (hyper-chaotic) systems with linearly dependent uncertain parameters is proposed in this Letter. With this effective scheme parameters identification and FSHPS of chaotic and hyper-chaotic systems can be realized simultaneously. Numerical simulations on the chaotic Chen system and the hyper-chaotic Chen system are presented to verify the effectiveness of the proposed scheme

  15. Complete functional characterization of sensory neurons by system identification.

    Science.gov (United States)

    Wu, Michael C-K; David, Stephen V; Gallant, Jack L

    2006-01-01

    System identification is a growing approach to sensory neurophysiology that facilitates the development of quantitative functional models of sensory processing. This approach provides a clear set of guidelines for combining experimental data with other knowledge about sensory function to obtain a description that optimally predicts the way that neurons process sensory information. This prediction paradigm provides an objective method for evaluating and comparing computational models. In this chapter we review many of the system identification algorithms that have been used in sensory neurophysiology, and we show how they can be viewed as variants of a single statistical inference problem. We then review many of the practical issues that arise when applying these methods to neurophysiological experiments: stimulus selection, behavioral control, model visualization, and validation. Finally we discuss several problems to which system identification has been applied recently, including one important long-term goal of sensory neuroscience: developing models of sensory systems that accurately predict neuronal responses under completely natural conditions.

  16. Identification of System Parameters by the Random Decrement Technique

    DEFF Research Database (Denmark)

    Brincker, Rune; Kirkegaard, Poul Henning; Rytter, Anders

    -Walker equations and finally least square fitting of the theoretical correlation function. The results are compared to the results of fitting an Auto Regressive Moving Average(ARMA) model directly to the system output. All investigations are performed on the simulated output from a single degree-off-freedom system......The aim of this paper is to investigate and illustrate the possibilities of using correlation functions estimated by the Random Decrement Technique as a basis for parameter identification. A two-stage system identification method is used: first the correlation functions are estimated by the Random...... Decrement technique and then the system parameters are identified from the correlation function estimates. Three different techniques are used in the parameters identification process: a simple non-paramatic method, estimation of an Auto Regressive(AR) model by solving an overdetermined set of Yule...

  17. Crack identification based on synthetic artificial intelligent technique

    International Nuclear Information System (INIS)

    Shim, Mun Bo; Suh, Myung Won

    2001-01-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

  18. Identification and systems methodologies for territorial delimitation

    Directory of Open Access Journals (Sweden)

    Iván Montoya R

    2010-12-01

    Full Text Available This document identifies the main issues affecting the delimitation of territories and explores the conceptual approaches for describing the relationship of the territories understood as organizations with their environment. Subsequently, we studied the systems methodologies known as soft systems methodology, SSM, and complex adaptive systems, CAS. Finally, the advantages of systemic approaches to territorial delimitation are shown

  19. Nuclear power plant transient identification using a neuro-fuzzy inference system

    International Nuclear Information System (INIS)

    Mol, Antonio Carlos de Abreu; Oliveira, Mauro Vitor de; Santos, Isaac Jose Antonio Luchetti dos; Carvalho, Paulo Victor Rodrigues de; Grecco, Claudio Henrique dos Santos; Auguto, Silas Cordeiro

    2005-01-01

    Transient identification in Nuclear Power Plant (NPP) is often a very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in nuclear power plants. The basis for the identification of a change in the system is that different system faults and anomalies lead to different patterns of evolution of the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments, that represents a specific type of event. In this work, an approach for the identification of transients is presented, aiming at helping the operator to make a decision relative to the procedure to be followed in situations of accidents/transients at nuclear power plants. In this way, a diagnostic strategy based on hierarchical use artificial neural networks (ANN) for a first level transient diagnose. After the ANN has done a preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. In order to validate the method, a Nuclear Power Plant transient identification problem, comprising postulated accidents, is proposed. Noisy data was used to evaluate the method robustness. The results obtained reveal the ability of the method in dealing with dynamic identification of transients and its reliability degree. (author)

  20. Eyewitness identification: Bayesian information gain, base-rate effect equivalency curves, and reasonable suspicion.

    Science.gov (United States)

    Wells, Gary L; Yang, Yueran; Smalarz, Laura

    2015-04-01

    We provide a novel Bayesian treatment of the eyewitness identification problem as it relates to various system variables, such as instruction effects, lineup presentation format, lineup-filler similarity, lineup administrator influence, and show-ups versus lineups. We describe why eyewitness identification is a natural Bayesian problem and how numerous important observations require careful consideration of base rates. Moreover, we argue that the base rate in eyewitness identification should be construed as a system variable (under the control of the justice system). We then use prior-by-posterior curves and information-gain curves to examine data obtained from a large number of published experiments. Next, we show how information-gain curves are moderated by system variables and by witness confidence and we note how information-gain curves reveal that lineups are consistently more proficient at incriminating the guilty than they are at exonerating the innocent. We then introduce a new type of analysis that we developed called base rate effect-equivalency (BREE) curves. BREE curves display how much change in the base rate is required to match the impact of any given system variable. The results indicate that even relatively modest changes to the base rate can have more impact on the reliability of eyewitness identification evidence than do the traditional system variables that have received so much attention in the literature. We note how this Bayesian analysis of eyewitness identification has implications for the question of whether there ought to be a reasonable-suspicion criterion for placing a person into the jeopardy of an identification procedure. (c) 2015 APA, all rights reserved).

  1. 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.)

  2. Experiment design for identification of structured linear systems

    NARCIS (Netherlands)

    Potters, M.G.

    2016-01-01

    Experiment Design for system identification involves the design of an optimal input signal with the purpose of accurately estimating unknown parameters in a system. Specifically, in the Least-Costly Experiment Design (LCED) framework, the optimal input signal results from an optimisation problem in

  3. The power grid AGC frequency bias coefficient online identification method based on wide area information

    Science.gov (United States)

    Wang, Zian; Li, Shiguang; Yu, Ting

    2015-12-01

    This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

  4. Parentage identification of Odontobutis potamophlia based on ...

    Indian Academy of Sciences (India)

    Peipei Wang

    2018-05-25

    May 25, 2018 ... based selective breeding of O. potamophila. The selective breeding is an ..... genetic relationship has gained recognition and attention in aquaculture ... which will benefit for estimating the actual number of loci and the ...

  5. Identification systems subject to plan cybersecurity

    International Nuclear Information System (INIS)

    Guerrero Sanz, J.; Perez Alcaniz, T.; Garcia Garcia, I.

    2012-01-01

    The implementation of a Plan Cybersecurity ensures that systems and communications networks that perform functions related to both physical security such emergency action and their support systems, and interfaces that may affect them, are protected with an effective system against cyber attacks.

  6. Immune System Toxicity and Immunotoxicity Hazard Identification

    Science.gov (United States)

    Exposure to chemicals may alter immune system health, increasing the risk of infections, allergy and autoimmune diseases. The chapter provides a concise overview of the immune system, host factors that affect immune system heal, and the effects that xenobiotic exposure may have ...

  7. Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets

    Directory of Open Access Journals (Sweden)

    Janusz Dudczyk

    2016-01-01

    Full Text Available More advanced recognition methods, which may recognize particular copies of radars of the same type, are called identification. The identification process of radar devices is a more specialized task which requires methods based on the analysis of distinctive features. These features are distinguished from the signals coming from the identified devices. Such a process is called Specific Emitter Identification (SEI. The identification of radar emission sources with the use of classic techniques based on the statistical analysis of basic measurable parameters of a signal such as Radio Frequency, Amplitude, Pulse Width, or Pulse Repetition Interval is not sufficient for SEI problems. This paper presents the method of hierarchical data clustering which is used in the process of radar identification. The Hierarchical Agglomerative Clustering Algorithm (HACA based on Generalized Agglomerative Scheme (GAS implemented and used in the research method is parameterized; therefore, it is possible to compare the results. The results of clustering are presented in dendrograms in this paper. The received results of grouping and identification based on HACA are compared with other SEI methods in order to assess the degree of their usefulness and effectiveness for systems of ESM/ELINT class.

  8. Task Characterisation and Cross-Platform Programming Through System Identification

    Directory of Open Access Journals (Sweden)

    Theocharis Kyriacou

    2005-12-01

    Full Text Available Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour, based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process. Such iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore present a modelling method that generates a faithful model of a robot's interaction with its environment, based on data logged while observing a physical robot's behaviour. Because this modelling method — nonlinear modelling using polynomials — is commonly used in the engineering discipline of system identification, we refer to it here as “robot identification”. We show in this paper that using robot identification to obtain a computer model of robot-environment interaction offers several distinct advantages: Very compact representations (one-line programs of the robot control program are generated The model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behaviour, and The generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type of robot to another. We demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot.

  9. An online ID identification system for liquefied-gas cylinder plant

    Science.gov (United States)

    He, Jin; Ding, Zhenwen; Han, Lei; Zhang, Hao

    2017-11-01

    An automatic ID identification system for gas cylinders' online production was developed based on the production conditions and requirements of the Technical Committee for Standardization of Gas Cylinders. A cylinder ID image acquisition system was designed to improve the image contrast of ID regions on gas cylinders against the background. Then the ID digits region was located by the CNN template matching algorithm. Following that, an adaptive threshold method based on the analysis of local average grey value and standard deviation was proposed to overcome defects of non-uniform background in the segmentation results. To improve the single digit identification accuracy, two BP neural networks were trained respectively for the identification of all digits and the easily confusable digits. If the single digit was classified as one of confusable digits by the former BP neural network, it was further tested by the later one, and the later result was taken as the final identification result of this single digit. At last, the majority voting was adopted to decide the final identification result for the 6-digit cylinder ID. The developed system was installed on a production line of a liquefied-petroleum-gas cylinder plant and worked in parallel with the existing weighing step on the line. Through the field test, the correct identification rate for single ID digit was 94.73%, and none of the tested 2000 cylinder ID was misclassified through the majority voting.

  10. Language identification of information blocks based on lexico-grammatic markers

    Directory of Open Access Journals (Sweden)

    Sergey N. Kalegin

    2017-12-01

    Full Text Available This article is a continuation of the author's series of publications on the subjects of language identification of texts. In the article is being considered the creation of a technological basis for language identification systems of unstructured information blocks based on lexico-grammatical markers, in which are used the forms of verbs, verbal formations or functionally analogous constructions, are described method and algorithm for its software implementation. These developments will significantly reduce the resource intensity and improve the quality of such systems, which will give a significant economic effect and the possibility of creating fundamentally new technologies for determining the linguistic affiliation of information in a multilingual environment. Consequently, the study is of interest for computer linguists and developers of automatic word processing systems, such as: global monitoring systems, multilingual knowledge bases, automatic translation systems, information retrieval systems, document summarizing systems, literature catalogers, etc.

  11. Qualitative identification of chaotic systems behaviours

    International Nuclear Information System (INIS)

    Vicha, T.; Dohnal, M.

    2008-01-01

    There are only three qualitative values positive, negative and zero. This means that there is a maximal number of qualitatively distinguishable scenarios, prescribed by the number of variables and the highest qualitative derivative taken into consideration. There are several chaos related tasks, which can be solved with great difficulties on the numerical level if multidimensional problems are studied. One of them is the identification of all qualitatively different behaviours. To make sure that all distinctive qualitative scenarios are identified a qualitative interpretation of a classical quantitative phase portrait is used. The highest derivatives are usually the second derivatives as it is not possible to safely identify higher derivatives if tasks related to ecology or economics are studied. Two classical models are discussed - Damped oscillation (non chaotic) and Lorenz model (chaotic). There are 191 scenarios of the Lorenz model if only the second derivatives are considered. If the third derivatives are taken into consideration then the number of scenarios is 2619. Complete qualitative results are given in details

  12. Transient identification system with noising data and 'don't know' response

    International Nuclear Information System (INIS)

    Mol, Antonio C. de A.; Martinez, Aquilino S.; Schirru, Roberto

    2002-01-01

    In the last years, many different approaches based on neural network (NN) has been proposed for transient identification in nuclear power plants (NPP). Some of them focus the dynamic identification using recurrent neural networks however, they are not able to deal with unrecognized transients. Other kind of solution uses competitive learning in order to allow the 'don't know' response. In this case dynamic, dynamic features are not well represented. This work presents a new approach for neural network based transient identification which allows either dynamic identification and 'don't know'response. Such approach uses two multilayer neural networks trained with backpropagation algorithm. The first one is responsible for the dynamic identification. This NN uses, a short set (in a movable time window) of recent measurements of each variable avoiding the necessity of using starting events. The other one is used to validate the instantaneous identification (from the first net) through the validation of each variable. This net is responsible for allowing the system to provide 'don't know' response. In order to validate the method a NPP transient identification problem comprising 15 postulated accidents, simulated for a pressurized water reactor, was proposed in the validation process it has been considered noising data in other to evaluate the method robustness. Obtained results reveal the ability of the method in dealing with both dynamic identification of transients and correct 'don't know' response. In order to validate the method, a NPP transient identification problem comprising 15 postulated accidents simulated for a pressurized water reactor, was proposed in the validation process it has been considered noising data in order to evaluate the method robustness. Obtained results reveal the ability of the method in dealing with both dynamic identification of transients and correct 'don't know' response. (author)

  13. A system boundary identification method for life cycle assessment

    DEFF Research Database (Denmark)

    Li, Tao; Zhang, Hongchao; Liu, Zhichao

    2014-01-01

    , technical, geographical and temporal dimensions are presented to limit the boundaries of LCA. An algorithm is developed to identify an appropriate boundary by searching the process tree and evaluating the environmental impact contribution of each process while it is added into the studied system...... as processes are added. The two threshold rules and identification methods presented can be used to identify system boundary of LCA. The case study demonstrated that the methodology presented in this paper is an effective tool for the boundary identification....

