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...

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.

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.

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.

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.

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

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.

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.

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.

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.

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%.

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.

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.

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.

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.

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...

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

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.

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

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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...

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.

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.

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.

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

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.

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.

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...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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)

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...

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.

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.

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

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.

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).

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).

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.

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...

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...

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.

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.

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.

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

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.

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"--

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...

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...

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

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.

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.

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.

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...

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.

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.

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.

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.

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...

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.

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

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...

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...

Performance study of LMS based adaptive algorithms for unknown system identification

Energy Technology Data Exchange (ETDEWEB)

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

2014-07-10

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

Performance study of LMS based adaptive algorithms for unknown system identification

International Nuclear Information System (INIS)

Javed, Shazia; Ahmad, Noor Atinah

2014-01-01

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

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.

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...

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,

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

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.

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.

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)

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.

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

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.

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)

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

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.

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.

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.

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.

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

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.

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)

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

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

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.

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

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.

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

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.

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.

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.

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.

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...

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%.

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.

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

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.

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)

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.

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.

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.

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 ...

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

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.  

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.

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

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

Directory of Open Access Journals (Sweden)

Chiu-Kuo LIANG

2015-06-01

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

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.

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

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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.

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...

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.

Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

International Nuclear Information System (INIS)

Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

2016-01-01

Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

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.

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.

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

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)

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

Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

Directory of Open Access Journals (Sweden)

Mokhamad Iklil Mustofa

2017-05-01

Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

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. 

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

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....

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....

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...

Sensor-based material tagging system

International Nuclear Information System (INIS)

Vercellotti, L.C.; Cox, R.W.; Ravas, R.J.; Schlotterer, J.C.

1991-01-01

Electronic identification tags are being developed for tracking material and personnel. In applying electronic identification tags to radioactive materials safeguards, it is important to measure attributes of the material to ensure that the tag remains with the material. The addition of a microcontroller with an on-board analog-to-digital converter to an electronic identification tag application-specific integrated-circuit has been demonstrated as means to provide the tag with sensor data. Each tag is assembled into a housing, which serves as a scale for measuring the weight of a paint-can-sized container and its contents. Temperature rise of the can above ambient is also measured, and a piezoelectric detector detects disturbances and immediately puts the tag into its alarm and beacon mode. Radiation measurement was also considered, but the background from nearby containers was found to be excessive. The sensor-based tagging system allows tracking of the material in cans as it is stored in vaults or is moved through the manufacturing process. The paper presents details of the sensor-based material tagging system and describes a demonstration system

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.

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. ...

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....

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 ...

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

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.

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.

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 ...

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

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.

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.

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%.

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].

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

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...

System identification through nonstationary data using Time-Frequency Blind Source Separation

Science.gov (United States)

Guo, Yanlin; Kareem, Ahsan

2016-06-01

Classical output-only system identification (SI) methods are based on the assumption of stationarity of the system response. However, measured response of buildings and bridges is usually non-stationary due to strong winds (e.g. typhoon, and thunder storm etc.), earthquakes and time-varying vehicle motions. Accordingly, the response data may have time-varying frequency contents and/or overlapping of modal frequencies due to non-stationary colored excitation. This renders traditional methods problematic for modal separation and identification. To address these challenges, a new SI technique based on Time-Frequency Blind Source Separation (TFBSS) is proposed. By selectively utilizing "effective" information in local regions of the time-frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties. This technique can also handle response with closely spaced modes which is a well-known challenge for the identification of large-scale structures. Based on the separated modal responses, frequency and damping can be easily identified using SI methods based on a single degree of freedom (SDOF) system. In addition to the exclusive advantage of handling non-stationary data and closely spaced modes, the proposed technique also benefits from the absence of the end effects and low sensitivity to noise in modal separation. The efficacy of the proposed technique is demonstrated using several simulation based studies, and compared to the popular Second-Order Blind Identification (SOBI) scheme. It is also noted that even some non-stationary response data can be analyzed by the stationary method SOBI. This paper also delineates non-stationary cases where SOBI and the proposed scheme perform comparably and highlights cases where the proposed approach is more advantageous. Finally, the performance of the

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

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...

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.

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.

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.

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.

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.

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.

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.

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

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.)

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.)

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.

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.

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.

Science.gov (United States)

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung; Lee, Jae Ho

2013-06-01

The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.

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.

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

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.

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

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.

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.