  14. Point source identification in nonlinear advection–diffusion–reaction systems

    International Nuclear Information System (INIS)

    Mamonov, A V; Tsai, Y-H R

    2013-01-01

    We consider a problem of identification of point sources in time-dependent advection–diffusion systems with a nonlinear reaction term. The linear counterpart of the problem in question can be reduced to solving a system of nonlinear algebraic equations via the use of adjoint equations. We extend this approach by constructing an algorithm that solves the problem iteratively to account for the nonlinearity of the reaction term. We study the question of improving the quality of source identification by adding more measurements adaptively using the solution obtained previously with a smaller number of measurements. (paper)

  15. Modeling emotional content of music using system identification.

    Science.gov (United States)

    Korhonen, Mark D; Clausi, David A; Jernigan, M Ed

    2006-06-01

    Research was conducted to develop a methodology to model the emotional content of music as a function of time and musical features. Emotion is quantified using the dimensions valence and arousal, and system-identification techniques are used to create the models. Results demonstrate that system identification provides a means to generalize the emotional content for a genre of music. The average R2 statistic of a valid linear model structure is 21.9% for valence and 78.4% for arousal. The proposed method of constructing models of emotional content generalizes previous time-series models and removes ambiguity from classifiers of emotion.

  16. Medical isotope identification with large mobile detection systems

    Science.gov (United States)

    Mukhopadhyay, Sanjoy; Maurer, Richard

    2012-10-01

    The Remote Sensing laboratory (RSL) of National Security Technologies Inc. has built an array of large (5.08 - cm x 10.16 - cm x 40.6 - cm) thallium doped sodium iodide (NaI: Tl) scintillators to locate and screen gamma-ray emitting radioisotopes that are of interests to radiological emergency responders [1]. These vehicle mounted detectors provide the operators with rapid, simple, specific information for radiological threat assessment. Applications include large area inspection, customs inspection, border protection, emergency response, and monitoring of radiological facilities. These RSL mobile units are currently being upgraded to meet the Defense Threat Reduction Agency mission requirements for a next-generation system capable of detecting and identifying nuclear threat materials. One of the challenging problems faced by these gamma-ray detectors is the unambiguous identification of medical isotopes like 131I (364.49 keV [81.7%], 636.99 keV [7.17%]), 99Tcm (140.51 keV [89.1%]) and 67Ga (184.6 keV [19.7%], 300.2 [16.0%], 393.5 [4.5%] that are used in radionuclide therapy and often have overlapping gamma-ray energy regions of interest (ROI). The problem is made worse by short (about 5 seconds) acquisition time of the spectral data necessary for dynamic mobile detectors. This article describes attempts to identify medical isotopes from data collected from this mobile detection system in a short period of time (not exceeding 5 secs) and a large standoff distance (typically 10 meters) The mobile units offer identification capabilities that are based on hardware auto stabilization of the amplifier gain. The 1461 keV gamma-energy line from 40K is tracked. It uses gamma-ray energy windowing along with embedded mobile Gamma Detector Response and Analysis Software (GADRAS) [2] simultaneously to deconvolve any overlapping gamma-energy ROIs. These high sensitivity detectors are capable of resolving complex masking scenarios and exceed all ANSI N42.34 (2006) requirements

  17. Text-based language identification for the South African languages

    CSIR Research Space (South Africa)

    Botha, G

    2006-11-01

    Full Text Available -crawling ap- proach described in [2]. That method employed an early language-identification system for au- tomatic selection of Web pages, and turned out to suffer from two limitations, namely wrongly identified web pages and web pages with mixed text (i...

  18. Damping characteristic identification of non-linear soil-structural system interaction by phase resonance

    International Nuclear Information System (INIS)

    Poterasu, V.F.

    1984-01-01

    It is presented a method and the phase resonance for damping characteristic identification of non-linear soil-structural interaction. The algorithm can be applied in case of any, not necessarily, damping characteristic of the system examined. For the identification, the system is harmonically excited and are considered the super-harmonic amplitudes for odd and even powers of the x. The response of shear beam system for different levels of base excitation and for different locations of the load is considered. (Author) [pt

  19. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...

  20. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...... choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...

  1. Advances in Modelling, System Identification and Parameter ...

    Indian Academy of Sciences (India)

    Authors show, using numerical simulation for two system functions, the improvement in percentage normalized ... of nonlinear systems. The approach is to use multiple linearizing models fitted along the operating trajectories. ... over emphasized in the light of present day high level of research activity in the field of aerospace ...

  2. Identification of invariant measures of interacting systems

    International Nuclear Information System (INIS)

    Chen Jinwen

    2004-01-01

    In this paper we provide an approach for identifying certain mixture representations of some invariant measures of interacting stochastic systems. This is related to the problem of ergodicity of certain extremal invariant measures that are translation invariant. Corresponding to these, results concerning the existence of invariant measures and certain weak convergence of the systems are also provided

  3. Tree Identification. Competency Based Teaching Materials in Horticulture.

    Science.gov (United States)

    Legacy, Jim; And Others

    This competency-based curriculum unit on tree identification is one of five developed for classroom use in teaching the landscape/nursery area of horticulture. The three sections are each divided into teaching content (in a question-and-answer format) and student skills that outline steps and factors for consideration. Topics covered include…

  4. Text-based language identification of multilingual names

    CSIR Research Space (South Africa)

    Giwa, O

    2015-11-01

    Full Text Available Text-based language identification (T-LID) of isolated words has been shown to be useful for various speech processing tasks, including pronunciation modelling and data categorisation. When the words to be categorised are proper names, the task...

  5. A security review of proximity identification based smart cards

    CSIR Research Space (South Africa)

    Lefophane, S

    2015-03-01

    Full Text Available International Conference on Cyber warfare and Security, Mpumalanga, Kruger National Park, South Africa, 24-25 March 2015 A SECURITY REVIEW OF PROXIMITY IDENTIFICATION BASED SMART CARDS S.Lefophane, J. Van der Merwe Modelling and Digital Science: CSIR...

  6. 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

  7. Limitations of the Current Microbial Identification System for Identification of Clinical Yeast Isolates

    Science.gov (United States)

    Kellogg, James A.; Bankert, David A.; Chaturvedi, Vishnu

    1998-01-01

    The ability of the rapid, computerized Microbial Identification System (MIS; Microbial ID, Inc.) to identify a variety of clinical isolates of yeast species was compared to the abilities of a combination of tests including the Yeast Biochemical Card (bioMerieux Vitek), determination of microscopic morphology on cornmeal agar with Tween 80, and when necessary, conventional biochemical tests and/or the API 20C Aux system (bioMerieux Vitek) to identify the same yeast isolates. The MIS chromatographically analyzes cellular fatty acids and compares the results with the fatty acid profiles in its database. Yeast isolates were subcultured onto Sabouraud dextrose agar and were incubated at 28°C for 24 h. The resulting colonies were saponified, methylated, extracted, and chromatographically analyzed (by version 3.8 of the MIS YSTCLN database) according to the manufacturer’s instructions. Of 477 isolates of 23 species tested, 448 (94%) were given species names by the MIS and 29 (6%) were unidentified (specified as “no match” by the MIS). Of the 448 isolates given names by the MIS, only 335 (75%) of the identifications were correct to the species level. While the MIS correctly identified only 102 (82%) of 124 isolates of Candida glabrata, the predictive value of an MIS identification of unknown isolates as C. glabrata was 100% (102 of 102) because no isolates of other species were misidentified as C. glabrata. In contrast, while the MIS correctly identified 100% (15 of 15) of the isolates of Saccharomyces cerevisiae, the predictive value of an MIS identification of unknown isolates as S. cerevisiae was only 47% (15 of 32), because 17 isolates of C. glabrata were misidentified as S. cerevisiae. The low predictive values for accuracy associated with MIS identifications for most of the remaining yeast species indicate that the procedure and/or database for the system need to be improved. PMID:9574676

  8. System identification advances and case studies

    CERN Document Server

    Mehra, Raman K

    1976-01-01

    In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank mat

  9. Tokamak plasma shape identification based on the boundary integral equations

    International Nuclear Information System (INIS)

    Kurihara, Kenichi; Kimura, Toyoaki

    1992-05-01

    A necessary condition for tokamak plasma shape identification is discussed and a new identification method is proposed in this article. This method is based on the boundary integral equations governing a vacuum region around a plasma with only the measurement of either magnetic fluxes or magnetic flux intensities. It can identify various plasmas with low to high ellipticities with the precision determined by the number of the magnetic sensors. This method is applicable to real-time control and visualization using a 'table-look-up' procedure. (author)

  10. Meta-domains for Automated System Identification

    National Research Council Canada - National Science Library

    Easley, Matthew; Bradley, Elizabeth

    2000-01-01

    .... In particular we introduce a new structure for automated model building known as a meta-domain which, when instantiated with domain-specific components tailors the space of candidate models to the system at hand...

  11. De novo pathway-based biomarker identification

    DEFF Research Database (Denmark)

    Alcaraz, Nicolas; List, Markus; Batra, Richa

    2017-01-01

    in a large cohort of breast cancer samples from The Cancer Genome Atlas (TCGA) revealed that MGs are considerably more stable than SG models, while also providing valuable insight into the cancer hallmarks that drive them. In addition, when tested on an independent benchmark non-TCGA dataset, MG features......Gene expression profiles have been extensively discussed as an aid to guide the therapy by predicting disease outcome for the patients suffering from complex diseases, such as cancer. However, prediction models built upon single-gene (SG) features show poor stability and performance on independent...... on their molecular subtypes can provide a detailed view of the disease and lead to more personalized therapies. We propose and discuss a novel MG approach based on de novo pathways, which for the first time have been used as features in a multi-class setting to predict cancer subtypes. Comprehensive evaluation...

  12. Multi-Frame Rate Based Multiple-Model Training for Robust Speaker Identification of Disguised Voice

    DEFF Research Database (Denmark)

    Prasad, Swati; Tan, Zheng-Hua; Prasad, Ramjee

    2013-01-01

    Speaker identification systems are prone to attack when voice disguise is adopted by the user. To address this issue,our paper studies the effect of using different frame rates on the accuracy of the speaker identification system for disguised voice.In addition, a multi-frame rate based multiple......-model training method is proposed. The experimental results show the superior performance of the proposed method compared to the commonly used single frame rate method for three types of disguised voice taken from the CHAINS corpus....

  13. Rapid identification of Yersinia pestis and Brucella melitensis by chip-based continuous flow PCR

    Science.gov (United States)

    Dietzsch, Michael; Hlawatsch, Nadine; Melzer, Falk; Tomaso, Herbert; Gärtner, Claudia; Neubauer, Heinrich

    2012-06-01

    To combat the threat of biological agents like Yersinia pestis and Brucella melitensis in bioterroristic scenarios requires fast, easy-to-use and safe identification systems. In this study we describe a system for rapid amplification of specific genetic markers for the identification of Yersinia pestis and Brucella melitensis. Using chip based PCR and continuous flow technology we were able to amplify the targets simultaneously with a 2-step reaction profile within 20 minutes. The subsequent analysis of amplified fragments by standard gel electrophoresis requires another 45 minutes. We were able to detect both pathogens within 75 minutes being much faster than most other nucleic acid amplification technologies.

  14. A rapid and direct real time PCR-based method for identification of Salmonella spp

    DEFF Research Database (Denmark)

    Rodriguez-Lazaro, D.; Hernández, Marta; Esteve, T.

    2003-01-01

    The aim of this work was the validation of a rapid, real-time PCR assay based on TaqMan((R)) technology for the unequivocal identification of Salmonella spp. to be used directly on an agar-grown colony. A real-time PCR system targeting at the Salmonella spp. invA gene was optimized and validated ...

  15. A personnel TLD system with person identification

    International Nuclear Information System (INIS)

    Widell, C.O.

    1974-01-01

    The TLD system uses Li 2 B 4 O 7 :Mn, Si sintered tablets which are heated by hot nitrogen. The slide which holds the tablets is coded by a self adhesive polyester-aluminium tape. This tape is BCD coded in an ordinary tape punch. The information on the punched tape includes a ten digit social-security number and a two digit information on location and type of dosimetry. By this system dosimetric data is directly transfered into a central dose register for Sweden. All personnel doses are there stored on social-security numbers. (author)

  16. ECG biometric identification: A compression based approach.

    Science.gov (United States)

    Bras, Susana; Pinho, Armando J

    2015-08-01

    Using the electrocardiogram signal (ECG) to identify and/or authenticate persons are problems still lacking satisfactory solutions. Yet, ECG possesses characteristics that are unique or difficult to get from other signals used in biometrics: (1) it requires contact and liveliness for acquisition (2) it changes under stress, rendering it potentially useless if acquired under threatening. Our main objective is to present an innovative and robust solution to the above-mentioned problem. To successfully conduct this goal, we rely on information-theoretic data models for data compression and on similarity metrics related to the approximation of the Kolmogorov complexity. The proposed measure allows the comparison of two (or more) ECG segments, without having to follow traditional approaches that require heartbeat segmentation (described as highly influenced by external or internal interferences). As a first approach, the method was able to cluster the data in three groups: identical record, same participant, different participant, by the stratification of the proposed measure with values near 0 for the same participant and closer to 1 for different participants. A leave-one-out strategy was implemented in order to identify the participant in the database based on his/her ECG. A 1NN classifier was implemented, using as distance measure the method proposed in this work. The classifier was able to identify correctly almost all participants, with an accuracy of 99% in the database used.

  17. Identification of linear error-models with projected dynamical systems

    Czech Academy of Sciences Publication Activity Database

    Krejčí, Pavel; Kuhnen, K.

    2004-01-01

    Roč. 10, č. 1 (2004), s. 59-91 ISSN 1387-3954 Keywords : identification * error models * projected dynamical systems Subject RIV: BA - General Mathematics Impact factor: 0.292, year: 2004 http://www.informaworld.com/smpp/content~db=all~content=a713682517

  18. Dynamic Parameter Identification of Hydrodynamic Bearing-Rotor System

    Directory of Open Access Journals (Sweden)

    Zhiqiang Song

    2015-01-01

    Full Text Available A new method called modal parameter genetic time domain identification was employed to study the characteristics of the bearing-rotor system. A multifrequency signal decomposition technology to identify the main components of the measured signal and reject the image mode produced by noise has been used. The first- and second-order natural frequency and damping ratios of the shaft system are identified. Furthermore, because of the deficiency of the traditional least square method, a new genetic identification method to identify the bearing dynamic characteristic parameters has been proposed. The method has been effective albeit with few testing points and operation cases. The derivation of oil-film dynamic coefficients could also provide a basis for shaft system natural vibration characteristic and vibration response analysis. Using the identified dynamic coefficients as the supporting condition, the shaft system modal characteristics were studied. The calculated first- and second-order natural frequencies match quite well those obtained from the modal parameter identification. It was proved that the modal parameter and physical parameter identification methods utilized in this paper are reasonable.

  19. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Automatic Transmitter Identification System (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter...

  20. Detection system for the identification of heavy ions

    International Nuclear Information System (INIS)

    Abriola, Daniel H.; Arazi, Andres; Achterberg, Erhard; Capurro, Oscar A.; Fernandez Niello, Jorge O.; Ferrero, Armando M. J.; Liberman, Rosa G.; Marti, Guillermo V.; Pacheco, Alberto J.; Ramirez, Marcelo C.; Testoni, Jorge E.

    1999-01-01

    The TANDAR laboratory has a magnetic spectrometer as one of its detection facilities. This device allows the separation of incident particles according to the relation between their lineal momentum and their charge state. To complete this identification there are two alternatives: 1) A system of three detectors consisting of a multiwire detector, an ionization chamber and scintillators; 2) A segmented anode ionization chamber. (author)

  1. Identification of continuous-time systems from samples of input ...

    Indian Academy of Sciences (India)

    Abstract. This paper presents an introductory survey of the methods that have been developed for identification of continuous-time systems from samples of input±output data. The two basic approaches may be described as (i) the indirect method, where first a discrete-time model is estimated from the sampled data and then ...

  2. Training Sessions Provide Working Knowledge of National Animal Identification System

    Science.gov (United States)

    Glaze, J. Benton, Jr.; Ahola, Jason K.

    2010-01-01

    One in-service and two train-the-trainer workshops were conducted by University of Idaho Extension faculty, Idaho State Department of Agriculture personnel, and allied industry representatives to increase Extension educators' knowledge and awareness of the National Animal Identification System (NAIS) and related topics. Training sessions included…

  3. A programmable logic controller-based system for the recirculation of liquid C6F14 in the ALICE high momentum particle identification detector at the Large Hadron Collider

    International Nuclear Information System (INIS)

    Sgura, I.; Cataldo, G. de; Franco, A.; Pastore, C.; Volpe, G.

    2012-01-01

    The aim of this paper is to present the design and the implementation of the Control System (CS) for the recirculation of liquid Perfluorohexane (C 6 F 14 ) for the ALICE High Momentum Particle Identification detector (HMPID). The HMPID is a detector of the ALICE experiment at the CERN Large Hadron Collider (LHC). It uses liquid C 6 F 14 as Cherenkov radiator medium in twenty-one quartz vessels for the measurement of the charged particles velocity. The primary task of the Liquid Circulation System (LCS) is to ensure the highest transparency of C 6 F 14 to the ultraviolet light. In order to provide safe long term operation a Programmable Logic Controller-based CS has been implemented. CS provides both automatic and manual operating modes, remotely or locally. Its finite state machine design minimizes the possible operator errors and provides a hierarchical control structure allowing the operation and monitoring down to a single radiator vessel. LCS is protected against unsafe working conditions by both active and passive measures. The passive ones are intrinsically guaranteed whereas the active ones are ensured via the control software running in the PLC. The human interface and data archiving are provided via PVSS, the Supervisory Control And Data Acquisition (SCADA) framework which integrates the full detector control. LCS under CS control proved to meet all designed requirements thus enabling HMPID detector to successfully collect data since the very beginning of LHC operation. (authors)

  4. Process identification method based on the Z transformation; Methode d'identification de processus par la transformation en Z

    Energy Technology Data Exchange (ETDEWEB)

    Zwingelstein, G [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1968-07-01

    A simple method is described for identifying the transfer function of a linear retard-less system, based on the inversion of the Z transformation of the transmittance using a computer. It is assumed in this study that the signals at the entrance and at the exit of the circuit considered are of the deterministic type. The study includes: the theoretical principle of the inversion of the Z transformation, details about programming simulation, and identification of filters whose degrees vary from the first to the fifth order. (authors) [French] On decrit une methode simple d'identification de fonction de transfert d'un systeme lineaire sans retard, qui repose sur l'inversion de la transformee en Z de la transmittance a l'aide d'un calculateur. On suppose dans cette etude, que les signaux a l'entree et a la sortie du circuit considere sont de type deterministe. L'etude comporte: le principe theorique de l'inversion de la transformation en Z, les details de la programmation, la simulation et l'identification de filtres dont le degre varie du premier au cinquieme ordre. (auteurs)

  5. New methodology for a person identification system

    Indian Academy of Sciences (India)

    Home; Journals; Sadhana; Volume 31; Issue 3. New methodology for a person identification system. R Bremananth A Chitra. Volume 31 Issue 3 June 2006 pp 259-276 ... Experimental results illustrate that the proposed method has been easily espoused in elections, bank transactions and other security applications.

  6. 77 FR 40735 - Unique Device Identification System

    Science.gov (United States)

    2012-07-10

    ... lessons learned from these pilot activities. FDA also solicited input through public meetings; a public... used to identify devices, and no assurance that different companies are using a given term in the same... weaknesses or problems in our implementation of the UDI system and to make appropriate mid-course corrections...

  7. System identification on two-phase flow stability

    International Nuclear Information System (INIS)

    Wu Shaorong; Zhang Youjie; Wang Dazhong; Bo Jinghai; Wang Fei

    1996-01-01

    The theoretical principle, experimental method and results of interrelation analysis identification for the instability of two-phase flow are described. A completely new concept of test technology and method on two-phase flow stability was developed by using he theory of information science on system stability and system identification for two-phase flow stability in thermo-physics field. Application of this method would make it possible to identify instability boundary of two-phase flow under stable operation conditions of two-phase flow system. The experiment was carried out on the thermohydraulic test system HRTL-5. Using reverse repeated pseudo-random sequences of heating power as input signal sources and flow rate as response function in the test, the two-phase flow stability and stability margin of the natural circulation system are investigated. The effectiveness and feasibility of identifying two-phase flow stability by using this system identification method were experimentally demonstrated. Basic data required for mathematics modeling of two-phase flow and analysis of two-phase flow stability were obtained, which are useful for analyzing, monitoring of the system operation condition, and forecasting of two-phase flow stability in engineering system

  8. Variation in Microbial Identification System accuracy for yeast identification depending on commercial source of Sabouraud dextrose agar.

    Science.gov (United States)

    Kellogg, J A; Bankert, D A; Chaturvedi, V

    1999-06-01

    The accuracy of the Microbial Identification System (MIS; MIDI, Inc. ) for identification of yeasts to the species level was compared by using 438 isolates grown on prepoured BBL Sabouraud dextrose agar (SDA) and prepoured Remel SDA. Correct identification was observed for 326 (74%) of the yeasts cultured on BBL SDA versus only 214 (49%) of yeasts grown on Remel SDA (P < 0.001). The commercial source of the SDA used in the MIS procedure significantly influences the system's accuracy.

  9. Parametric Identification of Nonlinear Dynamical Systems

    Science.gov (United States)

    Feeny, Brian

    2002-01-01

    In this project, we looked at the application of harmonic balancing as a tool for identifying parameters (HBID) in a nonlinear dynamical systems with chaotic responses. The main idea is to balance the harmonics of periodic orbits extracted from measurements of each coordinate during a chaotic response. The periodic orbits are taken to be approximate solutions to the differential equations that model the system, the form of the differential equations being known, but with unknown parameters to be identified. Below we summarize the main points addressed in this work. The details of the work are attached as drafts of papers, and a thesis, in the appendix. Our study involved the following three parts: (1) Application of the harmonic balance to a simulation case in which the differential equation model has known form for its nonlinear terms, in contrast to a differential equation model which has either power series or interpolating functions to represent the nonlinear terms. We chose a pendulum, which has sinusoidal nonlinearities; (2) Application of the harmonic balance to an experimental system with known nonlinear forms. We chose a double pendulum, for which chaotic response were easily generated. Thus we confronted a two-degree-of-freedom system, which brought forth challenging issues; (3) A study of alternative reconstruction methods. The reconstruction of the phase space is necessary for the extraction of periodic orbits from the chaotic responses, which is needed in this work. Also, characterization of a nonlinear system is done in the reconstructed phase space. Such characterizations are needed to compare models with experiments. Finally, some nonlinear prediction methods can be applied in the reconstructed phase space. We developed two reconstruction methods that may be considered if the common method (method of delays) is not applicable.

  10. A Situational-Awareness System For Networked Infantry Including An Accelerometer-Based Shot-Identification Algorithm For Direct-Fire Weapons

    Science.gov (United States)

    2016-09-01

    combine my love of shooting with my education. Dr. Xiaoping Yun graciously provided me with his wealth of technical knowledge. Dr. James Calusdian’s...expanding gasses forcing the projectile down the barrel restarting the process [10]. The major internal components of an AR15 are shown in Figure 1 with...of the three-plate system does not change, regardless of the movement of the middle plate, resulting in the relationship (2.11) Expanding

  11. Identification of protective antigens for vaccination against systemic salmonellosis

    Directory of Open Access Journals (Sweden)

    Dirk eBumann

    2014-08-01

    Full Text Available There is an urgent medical need for improved vaccines with broad serovar coverage and high efficacy against systemic salmonellosis. Subunit vaccines offer excellent safety profiles but require identification of protective antigens, which remains a challenging task. Here, I review crucial properties of Salmonella antigens that might help to narrow down the number of potential candidates from more than 4000 proteins encoded in Salmonella genomes, to a more manageable number of 50-200 most promising antigens. I also discuss complementary approaches for antigen identification and potential limitations of current pre-clinical vaccine testing.

  12. A identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongping

    2006-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of Detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on the theory discussed above. (authors)

  13. Identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongpin

    2007-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on this theory discussed above. (authors)

  14. Fuzzy systems for process identification and control

    International Nuclear Information System (INIS)

    Gorrini, V.; Bersini, H.

    1994-01-01

    Various issues related to the automatic construction and on-line adaptation of fuzzy controllers are addressed. A Direct Adaptive Fuzzy Control (this is an adaptive control methodology requiring a minimal knowledge of the processes to be coupled with) derived in a way reminiscent of neurocontrol methods, is presented. A classical fuzzy controller and a fuzzy realization of a PID controller is discussed. These systems implement a highly non-linear control law, and provide to be quite robust, even in the case of noisy inputs. In order to identify dynamic processes of order superior to one, we introduce a more complex architecture, called Recurrent Fuzzy System, that use some fuzzy internal variables to perform an inferential chaining.I

  15. EPICS based DAQ system

    International Nuclear Information System (INIS)

    Cheng Weixing; Chen Yongzhong; Zhou Weimin; Ye Kairong; Liu Dekang

    2002-01-01

    EPICS is the most popular developing platform to build control system and beam diagnostic system in modern physics experiment facilities. An EPICS based data acquisition system was built in Redhat 6.2 operation system. The system is successfully used in the beam position monitor mapping, it improves the mapping process a lot

  16. Biometric identification systems: the science of transaction facilitation

    Science.gov (United States)

    Rogers, Robert R.

    1994-10-01

    The future ofthe "secure transaction" and the success ofall undertakings that depend on absolute certainty that the individuals involved really are who and what they represent themselves to be is dependent upon the successful development of absolutely accurate, low-cost and easy-to-operate Biometric Identification Systems. Whether these transactions are political, military, financial or administrative (e.g. health cards, drivers licenses, welfare entitlement, national identification cards, credit card transactions, etc.), the need for such secure and positive identification has never been greater -and yet we are only at the beginning ofan era in which we will see the emergence and proliferation of Biometric Identification Systems in nearly every field ofhuman endeavor. Proper application ofthese systems will change the way the world operates, and that is precisely the goal ofComparator Systems Corporation. Just as with the photo-copier 40 years ago and the personal computer 20 years ago, the potential applications for positive personal identification are going to make the Biometric Identification System a commonplace component in the standard practice ofbusiness, and in interhuman relationships ofall kinds. The development of new and specific application hardware, as well as the necessary algorithms and related software required for integration into existing operating procedures and newly developed systems alike, has been a more-than-a-decade-long process at Comparator -and we are now on the verge of delivering these systems to the world markets so urgently in need of them. An individual could feel extremely confident and satisfied ifhe could present his credit, debit, or ATM card at any point of sale and, after inserting his card, could simply place his finger on a glass panel and in less than a second be positively accepted as being the person that the card purported him to be; not to mention the security and satisfaction of the vendor involved in knowing that

  17. 21 CFR 880.6300 - Implantable radiofrequency transponder system for patient identification and health information.