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)

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)

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

Identification of fractional-order systems with unknown initial values and structure

Energy Technology Data Exchange (ETDEWEB)

Du, Wei, E-mail: duwei0203@gmail.com [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Miao, Qingying, E-mail: qymiao@sjtu.edu.cn [School of Continuing Education, Shanghai Jiao Tong University, Shanghai 200030 (China); Tong, Le, E-mail: tongle0328@gmail.com [Faculty of Applied Science and Textiles, The Hong Kong Polytechnic University, Hong Kong (China); Tang, Yang [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China)

2017-06-21

In this paper, the identification problem of fractional-order chaotic systems is proposed and investigated via an evolutionary optimization approach. Different with other studies to date, this research focuses on the identification of fractional-order chaotic systems with not only unknown orders and parameters, but also unknown initial values and structure. A group of fractional-order chaotic systems, i.e., Lorenz, Lü, Chen, Rössler, Arneodo and Volta chaotic systems, are set as the system candidate pool. The identification problem of fractional-order chaotic systems in this research belongs to mixed integer nonlinear optimization in essence. A powerful evolutionary algorithm called composite differential evolution (CoDE) is introduced for the identification problem presented in this paper. Extensive experiments are carried out to show that the fractional-order chaotic systems with unknown initial values and structure can be successfully identified by means of CoDE. - Highlights: • Unknown initial values and structure are introduced in the identification of fractional-order chaotic systems; • Only a series of output is utilized in the identification of fractional-order chaotic systems; • CoDE is used for the identification problem and the results are satisfactory when compared with other DE variants.

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.

Ensemble of different approaches for a reliable person re-identification system

Directory of Open Access Journals (Sweden)

Loris Nanni

2016-07-01

Full Text Available An ensemble of approaches for reliable person re-identification is proposed in this paper. The proposed ensemble is built combining widely used person re-identification systems using different color spaces and some variants of state-of-the-art approaches that are proposed in this paper. Different descriptors are tested, and both texture and color features are extracted from the images; then the different descriptors are compared using different distance measures (e.g., the Euclidean distance, angle, and the Jeffrey distance. To improve performance, a method based on skeleton detection, extracted from the depth map, is also applied when the depth map is available. The proposed ensemble is validated on three widely used datasets (CAVIAR4REID, IAS, and VIPeR, keeping the same parameter set of each approach constant across all tests to avoid overfitting and to demonstrate that the proposed system can be considered a general-purpose person re-identification system. Our experimental results show that the proposed system offers significant improvements over baseline approaches. The source code used for the approaches tested in this paper will be available at https://www.dei.unipd.it/node/2357 and http://robotics.dei.unipd.it/reid/.

A MEMS-based, wireless, biometric-like security system

Science.gov (United States)

Cross, Joshua D.; Schneiter, John L.; Leiby, Grant A.; McCarter, Steven; Smith, Jeremiah; Budka, Thomas P.

2010-04-01

We present a system for secure identification applications that is based upon biometric-like MEMS chips. The MEMS chips have unique frequency signatures resulting from fabrication process variations. The MEMS chips possess something analogous to a "voiceprint". The chips are vacuum encapsulated, rugged, and suitable for low-cost, highvolume mass production. Furthermore, the fabrication process is fully integrated with standard CMOS fabrication methods. One is able to operate the MEMS-based identification system similarly to a conventional RFID system: the reader (essentially a custom network analyzer) detects the power reflected across a frequency spectrum from a MEMS chip in its vicinity. We demonstrate prototype "tags" - MEMS chips placed on a credit card-like substrate - to show how the system could be used in standard identification or authentication applications. We have integrated power scavenging to provide DC bias for the MEMS chips through the use of a 915 MHz source in the reader and a RF-DC conversion circuit on the tag. The system enables a high level of protection against typical RFID hacking attacks. There is no need for signal encryption, so back-end infrastructure is minimal. We believe this system would make a viable low-cost, high-security system for a variety of identification and authentication applications.

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

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

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.

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.

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)

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.

An Observed Voting System Based On Biometric Technique

Directory of Open Access Journals (Sweden)

B. Devikiruba

2015-08-01

Full Text Available ABSTRACT This article describes a computational framework which can run almost on every computer connected to an IP based network to study biometric techniques. This paper discusses with a system protecting confidential information puts strong security demands on the identification. Biometry provides us with a user-friendly method for this identification and is becoming a competitor for current identification mechanisms. The experimentation section focuses on biometric verification specifically based on fingerprints. This article should be read as a warning to those thinking of using methods of identification without first examine the technical opportunities for compromising mechanisms and the associated legal consequences. The development is based on the java language that easily improves software packages that is useful to test new control techniques.

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.

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.

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.

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.)

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.

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 ...

Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

Science.gov (United States)

Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

2017-07-01

Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

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....

PARAMETRIC IDENTIFICATION OF STOCHASTIC SYSTEM BY NON-GRADIENT RANDOM SEARCHING

Directory of Open Access Journals (Sweden)

A. A. Lobaty

2017-01-01

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

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…

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

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.

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.

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.

Identification of provenance rocks based on EPMA analyses of heavy minerals

Science.gov (United States)

Shimizu, M.; Sano, N.; Ueki, T.; Yonaga, Y.; Yasue, K. I.; Masakazu, N.