    Science.gov (United States)

    2010-04-01

    ... patient identification and health information. 880.6300 Section 880.6300 Food and Drugs FOOD AND DRUG... radiofrequency transponder system for patient identification and health information. (a) Identification. An implantable radiofrequency transponder system for patient identification and health information is a device...

  18. Identification of toxic cyclopeptides based on mass spectral library matching

    Directory of Open Access Journals (Sweden)

    Boris L. Milman

    2014-08-01

    Full Text Available To gain perspective on the use of tandem mass spectral libraries for identification of toxic cyclic peptides, the new library was built from 263 mass spectra (mainly MS2 spectra of 59 compounds of that group, such as microcystins, amatoxins, and some related compounds. Mass spectra were extracted from the literature or specially acquired on ESI-Q-ToF and MALDI-ToF/ToF tandem instruments. ESI-MS2 product-ion mass spectra appeared to be rather close to MALDI-ToF/ToF fragment spectra which are uncommon for mass spectral libraries. Testing of the library was based on searches where reference spectra were in turn cross-compared. The percentage of 1st rank correct identifications (true positives was 70% in a general case and 88–91% without including knowingly defective (‘one-dimension’ spectra as test ones. The percentage of 88–91% is the principal estimate for the overall performance of this library that can be used in a method of choice for identification of individual cyclopeptides and also for group recognition of individual classes of such peptides. The approach to identification of cyclopeptides based on mass spectral library matching proved to be the most effective for abundant toxins. That was confirmed by analysis of extracts from two cyanobacterial strains.

  19. 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.

  20. Noise source identification for ducted fan systems

    OpenAIRE

    BENNETT, GARETH; FITZPATRICK, JOHN AIDAN

    2008-01-01

    PUBLISHED Coherence based source analysis techniques can be used to identify the contribution of combustion noise in the exhaust of a jet engine and hence enable the design of noise reduction devices. However, when the combustion noise propagates in a non-linear fashion the identified contribution using ordinary coherence methods will be inaccurate. In this paper, an analysis technique to enable the contribution of linear and non-linear mechanisms to the propagated sound ...

  1. Online stress corrosion crack and fatigue usages factor monitoring and prognostics in light water reactor components: Probabilistic modeling, system identification and data fusion based big data analytics approach

    Energy Technology Data Exchange (ETDEWEB)

    Mohanty, Subhasish M. [Argonne National Lab. (ANL), Argonne, IL (United States); Jagielo, Bryan J. [Argonne National Lab. (ANL), Argonne, IL (United States); Oakland Univ., Rochester, MI (United States); Iverson, William I. [Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Illinois at Urbana-Champaign, Champaign, IL (United States); Bhan, Chi Bum [Argonne National Lab. (ANL), Argonne, IL (United States); Pusan National Univ., Busan (Korea, Republic of); Soppet, William S. [Argonne National Lab. (ANL), Argonne, IL (United States); Majumdar, Saurin M. [Argonne National Lab. (ANL), Argonne, IL (United States); Natesan, Ken N. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2014-12-10

    Nuclear reactors in the United States account for roughly 20% of the nation's total electric energy generation, and maintaining their safety in regards to key component structural integrity is critical not only for long term use of such plants but also for the safety of personnel and the public living around the plant. Early detection of damage signature such as of stress corrosion cracking, thermal-mechanical loading related material degradation in safety-critical components is a necessary requirement for long-term and safe operation of nuclear power plant systems.

  2. Attendance fingerprint identification system using arduino and single board computer

    Science.gov (United States)

    Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

    2018-03-01

    Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

  3. Applications of radio frequency identification systems in underground mining

    Energy Technology Data Exchange (ETDEWEB)

    Knights, P F; Kairouz, J; Daneshmend, L K; Pathak, J [McGill University, Montreal, PQ (Canada). Canadian Centre for Automation and Robotics in Mining

    1994-12-31

    The paper describes the application of Radio Frequency Identification (RFID) systems in underground hardrock mines. The operating principles and some of the applications of RDIF systems are described. The system operates by the exchange of information between transponder tags and an antenna and controller device. The suitability of RFID systems for process control, inventory control, materials handling, control of access, security, and transportation in underground coal and hardrock mines is discussed. An ore tonnage tracking system is under development that uses RDIF transponder tags to locate vehicles in an underground mine. 6 refs., 4 figs.

  4. Los Alamos Scientific Laboratory electronic vehicle identification system

    International Nuclear Information System (INIS)

    Landt, J.A.; Bobbett, R.E.; Koelle, A.R.; Salazar, P.H.

    1980-01-01

    A three-digit electronic identification system is described. Digits may be decimal (1000 combinations) or hexidecimal (8192 combinations). Battery-powered transponders are interrogated with a lower-power (1 W) radio signal. Line-of-sight interrogations up to 33 m (100 ft) are possible. Successful interrogations up to 7 m (20 ft) are possible for concealed transponders (that is, in the engine compartment). Vehicles moving at high rates of speed can be interrogated. This system provides data in a computer-compatible RS232 format. The system can be used for other applications with little or no modification. A similar system is in present use for identification and temperature monitoring of livestock. No unforeseen problems exist for expanding the coding scheme to identify larger numbers of objects

  5. System identification by methods from the statistical signal theory, history and state of the art

    International Nuclear Information System (INIS)

    Christensen, Palle; Gundersen, Vidar B.

    1999-01-01

    Condition monitoring is an important area in which the OECD Halden Reactor Project has developed several tools. This paper presents a general overview of methods utilised in diagnosis systems, signal validation systems and process optimisation systems such as EFD, Mocom, Aladdin and PEANO. An overview of lessons learned on diagnosis of technical systems with special reference to system identification is reported. The analysis of input-output behaviour by special, suitable methods may be used as a tool for diagnosis. An overview of methods for empirical modelling and data analysis and their major differences is presented. It is explained how system identification methods and transforms may be used to build models based on observed data from a system. According to the Webster dictionary diagnosis is 'Investigation or analysis of the cause or nature of a condition, situation or a problem.' By examining data collected from a process the aim is to detect abnormal conditions and if possible understand what has been the cause of the observed problem. Section 1 gives a retrospective view at the development in the field of system identification. Section 2 presents a classification of the methods, while section 3 provides some practical advice on how diagnosis can be carried out by means of system identification methods (author) (ml)

  6. Identification of active fault using analysis of derivatives with vertical second based on gravity anomaly data (Case study: Seulimeum fault in Sumatera fault system)

    Science.gov (United States)

    Hududillah, Teuku Hafid; Simanjuntak, Andrean V. H.; Husni, Muhammad

    2017-07-01

    Gravity is a non-destructive geophysical technique that has numerous application in engineering and environmental field like locating a fault zone. The purpose of this study is to spot the Seulimeum fault system in Iejue, Aceh Besar (Indonesia) by using a gravity technique and correlate the result with geologic map and conjointly to grasp a trend pattern of fault system. An estimation of subsurface geological structure of Seulimeum fault has been done by using gravity field anomaly data. Gravity anomaly data which used in this study is from Topex that is processed up to Free Air Correction. The step in the Next data processing is applying Bouger correction and Terrin Correction to obtain complete Bouger anomaly that is topographically dependent. Subsurface modeling is done using the Gav2DC for windows software. The result showed a low residual gravity value at a north half compared to south a part of study space that indicated a pattern of fault zone. Gravity residual was successfully correlate with the geologic map that show the existence of the Seulimeum fault in this study space. The study of earthquake records can be used for differentiating the active and non active fault elements, this gives an indication that the delineated fault elements are active.

  7. Identification of Managerial Competencies in Knowledge-based Organizations

    Directory of Open Access Journals (Sweden)

    Königová Martina

    2012-03-01

    Full Text Available Managerial competencies identification and development are important tools of human resources management that is aimed at achieving strategic organizational goals. Due to current dynamic development and changes, more and more attention is being paid to the personality of managers and their competencies, since they are viewed as important sources of achieving a competitive advantage. The objective of this article is to identify managerial competencies in the process of filling vacant working positions in knowledge-based organizations in the Czech Republic. The objective was determined with reference to the Czech Science Foundation GACR research project which focuses on the identification of managerial competencies in knowledge-based organizations in the Czech Republic. This identification within the frame of the research project is primarily designed and subsequently realised on the basis of content analysis of media communications such as advertisements - a means through which knowledge- based organizations search for suitable candidates for vacant managerial positions. The first part of the article deals with theoretical approaches to knowledge-based organizations and issues on competencies. The second part evaluates the outcomes of the survey carried out, and also summarizes the basic steps of the application of competencies. The final part summarizes the benefits and difficulties of applying the competency-based approach as a tool of efficient management of organizations for the purpose of achieving a competitive advantage.

  8. System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

    Directory of Open Access Journals (Sweden)

    Giorgio Bacelli

    2017-04-01

    Full Text Available Empirically based modeling is an essential aspect of design for a wave energy converter. Empirically based models are used in structural, mechanical and control design processes, as well as for performance prediction. Both the design of experiments and methods used in system identification have a strong impact on the quality of the resulting model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages, including an increased signal-to-noise ratio, reduced experimental time and higher frequency resolution. The experimental wave tank data is used to produce multiple models using different formulations to represent the dynamics of the wave energy converter. These models are validated and their performance is compared against one another. While most models of wave energy converters use a formulation with surface elevation as an input, this study shows that a model using a hull pressure measurement to incorporate the wave excitation phenomenon has better accuracy.

  9. 75 FR 57686 - Hazardous Waste Management System; Identification and Listing of Hazardous Waste Amendment

    Science.gov (United States)

    2010-09-22

    ... Waste Management System; Identification and Listing of Hazardous Waste Amendment AGENCY: Environmental...) 260.20 and 260.22 allows facilities to demonstrate that a specific waste from a particular generating facility should not be regulated as a hazardous waste. Based on waste-specific information provided by the...

  10. ECG Identification System Using Neural Network with Global and Local Features

    Science.gov (United States)

    Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

    2016-01-01

    This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

  11. Performance Modelling of Automatic Identification System with Extended Field of View

    DEFF Research Database (Denmark)

    Lauersen, Troels; Mortensen, Hans Peter; Pedersen, Nikolaj Bisgaard

    2010-01-01

    This paper deals with AIS (Automatic Identification System) behavior, to investigate the severity of packet collisions in an extended field of view (FOV). This is an important issue for satellite-based AIS, and the main goal is a feasibility study to find out to what extent an increased FOV...

  12. System identification and the modeling of sailing yachts

    Science.gov (United States)

    Legursky, Katrina

    This research represents an exploration of sailing yacht dynamics with full-scale sailing motion data, physics-based models, and system identification techniques. The goal is to provide a method of obtaining and validating suitable physics-based dynamics models for use in control system design on autonomous sailing platforms, which have the capacity to serve as mobile, long range, high endurance autonomous ocean sensing platforms. The primary contributions of this study to the state-of-the-art are the formulation of a five degree-of-freedom (DOF) linear multi-input multi-output (MIMO) state space model of sailing yacht dynamics, the process for identification of this model from full-scale data, a description of the maneuvers performed during on-water tests, and an analysis method to validate estimated models. The techniques and results described herein can be directly applied to and tested on existing autonomous sailing platforms. A full-scale experiment on a 23ft monohull sailing yacht is developed to collect motion data for physics-based model identification. Measurements include 3 axes of accelerations, velocities, angular rates, and attitude angles in addition to apparent wind speed and direction. The sailing yacht herein is treated as a dynamic system with two control inputs, the rudder angle, deltaR, and the mainsail angle, delta B, which are also measured. Over 20 hours of full scale sailing motion data is collected, representing three sail configurations corresponding to a range of wind speeds: the Full Main and Genoa (abbrev. Genoa) for lower wind speeds, the Full Main and Jib (abbrev. Jib) for mid-range wind speeds, and the Reefed Main and Jib (abbrev. Reef) for the highest wind speeds. The data also covers true wind angles from upwind through a beam reach. A physics-based non-linear model to describe sailing yacht motion is outlined, including descriptions of methods to model the aerodynamics and hydrodynamics of a sailing yacht in surge, sway, roll, and

  13. The application of an artificial immune system for solving the identification problem

    Directory of Open Access Journals (Sweden)

    Astachova Irina

    2017-01-01

    Full Text Available Ecological prognosis sets the identification task, which is to find the capacity of pollution sources based on the available experimental data. This problem is an inverse problem, for the solution of which the method of symbolic regression is considered. The distributed artificial immune system is used as an algorithm for the problem solving. The artificial immune system (AIS is a model that allows solving various problems of identification, its concept was borrowed from biology. The solution is sought using a distributed version of the artificial immune system, which is implemented through a network. This distributed network can operate in any heterogeneous environment, which is achieved through the use of cross-platform Python programming language. AIS demonstrates the ability to restore the original function in the problem of identification. The obtained solution for the test data is represented by the graph.