2017-12-01

Information on mountain building is significant in the field of geological disposal of high-level radioactive waste, because this affects long-term stability in groundwater flow system. Provenance analysis is one of effective approaches for understanding building process of mountains. Chemical compositions of heavy minerals, as well as their chronological data, can be an index for identification of provenance rocks. The accurate identification requires the measurement of as many grains as possible. In order to achieve an efficient provenance analysis, we developed a method for quick identification of heavy minerals using an Electron Probe Micro Analyzer (EPMA). In this method, heavy mineral grains extracted from a sample were aligned on a glass slide and mounted in a resin. Concentration of 28 elements was measured for 300-500 grains per sample using EPMA. To measure as many grains as possible, we prioritized swiftness of measurement over precision, configuring measurement time of about 3.5 minutes for each grain. Identification of heavy minerals was based on their chemical composition. We developed a Microsoft® Excel® spread sheet input criteria of mineral identification using a typical range of chemical compositions for each mineral. The grains of 110 wt.% total were rejected. The criteria of mineral identification were revised through the comparison between mineral identification by optical microscopy and chemical compositions of grains classified as "unknown minerals". Provenance rocks can be identified based on abundance ratio of identified minerals. If no significant difference of the abundance ratio was found among source rocks, chemical composition of specific minerals was used as another index. This method was applied to the sediments of some regions in Japan where provenance rocks had lithological variations but similar formation ages. Consequently, the provenance rocks were identified based on chemical compositions of heavy minerals resistant to

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...

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.

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....

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

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.

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...

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...

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)

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.

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)

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

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.

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.

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.

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.

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...

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

Multimodal Person Re-identification Using RGB-D Sensors and a Transient Identification Database

DEFF Research Database (Denmark)

Møgelmose, Andreas; Moeslund, Thomas B.; Nasrollahi, Kamal

2013-01-01

This paper describes a system for person re-identification using RGB-D sensors. The system covers the full flow, from detection of subjects, over contour extraction, to re-identification using soft biometrics. The biometrics in question are part-based color histograms and the subjects height...

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...

Blind identification of the number of sub-carriers for orthogonal frequency division multiplexing-based elastic optical networking

Science.gov (United States)

Zhao, Lei; Xu, Hengying; Bai, Chenglin

2018-03-01

In orthogonal frequency division multiplexing (OFDM)-based elastic optical networking (EON), it is imperative to identify unknown parameters of OFDM-based EON signals quickly, intelligently and robustly. Because the number of sub-carriers determines the size of the sub-carriers spacing and then affects the symbol period of the OFDM and the anti-dispersion capability of the system, the identification of the number of sub-carriers has a profound effect on the identification of other key parameters of the system. In this paper, we proposed a method of number identification for sub-carriers of OFDM-based EON signals with help of high-order cyclic cumulant. The specific fourth-order cyclic cumulant exists only at the location of its sub-carriers frequencies. So the identification of the number of sub-carriers can be implemented by detecting the cyclic-frequencies. The proposed scheme in our study can be divided into three sub-stages, i.e. estimating the spectral range, calculating the high-order cyclic cumulant and identifying the number of sub-carriers. When the optical signal-to-noise ratios (OSNR) varied from 16dB to 22dB, the number of sub-carriers (64-512) was successfully identified in the experiment, and from the statistical point of view, the average identification absolute accuracy (IAAs) exceeded 94%.

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.

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)

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.)

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

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

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

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.

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.

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.

A Support Vector Machine-Based Gender Identification Using Speech Signal

Science.gov (United States)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

An Oracle-based co-training framework for writer identification in offline handwriting

Science.gov (United States)

Porwal, Utkarsh; Rajan, Sreeranga; Govindaraju, Venu

2012-01-01

State-of-the-art techniques for writer identification have been centered primarily on enhancing the performance of the system for writer identification. Machine learning algorithms have been used extensively to improve the accuracy of such system assuming sufficient amount of data is available for training. Little attention has been paid to the prospect of harnessing the information tapped in a large amount of un-annotated data. This paper focuses on co-training based framework that can be used for iterative labeling of the unlabeled data set exploiting the independence between the multiple views (features) of the data. This paradigm relaxes the assumption of sufficiency of the data available and tries to generate labeled data from unlabeled data set along with improving the accuracy of the system. However, performance of co-training based framework is dependent on the effectiveness of the algorithm used for the selection of data points to be added in the labeled set. We propose an Oracle based approach for data selection that learns the patterns in the score distribution of classes for labeled data points and then predicts the labels (writers) of the unlabeled data point. This method for selection statistically learns the class distribution and predicts the most probable class unlike traditional selection algorithms which were based on heuristic approaches. We conducted experiments on publicly available IAM dataset and illustrate the efficacy of the proposed approach.