  14. Structural System Identification with Extended Kalman Filter and Orthogonal Decomposition of Excitation

    Directory of Open Access Journals (Sweden)

    Y. Ding

    2014-01-01

    Full Text Available Both the structural parameter and external excitation have coupling influence on structural response. A new system identification method in time domain is proposed to simultaneously evaluate structural parameter and external excitation. The method can be used for linear and hysteresis nonlinear structural condition assessment based on incomplete structural responses. In this method, the structural excitation is decomposed by orthogonal approximation. With this approximation, the strongly time-variant excitation identification is transformed to gentle time-variant, even constant parameters identification. Then the extended Kalman filter is applied to simultaneously identify state vector including the structural parameters and excitation orthogonal parameters in state space based on incomplete measurements. The proposed method is validated numerically with the simulation of three-story linear and nonlinear structures subject to external force. The external force on the top floor and the structural parameters are simultaneously identified with the proposed system identification method. Results from both simulations indicate that the proposed method is capable of identifing the dynamic load and structural parameters fairly accurately with contaminated incomplete measurement for both of the linear and nonlinear structural systems.

  15. Evaluation of cell lysis procedures and use of a micro fluidic system for an automated DNA-based cell identification in interplanetary missions

    Science.gov (United States)

    Hall, J. A.; Felnagle, E.; Fries, M.; Spearing, S.; Monaco, L.; Steele, A.

    2006-12-01

    A Modular Assay System for Solar System Exploration (MASSE) is being developed to include sample handling, pre-treatment, separation and analysis of biological target compounds by both DNA and protein microarrays. To better design sensitive and accurate initial upstream sample handling of the MASSE instrument, experiments investigating the sensitivity and potential extraction bias of commercially available DNA extraction kits between classes of environmentally relevant prokaryotes such as gram-negative bacteria ( Escherichia coli), gram-positive bacteria ( Bacillus megatarium), and Archaea ( Haloarcula marismortui) were performed. For extractions of both planktonic cultures and spiked Mars simulated regolith, FTA ® paper demonstrated the highest sensitivity, with detection as low as ˜1×10 1 cells and ˜3.3×10 2 cells, respectively. In addition to the highest sensitivity, custom modified application of FTA ® paper extraction protocol is the simplest in terms of incorporation into MASSE and displayed little bias in sensitivity with respect to prokaryotic cell type. The implementation of FTA paper for environmental microbiology investigations appears to be a viable and effective option potentially negating the need for other pre-concentration steps such as filtration and negating concerns regarding extraction efficiency of cells. In addition to investigations on useful technology for upstream sample handling in MASSE, we have also evaluated the potential for μTAS to be employed in the MASSE instrument by employing proprietary lab-on-a-chip development technology to investigate the potential for microfluidic cell lysis of different prokaryotic cells employing both chemical and biological lysis agents. Real-time bright-field microscopy and quantitative PMT detection indicated that that gram positive, gram negative and archaeal cells were effectively lyzed in a few seconds using the microfluidic chip protocol developed. This included employing a lysis buffer with

  16. Biometric and Emotion Identification: An ECG Compression Based Method

    Directory of Open Access Journals (Sweden)

    Susana Brás

    2018-04-01

    Full Text Available We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG. The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1 conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2 conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3 identification of the ECG record class, using a 1-NN (nearest neighbor classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

  17. 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.

  18. Biometric and Emotion Identification: An ECG Compression Based Method.

    Science.gov (United States)

    Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J

    2018-01-01

    We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

  19. Biometric and Emotion Identification: An ECG Compression Based Method

    Science.gov (United States)

    Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

    2018-01-01

    We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564

  20. Modelling of Biometric Identification System with Given Parameters Using Colored Petri Nets

    Science.gov (United States)

    Petrosyan, G.; Ter-Vardanyan, L.; Gaboutchian, A.

    2017-05-01

    Biometric identification systems use given parameters and function on the basis of Colored Petri Nets as a modelling language developed for systems in which communication, synchronization and distributed resources play an important role. Colored Petri Nets combine the strengths of Classical Petri Nets with the power of a high-level programming language. Coloured Petri Nets have both, formal intuitive and graphical presentations. Graphical CPN model consists of a set of interacting modules which include a network of places, transitions and arcs. Mathematical representation has a well-defined syntax and semantics, as well as defines system behavioural properties. One of the best known features used in biometric is the human finger print pattern. During the last decade other human features have become of interest, such as iris-based or face recognition. The objective of this paper is to introduce the fundamental concepts of Petri Nets in relation to tooth shape analysis. Biometric identification systems functioning has two phases: data enrollment phase and identification phase. During the data enrollment phase images of teeth are added to database. This record contains enrollment data as a noisy version of the biometrical data corresponding to the individual. During the identification phase an unknown individual is observed again and is compared to the enrollment data in the database and then system estimates the individual. The purpose of modeling biometric identification system by means of Petri Nets is to reveal the following aspects of the functioning model: the efficiency of the model, behavior of the model, mistakes and accidents in the model, feasibility of the model simplification or substitution of its separate components for more effective components without interfering system functioning. The results of biometric identification system modeling and evaluating are presented and discussed.

  1. Case studies using the United States Coast Guard's Oil Identification System for petroleum spill source identification

    International Nuclear Information System (INIS)

    Grosser, P.W.; Castellano, F.P.

    1993-01-01

    The Oil Identification System (OIS) was developed in the 1970's at the Coast Guard Research and Development Center, to determine the unique, intrinsic properties which would allow the matching of a spilled oil with its correct source. The Central Oil Identification Laboratory (COIL) was established in 1978 as the operating facility to implement the OIS. The OIS encompasses four analytical methods; thin layer chromatography, fluorescence spectroscopy, infrared spectroscopy and gas chromatography. A sample can be studied according to each individual method or multi-methods approach can be chosen if no single technique gives unequivocal results. Combined these methods are greater than 99% effective. The authors recently utilized the OIS and the COIL for three petroleum spill investigations in New York. As part of the investigation to determine the source(s) of several different petroleum product spills, OIS was conducted along with a review of groundwater sample chromatograms

  2. DNA based identification of medicinal materials in Chinese patent medicines

    Science.gov (United States)

    Chen, Rong; Dong, Juan; Cui, Xin; Wang, Wei; Yasmeen, Afshan; Deng, Yun; Zeng, Xiaomao; Tang, Zhuo

    2012-12-01

    Chinese patent medicines (CPM) are highly processed and easy to use Traditional Chinese Medicine (TCM). The market for CPM in China alone is tens of billions US dollars annually and some of the CPM are also used as dietary supplements for health augmentation in the western countries. But concerns continue to be raised about the legality, safety and efficacy of many popular CPM. Here we report a pioneer work of applying molecular biotechnology to the identification of CPM, particularly well refined oral liquids and injections. What's more, this PCR based method can also be developed to an easy to use and cost-effective visual chip by taking advantage of G-quadruplex based Hybridization Chain Reaction. This study demonstrates that DNA identification of specific Medicinal materials is an efficient and cost-effective way to audit highly processed CPM and will assist in monitoring their quality and legality.

  3. An Innovative Fuzzy-Logic-Based Methodology for Trend Identification

    International Nuclear Information System (INIS)

    Wang Xin; Tsoukalas, Lefteri H.; Wei, Thomas Y.C.; Reifman, Jaques

    2001-01-01

    A new fuzzy-logic-based methodology for on-line signal trend identification is introduced. The methodology may be used for detecting the onset of nuclear power plant (NPP) transients at the earliest possible time and could be of great benefit to diagnostic, maintenance, and performance-monitoring programs. Although signal trend identification is complicated by the presence of noise, fuzzy methods can help capture important features of on-line signals, integrate the information included in these features, and classify incoming NPP signals into increasing, decreasing, and steady-state trend categories. A computer program named PROTREN is developed and tested for the purpose of verifying this methodology using NPP and simulation data. The results indicate that the new fuzzy-logic-based methodology is capable of detecting transients accurately, it identifies trends reliably and does not misinterpret a steady-state signal as a transient one

  4. A Heterogeneous Wireless Identification Network for the Localization of Animals Based on Stochastic Movements

    Directory of Open Access Journals (Sweden)

    Ivana Raos

    2009-05-01

    Full Text Available The improvement in the transmission range in wireless applications without the use of batteries remains a significant challenge in identification applications. In this paper, we describe a heterogeneous wireless identification network mostly powered by kinetic energy, which allows the localization of animals in open environments. The system relies on radio communications and a global positioning system. It is made up of primary and secondary nodes. Secondary nodes are kinetic-powered and take advantage of animal movements to activate the node and transmit a specific identifier, reducing the number of batteries of the system. Primary nodes are battery-powered and gather secondary-node transmitted information to provide it, along with position and time data, to a final base station in charge of the animal monitoring. The system allows tracking based on contextual information obtained from statistical data.

  5. Two-dimensional PCA-based human gait identification

    Science.gov (United States)

    Chen, Jinyan; Wu, Rongteng

    2012-11-01

    It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

  6. Identification of cholinergic synaptic transmission in the insect nervous system.

    Science.gov (United States)

    Thany, Steeve Hervé; Tricoire-Leignel, Hélène; Lapied, Bruno

    2010-01-01

    A major criteria initially used to localize cholinergic neuronal elements in nervous systems tissues that involve acetylcholine (ACh) as neurotransmitter is mainly based on immunochemical studies using choline acetyltransferase (ChAT), an enzyme which catalyzes ACh biosynthesis and the ACh degradative enzyme named acetylcholinesterase (AChE). Immunochemical studies using anti-ChAT monoclonal antibody have allowed the identification of neuronal processes and few types of cell somata that contain ChAT protein. In situ hybridization using cRNA probes to ChAT or AChE messenger RNA have brought new approaches to further identify cell bodies transcribing the ChAT or AChE genes. Combined application of all these techniques reveals a widespread expression of ChAT and AChE activities in the insect central nervous system and peripheral sensory neurons which implicates ACh as a key neurotransmitter. The discovery of the snake toxin alpha-bungatoxin has helped to identify nicotinic acetylcholine receptors (nAChRs). In fact, nicotine when applied to insect neurons, resulted in the generation of an inward current through the activation of nicotinic receptors which were blocked by alpha-bungarotoxin. Thus, insect nAChRs have been divided into two categories, sensitive and insensitive to this snake toxin. Up to now, the recent characterization and distribution pattern of insect nAChR subunits and the biochemical evidence that the insect central nervous system contains different classes of cholinergic receptors indicated that ACh is involved in several sensory pathways.

  7. Single camera photogrammetry system for EEG electrode identification and localization.

    Science.gov (United States)

    Baysal, Uğur; Sengül, Gökhan

    2010-04-01

    In this study, photogrammetric coordinate measurement and color-based identification of EEG electrode positions on the human head are simultaneously implemented. A rotating, 2MP digital camera about 20 cm above the subject's head is used and the images are acquired at predefined stop points separated azimuthally at equal angular displacements. In order to realize full automation, the electrodes have been labeled by colored circular markers and an electrode recognition algorithm has been developed. The proposed method has been tested by using a plastic head phantom carrying 25 electrode markers. Electrode locations have been determined while incorporating three different methods: (i) the proposed photogrammetric method, (ii) conventional 3D radiofrequency (RF) digitizer, and (iii) coordinate measurement machine having about 6.5 mum accuracy. It is found that the proposed system automatically identifies electrodes and localizes them with a maximum error of 0.77 mm. It is suggested that this method may be used in EEG source localization applications in the human brain.

  8. 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.

  9. 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.

  10. Wavelet-based blind identification of the UCLA Factor building using ambient and earthquake responses

    International Nuclear Information System (INIS)

    Hazra, B; Narasimhan, S

    2010-01-01

    Blind source separation using second-order blind identification (SOBI) has been successfully applied to the problem of output-only identification, popularly known as ambient system identification. In this paper, the basic principles of SOBI for the static mixtures case is extended using the stationary wavelet transform (SWT) in order to improve the separability of sources, thereby improving the quality of identification. Whereas SOBI operates on the covariance matrices constructed directly from measurements, the method presented in this paper, known as the wavelet-based modified cross-correlation method, operates on multiple covariance matrices constructed from the correlation of the responses. The SWT is selected because of its time-invariance property, which means that the transform of a time-shifted signal can be obtained as a shifted version of the transform of the original signal. This important property is exploited in the construction of several time-lagged covariance matrices. The issue of non-stationary sources is addressed through the formation of several time-shifted, windowed covariance matrices. Modal identification results are presented for the UCLA Factor building using ambient vibration data and for recorded responses from the Parkfield earthquake, and compared with published results for this building. Additionally, the effect of sensor density on the identification results is also investigated

  11. Village Building Identification Based on Ensemble Convolutional Neural Networks

    Science.gov (United States)

    Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

    2017-01-01

    In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

  12. Variation in Microbial Identification System Accuracy for Yeast Identification Depending on Commercial Source of Sabouraud Dextrose Agar

    OpenAIRE

    Kellogg, James A.; Bankert, David A.; Chaturvedi, Vishnu

    1999-01-01

    The accuracy of the Microbial Identification System (MIS; MIDI, Inc.) for identification of yeasts to the species level was compared by using 438 isolates grown on prepoured BBL Sabouraud dextrose agar (SDA) and prepoured Remel SDA. Correct identification was observed for 326 (74%) of the yeasts cultured on BBL SDA versus only 214 (49%) of yeasts grown on Remel SDA (P < 0.001). The commercial source of the SDA used in the MIS procedure significantly influences the system’s accuracy.

  13. Data model for the collaboration between land administration systems and agricultural land parcel identification systems.

    Science.gov (United States)

    Inan, Halil Ibrahim; Sagris, Valentina; Devos, Wim; Milenov, Pavel; van Oosterom, Peter; Zevenbergen, Jaap

    2010-12-01

    The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Event storm detection and identification in communication systems

    International Nuclear Information System (INIS)

    Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

    2006-01-01

    Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

  15. System Identification and Resonant Control of Thermoacoustic Engines for Robust Solar Power

    Directory of Open Access Journals (Sweden)

    Boe-Shong Hong

    2015-05-01

    Full Text Available It was found that thermoacoustic solar-power generators with resonant control are more powerful than passive ones. To continue the work, this paper focuses on the synthesis of robustly resonant controllers that guarantee single-mode resonance not only in steady states, but also in transient states when modelling uncertainties happen and working temperature temporally varies. Here the control synthesis is based on the loop shifting and the frequency-domain identification in advance thereof. Frequency-domain identification is performed to modify the mathematical modelling and to identify the most powerful mode, so that the DSP-based feedback controller can online pitch the engine to the most powerful resonant-frequency robustly and accurately. Moreover, this paper develops two control tools, the higher-order van-der-Pol oscillator and the principle of Dynamical Equilibrium, to assist in system identification and feedback synthesis, respectively.

  16. Hydrogel based occlusion systems

    NARCIS (Netherlands)

    Stam, F.A.; Jackson, N.; Dubruel, P.; Adesanya, K.; Embrechts, A.; Mendes, E.; Neves, H.P.; Herijgers, P.; Verbrugghe, Y.; Shacham, Y.; Engel, L.; Krylov, V.

    2013-01-01

    A hydrogel based occlusion system, a method for occluding vessels, appendages or aneurysms, and a method for hydrogel synthesis are disclosed. The hydrogel based occlusion system includes a hydrogel having a shrunken and a swollen state and a delivery tool configured to deliver the hydrogel to a

  17. Sub-word based Arabic handwriting analysis for writer identification

    Science.gov (United States)

    Maliki, Makki; Al-Jawad, Naseer; Jassim, Sabah

    2013-05-01

    Analysing a text or part of it is key to handwriting identification. Generally, handwriting is learnt over time and people develop habits in the style of writing. These habits are embedded in special parts of handwritten text. In Arabic each word consists of one or more sub-word(s). The end of each sub-word is considered to be a connect stroke. The main hypothesis in this paper is that sub-words are essential reflection of Arabic writer's habits that could be exploited for writer identification. Testing this hypothesis will be based on experiments that evaluate writer's identification, mainly using K nearest neighbor from group of sub-words extracted from longer text. The experimental results show that using a group of sub-words could be used to identify the writer with a successful rate between 52.94 % to 82.35% when top1 is used, and it can go up to 100% when top5 is used based on K nearest neighbor. The results show that majority of writers are identified using 7 sub-words with a reliability confident of about 90% (i.e. 90% of the rejected templates have significantly larger distances to the tested example than the distance from the correctly identified template). However previous work, using a complete word, shows successful rate of at most 90% in top 10.

  18. Diagnosis and Model Based Identification of a Coupling Misalignment

    Directory of Open Access Journals (Sweden)

    P. Pennacchi

    2005-01-01

    Full Text Available This paper is focused on the application of two different diagnostic techniques aimed to identify the most important faults in rotating machinery as well as on the simulation and prediction of the frequency response of rotating machines. The application of the two diagnostics techniques, the orbit shape analysis and the model based identification in the frequency domain, is described by means of an experimental case study that concerns a gas turbine-generator unit of a small power plant whose rotor-train was affected by an angular misalignment in a flexible coupling, caused by a wrong machine assembling. The fault type is identified by means of the orbit shape analysis, then the equivalent bending moments, which enable the shaft experimental vibrations to be simulated, have been identified using a model based identification method. These excitations have been used to predict the machine vibrations in a large rotating speed range inside which no monitoring data were available. To the best of the authors' knowledge, this is the first case of identification of coupling misalignment and prediction of the consequent machine behaviour in an actual size rotating machinery. The successful results obtained emphasise the usefulness of integrating common condition monitoring techniques with diagnostic strategies.

  19. TLM modeling and system identification of optimized antenna structures

    Directory of Open Access Journals (Sweden)

    N. Fichtner

    2008-05-01

    Full Text Available The transmission line matrix (TLM method in conjunction with the genetic algorithm (GA is presented for the bandwidth optimization of a low profile patch antenna. The optimization routine is supplemented by a system identification (SI procedure. By the SI the model parameters of the structure are estimated which is used for a reduction of the total TLM simulation time. The SI utilizes a new stability criterion of the physical poles for the parameter extraction.

  20. Aerial Remote Radio Frequency Identification System for Small Vessel Monitoring

    Science.gov (United States)

    2009-12-01

    technology as a tool that can benefit everyone (Warner 2008, p.144). Lippitt’s model , coupled with Vroom and Lawler’s Expectancy Theory (Miner 2005, p...Identification System for Small Vessel Monitoring 6. AUTHOR( S ) Jason Appler, Sean Finney, Michael McMellon 5. FUNDING NUMBERS 7. PERFORMING...ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING

  1. System identification of an unmanned quadcopter system using MRAN neural

    Science.gov (United States)

    Pairan, M. F.; Shamsudin, S. S.

    2017-12-01

    This project presents the performance analysis of the radial basis function neural network (RBF) trained with Minimal Resource Allocating Network (MRAN) algorithm for real-time identification of quadcopter. MRAN’s performance is compared with the RBF with Constant Trace algorithm for 2500 input-output pair data sampling. MRAN utilizes adding and pruning hidden neuron strategy to obtain optimum RBF structure, increase prediction accuracy and reduce training time. The results indicate that MRAN algorithm produces fast training time and more accurate prediction compared with standard RBF. The model proposed in this paper is capable of identifying and modelling a nonlinear representation of the quadcopter flight dynamics.

  2. 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

  3. Systems and methods for remote long standoff biometric identification using microwave cardiac signals

    Science.gov (United States)

    McGrath, William R. (Inventor); Talukder, Ashit (Inventor)

    2012-01-01

    Systems and methods for remote, long standoff biometric identification using microwave cardiac signals are provided. In one embodiment, the invention relates to a method for remote biometric identification using microwave cardiac signals, the method including generating and directing first microwave energy in a direction of a person, receiving microwave energy reflected from the person, the reflected microwave energy indicative of cardiac characteristics of the person, segmenting a signal indicative of the reflected microwave energy into a waveform including a plurality of heart beats, identifying patterns in the microwave heart beats waveform, and identifying the person based on the identified patterns and a stored microwave heart beats waveform.

  4. Closed-loop Identification for Control of Linear Parameter Varying Systems

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2014-01-01

    , closed- loop system identification is more difficult than open-loop identification. In this paper we prove that the so-called Hansen Scheme, a technique known from linear time-invariant systems theory for transforming closed-loop system identification problems into open-loop-like problems, can...

  5. Tip-tilt disturbance model identification based on non-linear least squares fitting for Linear Quadratic Gaussian control

    Science.gov (United States)

    Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing

    2018-05-01

    We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.

  6. Development of a wireless protection against imitation system for identification and control of vehicle access

    Directory of Open Access Journals (Sweden)

    Aleksei A. Gavrishev

    2018-03-01

    Full Text Available This article deals with wireless systems for identification and control of vehicle access to protected objects. Known systems are considered. As a result, it has been established that one of the most promising approaches to identifying and controlling vehicle access to protected objects is the use of systems based on the "friend or foe" principle. Among these systems, there are "one-directional" and "bedirectional" identification and access control systems. "Bidirectional" systems are more preferable for questions of identification and access control. However, at present, these systems should have a reduced probability of recognizing the structure of the request and response signals because the potential attacker can easily perform unauthorized access to the radio channel of the system. On this basis, developed a wireless system identification and control vehicle access to protected objects based on the principle of "friend or foe", featuring increased protection from unauthorized access and jamming through the use of rewritable drives chaotic sequences. In addition, it’s proposed to use to identify the vehicle's RFID tag containing additional information about it. Are some specifications of the developed system (the possible frequency range of the request-response signals, the communication range, data rate, the size of the transmitted data, guidelines for choosing RFID. Also, with the help of fuzzy logic, was made the security assessment from unauthorized access request-response signals based on the system of "friend or foe", which are transferred via radio channel, developed systems and analogues. The security assessment of the developed system shows an adequate degree of protection against complex threats (view, spoofing, interception and jamming of traffic in comparison with known systems of this class. Among the main advantages of the developed system it’s necessary to mention increased security from unauthorized access and jamming

  7. An Efficient Human Identification through MultiModal Biometric System

    Directory of Open Access Journals (Sweden)

    K. Meena

    Full Text Available ABSTRACT Human identification is essential for proper functioning of society. Human identification through multimodal biometrics is becoming an emerging trend, and one of the reasons is to improve recognition accuracy. Unimodal biometric systems are affected by various problemssuch as noisy sensor data,non-universality, lack of individuality, lack of invariant representation and susceptibility to circumvention.A unimodal system has limited accuracy. Hence, Multimodal biometric systems by combining more than one biometric feature in different levels are proposed in order to enhance the performance of the system. A supervisor module combines the different opinions or decisions delivered by each subsystem and then make a final decision. In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. Biometric features are extracted by Local Derivative Ternary Pattern (LDTP in Contourlet domain and an extensive evaluation of LDTP is done using Support Vector Machine and Nearest Neighborhood Classifier. The experimental evaluations are performed on a public dataset demonstrating the accuracy of the proposed system compared with the existing systems. It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time.

  8. The Automated Threaded Fastening Based on On-line Identification

    Directory of Open Access Journals (Sweden)

    Nicolas Ivan Giannoccaro

    2008-11-01

    Full Text Available The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.

  9. High Resolution Spectrometer (HRS) particle-identification system

    International Nuclear Information System (INIS)

    Pratt, J.C.; Spencer, J.E.; Whitten, C.A.

    1977-08-01

    The functions of the particle-identification system (PIDS) designed for the High Resolution Spectrometer facility (HRS) at LAMPF are described, together with the mechanical layout, counter hardware, and associated electronics. The system was designed for easy use and to be applicable to currently proposed experiments at HRS. The several strobe signals that can be generated correspond to different event types or characteristics, and logic configuration and timing can be remotely controlled by computer. Concepts of discrete pattern recognition and multidimensional, analog pulse discrimination are used to distinguish between different event types

  10. Design and development of a prototype hot spot identification system

    International Nuclear Information System (INIS)

    Jain, Amit; Thakur, Vaishali M.; Anilkumar, Rekha; Sawant, Pravin; Chaudhury, Probal; Pradeepkumar, K.S.

    2015-01-01

    The proper assessment of radiological environments inside nuclear facilities require accurate spatial mapping of the gamma ray field. A prototype Hotspot Identification System has been designed and developed in-house for gamma ray imaging by combining a gamma spectrometer with a pinhole collimator and a digital camera. The system can rapidly determine the location, distribution and intensity of gamma ray sources by carrying a scan of the suspected locations. The measured data was compared with simulated values for NaI(Tl) response, generated using the MCNP 4B Transport code. The data obtained by experimental and theoretical method are in good agreement. (author)

  11. System for identification of microorganism and detection of infectious disorder

    DEFF Research Database (Denmark)

    2013-01-01

    Methods for the identification of microorganisms or infectious disorders are disclosed, comprising obtaining a suitable sample from sources such as persons, animals, plants, food, water or soil. The methods also comprise providing tailored nucleic acid substrate(s) designed to react with a type 1...... topoisomerase from one or more microorganism(s) or infectious agent(s), and incubating said substrate with said sample, or extracts or preparations from the sample, so that the substrate is processed by said topoisomerase if said microorganism(s) or infectious agent(s) is present in the sample. Finally......, processed substrates are identified and potentially quantified by one or more of a range of standard molecular biology methods and read-out systems. The identification and potential quantification of microorganisms and infectious agents, including but not limited to Plasmodium falciparum and Mycobacterium...

  12. Development of a New Marker System for Identification of Spirodela polyrhiza and Landoltia punctata

    Directory of Open Access Journals (Sweden)

    Bo Feng

    2017-01-01

    Full Text Available Lemnaceae (commonly called duckweed is an aquatic plant ideal for quantitative analysis in plant sciences. Several species of this family represent the smallest and fastest growing flowering plants. Different ecotypes of the same species vary in their biochemical and physiological properties. Thus, selecting of desirable ecotypes of a species is very important. Here, we developed a simple and rapid molecular identification system for Spirodela polyrhiza and Landoltia punctata based on the sequence polymorphism. First, several pairs of primers were designed and three markers were selected as good for identification. After PCR amplification, DNA fragments (the combination of three PCR products in different duckweeds were detected using capillary electrophoresis. The high-resolution capillary electrophoresis displayed high identity to the sequencing results. The combination of the PCR products containing several DNA fragments highly improved the identification frequency. These results indicate that this method is not only good for interspecies identification but also ideal for intraspecies distinguishing. Meanwhile, 11 haplotypes were found in both the S. polyrhiza and L. punctata ecotypes. The results suggest that this marker system is useful for large-scale identification of duckweed and for the screening of desirable ecotypes to improve the diverse usage in duckweed utilization.

  13. Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture

    Science.gov (United States)

    Steele, Kerry D [Kennewick, WA; Anderson, Gordon A [Benton City, WA; Gilbert, Ronald W [Morgan Hill, CA

    2011-02-01

    Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture are described. In one aspect, a communications device identification method includes providing identification information regarding a group of wireless identification devices within a wireless communications range of a reader, using the provided identification information, selecting one of a plurality of different search procedures for identifying unidentified ones of the wireless identification devices within the wireless communications range, and identifying at least some of the unidentified ones of the wireless identification devices using the selected one of the search procedures.

  14. Model-based version management system framework

    International Nuclear Information System (INIS)

    Mehmood, W.

    2016-01-01

    In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

  15. Evaluation of the RapID-ANA system for identification of anaerobic bacteria of veterinary origin.

    Science.gov (United States)

    Adney, W S; Jones, R L

    1985-12-01

    This study evaluated the ability of the RapID-ANA system (Innovative Diagnostic Systems, Inc., Atlanta, Ga.) to accurately identify a spectrum of freshly isolated veterinary anaerobes. A total of 183 isolates were tested and included 7 Actinomyces spp., 53 Bacteroides spp., 32 Clostridium spp., 2 Eubacterium spp., 65 Fusobacterium spp., 1 Peptococcus spp., 22 Peptostreptococcus spp., and 1 Propionibacterium spp. All isolates were initially identified by conventional biochemical testing and gas-liquid chromatography of short-chain fatty acid metabolites. Additional tests were performed as required by the RapID-ANA system. Of these isolates, 81.4% were correctly identified to the genus level, including 59.6% to the species level, 14.2% were incorrectly identified at the genus level, and 4.4% were not identified. Initially, 20.2% of the strains were not identified because the microcodes were not in the code book. The majority of the incorrect identifications were caused by the misidentification of Fusobacterium spp. as Bacteroides spp. Errors also occurred when veterinary anaerobes not included in the data base were assigned an identification from the existing data base. The RapID-ANA system appears to be a promising new method for rapid identification of veterinary anaerobes; however, further evaluation with an extended data base is needed before the system can accurately identify all clinically significant anaerobes.

  16. Application of neural networks to connectional expert system for identification of transients in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Kim, Wan Joo; Chang, Soon Heung; Roh, Myung Sub

    1991-01-01

    The Back-propagation Neural Network (BPN) algorithm is applied to connectionist expert system for the identification of BWR transients. Several powerful features of neural network-based expert systems over traditional rule-based expert systems are described. The general mapping capability of the neural networks enables to identify transients easily. A number of case studies were performed with emphasis on the applicability of the neural networks to the diagnostic domain. It is revealed that the BPN algorithm can identify transients properly, even when incomplete or untrained symptoms are given. It is also shown that multiple transients are easily identified

  17. Experimental evaluation of a quasi-modal parameter based rotor foundation identification technique

    Science.gov (United States)

    Yu, Minli; Liu, Jike; Feng, Ningsheng; Hahn, Eric J.

    2017-12-01

    Correct modelling of the foundation of rotating machinery is an invaluable asset in model-based rotor dynamic study. One attractive approach for such purpose is to identify the relevant modal parameters of an equivalent foundation using the motion measurements of rotor and foundation at the bearing supports. Previous research showed that, a complex quasi-modal parameter based system identification technique could be feasible for this purpose; however, the technique was only validated by identifying simple structures under harmonic excitation. In this paper, such identification technique is further extended and evaluated by identifying the foundation of a numerical rotor-bearing-foundation system and an experimental rotor rig respectively. In the identification of rotor foundation with multiple bearing supports, all application points of excitation forces transmitted through bearings need to be included; however the assumed vibration modes far outside the rotor operating speed cannot or not necessary to be identified. The extended identification technique allows one to identify correctly an equivalent foundation with fewer modes than the assumed number of degrees of freedom, essentially by generalising the technique to be able to handle rectangular complex modal matrices. The extended technique is robust in numerical and experimental validation and is therefore likely to be applicable in the field.

  18. Heart Sound Biometric System Based on Marginal Spectrum Analysis

    Science.gov (United States)

    Zhao, Zhidong; Shen, Qinqin; Ren, Fangqin

    2013-01-01

    This work presents a heart sound biometric system based on marginal spectrum analysis, which is a new feature extraction technique for identification purposes. This heart sound identification system is comprised of signal acquisition, pre-processing, feature extraction, training, and identification. Experiments on the selection of the optimal values for the system parameters are conducted. The results indicate that the new spectrum coefficients result in a significant increase in the recognition rate of 94.40% compared with that of the traditional Fourier spectrum (84.32%) based on a database of 280 heart sounds from 40 participants. PMID:23429515

  19. Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset

    NARCIS (Netherlands)

    M.K. Chan (Man K.); M.-O. Krebs (M-O); D. Cox; P.C. Guest (Paul); R.H. Yolken; H. Rahmoune (Hassan); M. Rothermundt (Matthias); J. Steiner (Johann); F.M. Leweke (Marcus); N.J.M. van Beveren (Nico); D. Niebuhr (David); N. Weber (Natalya); D. Cowan (David); P. Suarez-Pinilla; B. Crespo-Facorro (Benedicto); C. Mam-Lam-Fook; J. Bourgin; R.J. Wenstrup (Richard); R.R. Kaldate; J.D. Cooper (Jason); S. Bahn (Sabine)

    2015-01-01

    markdownabstractRecent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based

  20. Acute asthma severity identification of expert system flow in emergency department

    Science.gov (United States)

    Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

    2017-11-01

    Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

  1. 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.

  2. Model identification methodology for fluid-based inerters

    Science.gov (United States)

    Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew

    2018-06-01

    Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.

  3. The KKS power plant identification system. 3. ed.

    International Nuclear Information System (INIS)

    1988-01-01

    The previous first and second editions of the KKS, system for power plant identification, consisted of the following: introduction; instructions for application with a comparative presentation of the DIN/KKS systems and subject index; keys (functional key, equipment key, operating media key). The third edition now available incorporates the following revisions and additions: instructions for application refer exclusively to the KKS system; key updates; revised coordinating file for the equipment key and operating media key; a completely new section entitled 'Agreements for coordination of project activities', in an annex to the KKS instructions; comparison DIN/KKS adapted to new version of KKS instructions; the subject index of the 2nd edition has been extended by a keyword index referring to the explanations for application of the KKS system. (orig./HP) [de

  4. Creation of hybrid optoelectronic systems for document identification

    Science.gov (United States)

    Muravsky, Leonid I.; Voronyak, Taras I.; Kulynych, Yaroslav P.; Maksymenko, Olexander P.; Pogan, Ignat Y.

    2001-06-01

    Use of security devices based on a joint transform correlator (JTC) architecture for identification of credit cards and other products is very promising. The experimental demonstration of the random phase encoding technique for security verification shows that hybrid JTCs can be successfully utilized. The random phase encoding technique provides a very high protection level of products and things to be identified. However, the realization of this technique is connected with overcoming of the certain practical problems. To solve some of these problems and simultaneously to improve the security of documents and other products, we propose to use a transformed phase mask (TPM) as an input object in an optical correlator. This mask is synthesized from a random binary pattern (RBP), which is directly used to fabricate a reference phase mask (RPM). To obtain the TPM, we previously separate the RBP on a several parts (for example, K parts) of an arbitrary shape and further fabricate the TPM from this transformed RBP. The fabricated TPM can be bonded as the optical mark to any product or thing to be identified. If the RPM and the TPM are placed on the optical correlator input, the first diffracted order of the output correlation signal is containing the K narrow autocorrelation peaks. The distances between the peaks and the peak's intensities can be treated as the terms of the identification feature vector (FV) for the TPM identification.

  5. Resting State EEG-based biometrics for individual identification using convolutional neural networks.

    Science.gov (United States)

    Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

    2015-08-01

    Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

  6. Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

    Science.gov (United States)

    Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

    2014-05-01

    By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

  7. Evidence based guidelines for the prevention, identification, and management of occupational asthma.

    Science.gov (United States)

    Nicholson, P J; Cullinan, P; Taylor, A J Newman; Burge, P S; Boyle, C

    2005-05-01

    Occupational asthma is the most frequently reported work related respiratory disease in many countries. This work was commissioned by the British Occupational Health Research Foundation to assist the Health and Safety Executive in achieving its target of reducing the incidence of occupational asthma in Great Britain by 30% by 2010. The guidelines aim to improve the prevention, identification, and management of occupational asthma by providing evidence based recommendations on which future practice can be based. The literature was searched systematically using Medline and Embase for articles published in all languages up to the end of June 2004. Evidence based statements and recommendations were graded according to the Royal College of General Practitioner's star system and the revised Scottish Intercollegiate Guidelines Network grading system. A total of 474 original studies were selected for appraisal from over 2500 abstracts. The systematic review produced 52 graded evidence statements and 22 recommendations based on 223 studies. Evidence based guidelines have become benchmarks for practice in healthcare and the process used to prepare them is well established. This evidence review and its recommendations focus on interventions and outcomes to provide a robust approach to the prevention, identification, and management of occupational asthma, based on and using the best available medical evidence. The most important action to prevent cases of occupational asthma is to reduce exposure at source. Thereafter surveillance should be performed for the early identification of symptoms, including occupational rhinitis, with additional functional and immunological tests where appropriate. Effective management of workers suspected to have occupational asthma involves the identification and investigation of symptoms suggestive of asthma immediately they occur. Those workers who are confirmed to have occupational asthma should be advised to avoid further exposure completely

  8. Methods, Systems and Apparatuses for Radio Frequency Identification

    Science.gov (United States)

    Fink, Patrick W. (Inventor); Chu, Andrew W. (Inventor); Lin, Gregory Y. (Inventor); Kennedy, Timothy F. (Inventor); Ngo, Phong H. (Inventor); Brown, Dewey T. (Inventor); Byerly, Diane (Inventor)

    2017-01-01

    A system for radio frequency identification (RFID) includes an enclosure defining an interior region interior to the enclosure, and a feed for generating an electromagnetic field in the interior region in response to a signal received from an RFID reader via a radio frequency (RF) transmission line and, in response to the electromagnetic field, receiving a signal from an RFID sensor attached to an item in the interior region. The structure of the enclosure may be conductive and may include a metamaterial portion, an electromagnetically absorbing portion, or a wall extending in the interior region. Related apparatuses and methods for performing RFID are provided.

  9. Rotor-System Log-Decrement Identification Using Short-Time Fourier-Transform Filter

    Directory of Open Access Journals (Sweden)

    Qihang Li

    2015-01-01

    Full Text Available With the increase of the centrifugal compressor capability, such as large scale LNG and CO2 reinjection, the stability margin evaluation is crucial to assure the compressor work in the designed operating conditions in field. Improving the precision of parameter identification of stability is essential and necessary as well. Based on the time-varying characteristics of response vibration during the sine-swept process, a short-time Fourier transform (STFT filter was introduced to increase the signal-noise ratio and improve the accuracy of the estimated stability parameters. A finite element model was established to simulate the sine-swept process, and the simulated vibration signals were used to study the filtering effect and demonstrate the feasibility to identify the stability parameters by using Multiple-Input and Multiple-Output system identification method that combines the prediction error method and instrumental variable method. Simulation results show that the identification method with STFT filter improves the estimated accuracy much well and makes the curves of frequency response function clearer. Experiment was carried out on a test rig as well, which indicates the identification method is feasible in stability identification, and the results of experiment indicate that STFT filter works very well.

  10. Accident identification system with automatic detection of abnormal condition using quantum computation

    International Nuclear Information System (INIS)

    Nicolau, Andressa dos Santos; Schirru, Roberto; Lima, Alan Miranda Monteiro de

    2011-01-01

    Transient identification systems have been proposed in order to maintain the plant operating in safe conditions and help operators in make decisions in emergency short time interval with maximum certainty associated. This article presents a system, time independent and without the use of an event that can be used as a starting point for t = 0 (reactor scram, for instance), for transient/accident identification of a pressurized water nuclear reactor (PWR). The model was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the Nuclear Power Plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). Were used several sets of process variables in order to establish a minimum set of variables considered necessary and sufficient. The optimization step of the identification algorithm is based upon the paradigm of Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and works as a data mining tool. The results obtained with the QEA without the time variable are compatible to the techniques in the reference literature, for the transient identification problem, with less computational effort (number of evaluations). This system allows a solution that approximates the ideal solution, the Voronoi Vectors with only one partition for the classes of accidents with robustness. (author)

  11. A Gamma Memory Neural Network for System Identification

    Science.gov (United States)

    Motter, Mark A.; Principe, Jose C.

    1992-01-01

    A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

  12. Optimization-based topology identification of complex networks

    International Nuclear Information System (INIS)

    Tang Sheng-Xue; Chen Li; He Yi-Gang

    2011-01-01

    In many cases, the topological structures of a complex network are unknown or uncertain, and it is of significance to identify the exact topological structure. An optimization-based method of identifying the topological structure of a complex network is proposed in this paper. Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network. Then, an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem. Compared with the previous adaptive synchronization-based method, the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks. In some cases where the states of a complex network are only partially observable, the exact topological structure of a network can also be identified by using the proposed method. Finally, numerical simulations are provided to show the effectiveness of the proposed method. (general)

  13. [Progress in the spectral library based protein identification strategy].

    Science.gov (United States)

    Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

    2018-04-25

    Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

  14. 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.

  15. Identification of coagulase-negative staphylococci with the API staph system.

    OpenAIRE

    Gemmell, C G; Dawson, J E

    1982-01-01

    A kit for the identification of staphylococci based on the biochemical criteria proposed by Kloos and Schleifer (W.E. Kloos and K.H. Schleifer, J. Clin. Microbiol., 1:82-88, 1975) is now available commercially. The system was used to identify 100 strains of coagulase-negative staphylococci isolated from various body sites as the primary etiological agent of clinical infection. The increasing importance of staphylococci and their resistance to antibiotics provided the rationale for such an inv...

  16. Design and implementation of an identification system in construction site safety for proactive accident prevention.

    Science.gov (United States)

    Yang, Huanjia; Chew, David A S; Wu, Weiwei; Zhou, Zhipeng; Li, Qiming

    2012-09-01

    Identifying accident precursors using real-time identity information has great potential to improve safety performance in construction industry, which is still suffering from day to day records of accident fatality and injury. Based on the requirements analysis for identifying precursor and the discussion of enabling technology solutions for acquiring and sharing real-time automatic identification information on construction site, this paper proposes an identification system design for proactive accident prevention to improve construction site safety. Firstly, a case study is conducted to analyze the automatic identification requirements for identifying accident precursors in construction site. Results show that it mainly consists of three aspects, namely access control, training and inspection information and operation authority. The system is then designed to fulfill these requirements based on ZigBee enabled wireless sensor network (WSN), radio frequency identification (RFID) technology and an integrated ZigBee RFID sensor network structure. At the same time, an information database is also designed and implemented, which includes 15 tables, 54 queries and several reports and forms. In the end, a demonstration system based on the proposed system design is developed as a proof of concept prototype. The contributions of this study include the requirement analysis and technical design of a real-time identity information tracking solution for proactive accident prevention on construction sites. The technical solution proposed in this paper has a significant importance in improving safety performance on construction sites. Moreover, this study can serve as a reference design for future system integrations where more functions, such as environment monitoring and location tracking, can be added. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. A pattern recognition approach based on DTW for automatic transient identification in nuclear power plants

    International Nuclear Information System (INIS)

    Galbally, Javier; Galbally, David

    2015-01-01

    Highlights: • Novel transient identification method for NPPs. • Low-complexity. • Low training data requirements. • High accuracy. • Fully reproducible protocol carried out on a real benchmark. - Abstract: Automatic identification of transients in nuclear power plants (NPPs) allows monitoring the fatigue damage accumulated by critical components during plant operation, and is therefore of great importance for ensuring that usage factors remain within the original design bases postulated by the plant designer. Although several schemes to address this important issue have been explored in the literature, there is still no definitive solution available. In the present work, a new method for automatic transient identification is proposed, based on the Dynamic Time Warping (DTW) algorithm, largely used in other related areas such as signature or speech recognition. The novel transient identification system is evaluated on real operational data following a rigorous pattern recognition protocol. Results show the high accuracy of the proposed approach, which is combined with other interesting features such as its low complexity and its very limited requirements of training data

  18. SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

    Directory of Open Access Journals (Sweden)

    Demidova Liliya

    2017-01-01

    Full Text Available The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers on the base of the modified PSO algorithm, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.

  19. AFM-based identification of the dynamic properties of globular proteins: simulation study

    International Nuclear Information System (INIS)

    Kim, Deok Ho; Park, Jung Yul; Kim, Moon K.; Hong, Keum Shik

    2008-01-01

    Nowadays a mathematical model-based computational approach is getting more attention as an effective tool for understanding the mechanical behaviors of biological systems. To find the mechanical properties of the proteins required to build such a model, this paper investigates a real-time identification method based on an AFM nanomanipulation system. First, an AFM-based bio-characterization system is introduced. Second, a second-order time-varying linear model representing the interaction between an AFM cantilever and globular proteins in a solvent is presented. Finally, we address a real-time estimation method in which the results of AFM experiments are designed to be inputs of the state estimator proposed here. Our attention is restricted to a theoretical feasibility analysis of the proposed methodology. We simply set the mechanical properties of the particular protein such as mass, stiffness, and damping coefficient in the system model prior to running the simulation. Simulation results show very good agreement with the preset properties. We anticipate that the realization of the AFM-based bio-characterization system will also provide an experimental validation of the proposed identification procedure in the future. This methodology can be used to determine a model of protein motion for the purpose of computer simulation and for a real-time modification of protein deformation

  20. The PLR-DTW method for ECG based biometric identification.

    Science.gov (United States)

    Shen, Jun; Bao, Shu-Di; Yang, Li-Cai; Li, Ye

    2011-01-01

    There has been a surge of research on electrocardiogram (ECG) signal based biometric for person identification. Though most of the existing studies claimed that ECG signal is unique to an individual and can be a viable biometric, one of the main difficulties for real-world applications of ECG biometric is the accuracy performance. To address this problem, this study proposes a PLR-DTW method for ECG biometric, where the Piecewise Linear Representation (PLR) is used to keep important information of an ECG signal segment while reduce the data dimension at the same time if necessary, and the Dynamic Time Warping (DTW) is used for similarity measures between two signal segments. The performance evaluation was carried out on three ECG databases, and the existing method using wavelet coefficients, which was proved to have good accuracy performance, was selected for comparison. The analysis results show that the PLR-DTW method achieves an accuracy rate of 100% for identification, while the one using wavelet coefficients achieved only around 93%.

  1. A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

    Science.gov (United States)

    Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

    2016-01-01

    Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

  2. A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments

    Directory of Open Access Journals (Sweden)

    Anthony C. Dona

    2016-01-01

    Full Text Available Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR spectroscopy and mass spectrometry (MS, the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC, in a configuration known as LC–MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

  3. 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.

  4. On the orthogonalised reverse path method for nonlinear system identification

    Science.gov (United States)

    Muhamad, P.; Sims, N. D.; Worden, K.

    2012-09-01

    The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.

  5. Fault Features Extraction and Identification based Rolling Bearing Fault Diagnosis

    International Nuclear Information System (INIS)

    Qin, B; Sun, G D; Zhang L Y; Wang J G; HU, J

    2017-01-01

    For the fault classification model based on extreme learning machine (ELM), the diagnosis accuracy and stability of rolling bearing is greatly influenced by a critical parameter, which is the number of nodes in hidden layer of ELM. An adaptive adjustment strategy is proposed based on vibrational mode decomposition, permutation entropy, and nuclear kernel extreme learning machine to determine the tunable parameter. First, the vibration signals are measured and then decomposed into different fault feature models based on variation mode decomposition. Then, fault feature of each model is formed to a high dimensional feature vector set based on permutation entropy. Second, the ELM output function is expressed by the inner product of Gauss kernel function to adaptively determine the number of hidden layer nodes. Finally, the high dimension feature vector set is used as the input to establish the kernel ELM rolling bearing fault classification model, and the classification and identification of different fault states of rolling bearings are carried out. In comparison with the fault classification methods based on support vector machine and ELM, the experimental results show that the proposed method has higher classification accuracy and better generalization ability. (paper)

  6. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    Patan, Maciej

    2012-01-01

    Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

  7. System Identification of Wind Turbines for Structural Health Monitoring

    DEFF Research Database (Denmark)

    Perisic, Nevena

    Structural health monitoring is a multi-disciplinary engineering field that should allow the actual wind turbine maintenance programmes to evolve to the next level, hence increasing safety and reliability and decreasing turbines downtime. The main idea is to have a sensing system on the structure...... cases are considered, two practical problems from the wind industry are studied, i.e. monitoring of the gearbox shaft torque and the tower root bending moments. The second part of the thesis is focused on the influence of friction on the health of the wind turbine and on the nonlinear identification...... that monitors the system responses and notifies the operator when damages or degradations have been detected. However, some of the response signals that contain important information about the health of the wind turbine components cannot be directly measured, or measuring them is highly complex and costly...

  8. Autonomous identification of matrices in the APNea system

    International Nuclear Information System (INIS)

    Hensley, D.

    1995-01-01

    The APNea System is a passive and active neutron assay device which features imaging to correct for nonuniform distributions of source material. Since the imaging procedure requires a detailed knowledge of both the detection efficiency and the thermal neutron flux for (sub)volumes of the drum of interest, it is necessary to identify which mocked-up matrix, to be used for detailed characterization studies, best matches the matrix of interest. A methodology referred to as the external matrix probe (EMP) has been established which links external measures of a drum matrix to those of mocked-up matrices. These measures by themselves are sufficient to identify the appropriate mock matrix, from which the necessary characterization data are obtained. This independent matrix identification leads to an autonomous determination of the required system response parameters for the assay analysis

  9. Parametric system identification of catamaran for improving controller design

    Science.gov (United States)

    Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

    2018-01-01

    This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

  10. Computer Based Expert Systems.

    Science.gov (United States)

    Parry, James D.; Ferrara, Joseph M.

    1985-01-01

    Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

  11. Establishment of a Fast Chemical Identification System for screening of counterfeit drugs of macrolide antibiotics.

    Science.gov (United States)

    Hu, Chang-Qin; Zou, Wen-Buo; Hu, Wang-Sheng; Ma, Xiao-Kang; Yang, Min-Zhi; Zhou, Shi-Lin; Sheng, Jin-Fang; Li, Yuan; Cheng, Shuang-Hong; Xue, Jing

    2006-01-23

    A Fast Chemical Identification System (FCIS) consisting of two colour reactions based on functional groups in molecules of macrolide antibiotics and two TLC methods was developed for screening of fake macrolide drugs. The active ingredients could be extracted from their oral preparations by absolute alcohol. Sulfuric acid reaction as a common reaction of macrolides was first used to distinguish the macrolides from other types of drugs and then 16-membered macrolides and 14-membered ones were distinguished by potassium permanganate reactions depending on the time of loss of colour in the test solution; after which a TLC method carried out on a GF(254) plate (5 cm x 10 cm) was chosen to further identification of the macrolides. The mobile phase A consisting of ethyl acetate, hexane and ammonia (100:15:15, v/v) was used for the identification of 14-membered macrolides, and the mobile phase B consisting of trichloromethane, methanol and ammonia (100:5:1, v/v) was used for the identification of 16-membered ones. A suspected counterfeit macrolide preparation can be identified within 40 min. The system can be used under different conditions and has the virtues of robustness, simplicity and speed.

  12. Reliability of System Identification Techniques to Assess Standing Balance in Healthy Elderly.

    Directory of Open Access Journals (Sweden)

    Jantsje H Pasma

    Full Text Available System identification techniques have the potential to assess the contribution of the underlying systems involved in standing balance by applying well-known disturbances. We investigated the reliability of standing balance parameters obtained with multivariate closed loop system identification techniques.In twelve healthy elderly balance tests were performed twice a day during three days. Body sway was measured during two minutes of standing with eyes closed and the Balance test Room (BalRoom was used to apply four disturbances simultaneously: two sensory disturbances, to the proprioceptive and the visual system, and two mechanical disturbances applied at the leg and trunk segment. Using system identification techniques, sensitivity functions of the sensory disturbances and the neuromuscular controller were estimated. Based on the generalizability theory (G theory, systematic errors and sources of variability were assessed using linear mixed models and reliability was assessed by computing indexes of dependability (ID, standard error of measurement (SEM and minimal detectable change (MDC.A systematic error was found between the first and second trial in the sensitivity functions. No systematic error was found in the neuromuscular controller and body sway. The reliability of 15 of 25 parameters and body sway were moderate to excellent when the results of two trials on three days were averaged. To reach an excellent reliability on one day in 7 out of 25 parameters, it was predicted that at least seven trials must be averaged.This study shows that system identification techniques are a promising method to assess the underlying systems involved in standing balance in elderly. However, most of the parameters do not appear to be reliable unless a large number of trials are collected across multiple days. To reach an excellent reliability in one third of the parameters, a training session for participants is needed and at least seven trials of two

  13. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

    Directory of Open Access Journals (Sweden)

    Monica Villaverde

    2015-11-01

    Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  14. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    Science.gov (United States)

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-11-17

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  15. BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

    Science.gov (United States)

    Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

    2013-01-01

    De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

  16. Behavior Identification Based on Geotagged Photo Data Set

    Directory of Open Access Journals (Sweden)

    Guo-qi Liu

    2014-01-01

    Full Text Available The popularity of mobile devices has produced a set of image data with geographic information, time information, and text description information, which is called geotagged photo data set. The division of this kind of data by its behavior and the location not only can identify the user’s important location and daily behavior, but also helps users to sort the huge image data. This paper proposes a method to build an index based on multiple classification result, which can divide the data set multiple times and distribute labels to the data to build index according to the estimated probability of classification results in order to accomplish the identification of users’ important location and daily behaviors. This paper collects 1400 discrete sets of data as experimental data to verify the method proposed in this paper. The result of the experiment shows that the index and actual tagging results have a high inosculation.

  17. 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.

  18. Ontology-based validation and identification of regulatory phenotypes

    KAUST Repository

    Kulmanov, Maxat

    2018-01-31

    Motivation: Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations Results: We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. Our method can also be applied to the rule-based prediction of phenotypes from functions. We show that the predicted phenotypes can be utilized for identification of protein-protein interactions and gene-disease associations. Based on experimental functional annotations, we predict phenotypes for 1,986 genes in mouse and 7,301 genes in human for which no experimental phenotypes have yet been determined.

  19. Ontology-based validation and identification of regulatory phenotypes

    KAUST Repository

    Kulmanov, Maxat; Schofield, Paul N; Gkoutos, Georgios V; Hoehndorf, Robert

    2018-01-01

    Motivation: Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations Results: We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. Our method can also be applied to the rule-based prediction of phenotypes from functions. We show that the predicted phenotypes can be utilized for identification of protein-protein interactions and gene-disease associations. Based on experimental functional annotations, we predict phenotypes for 1,986 genes in mouse and 7,301 genes in human for which no experimental phenotypes have yet been determined.

  20. Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

    Science.gov (United States)

    Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

    2016-11-01

    This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.