New pattern recognition system in the e-nose for Chinese spirit identification

International Nuclear Information System (INIS)

Zeng Hui; Li Qiang; Gu Yu

2016-01-01

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (S f ), crest factor value (C f ), impulse factor value (I f ), clearance factor value (CL f ), kurtosis factor value (K v ) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. (paper)

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.

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

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

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.

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.

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.

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.

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.

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

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...

Identification of time-varying nonlinear systems using differential evolution algorithm

DEFF Research Database (Denmark)

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

2013-01-01

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

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.

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.

Metodology of identification parameters of models control objects of automatic trailing system

Directory of Open Access Journals (Sweden)

I.V. Zimchuk

2017-04-01

Full Text Available The determining factor for the successful solution of the problem of synthesis of optimal control systems of different processes are adequacy of mathematical model of control object. In practice, the options can differ from the objects taken priori, causing a need to clarification of them. In this context, the article presents the results of the development and application of methods parameters identification of mathematical models of control object of automatic trailing system. The stated problem in the article is solved provided that control object is fully controlled and observed, and a differential equation of control object is known a priori. The coefficients of this equation to be determined. Identifying quality criterion is to minimize the integral value of squared error of identification. The method is based on a description of the dynamics of the object in space state. Equation of identification synthesized using the vector-matrix representation of model. This equation describes the interconnection of coefficients of matrix state and control with inputs and outputs of object. The initial data for calculation are the results of experimental investigation of the reaction of phase coordinates of control object at a typical input signal. The process of calculating the model parameters is reduced to solving the system of equations of the first order each. Application the above approach is illustrated in the example identification of coefficients transfer function of control object first order. Results of digital simulation are presented, they are confirming the justice of set out mathematical calculations. The approach enables to do the identification of models of one-dimensional and multidimensional objects and does not require a large amount of calculation for its implementation. The order of identified model is limited capabilities of measurement phase coordinates of corresponding control object. The practical significance of the work is

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

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.

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

Science.gov (United States)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

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

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.

Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

International Nuclear Information System (INIS)

Xia, Bing; Zhao, Xin; Callafon, Raymond de; Garnier, Hugues; Nguyen, Truong; Mi, Chris

2016-01-01

Highlights: • Continuous-time system identification is applied in Lithium-ion battery modeling. • Continuous-time and discrete-time identification methods are compared in detail. • The instrumental variable method is employed to further improve the estimation. • Simulations and experiments validate the advantages of continuous-time methods. - Abstract: The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. However, in real applications, there is a fundamental limitation of the discrete-time methods in dealing with sensitivity when the system is stiff and the storage resolutions are limited. To overcome this problem, this paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to disturbances. A case of a 2"n"d-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. In addition, the estimation by the conventional continuous-time least squares method is further improved in the case of noisy output measurement by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the advantages of the continuous-time system identification methods in battery applications.

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.

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.

Overcoming Inter-Subject Variability in BCI Using EEG-Based Identification

Directory of Open Access Journals (Sweden)

J. Stastny

2014-04-01

Full Text Available The high dependency of the Brain Computer Interface (BCI system performance on the BCI user is a well-known issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classification process and of the BCI protocol to maximize the BCI performance. In addition to this we present an algorithm for EEG-based identification designed to be resistant to variations in EEG recordings between sessions, which is also demonstrated by an experiment with an EEG database containing two sessions recorded one year apart. Further, our algorithm is designed to be compatible with our movement-related BCI device and the evaluation of the algorithm performance took place under conditions of a standard BCI experiment. Estimation of the mu rhythm fundamental frequency using the Frequency Zooming AR modeling is used for EEG feature extraction followed by a classifier based on the regularized Mahalanobis distance. An average subject identification score of 96 % is achieved.

System Identification for Experimental Study for Polymerization Catalyst Reaction in Fluidized Bed

Directory of Open Access Journals (Sweden)

Ahmmed Saadi Ibrehem

2011-11-01

Full Text Available In this work, system identification method is used to capture the reactor characteristics of production rate of polyethylene (PE based on published experimental data. The identification method is used to measure the percentage effect on the production rate of PE by measuring the effect of input factors of temperature of reaction, hydrogen concentration, and [Al]/[Ti] molar catalyst ratio. Temperature of reaction has big effects equal 52.4 % on the output of the system and 47.6 % on interaction of the system's parameters compare to other two factors. Also, hydrogen concentration has big effect equal 45.66 % on the output of the system and 14.7 % on interaction of the system's parameters. [Al]/[Ti] molar catalyst ratio has big effect on interaction of the system equal 28.6 and 1.94 % on the output of the system but less than the reaction temperature and hydrogen concentration. All these results depend on experiment results and these results are very important in industrial plants. ©2011 BCREC UNDIP. All rights reserved(Received: 13rd May 2011; Revised: 27th July 2011; Accepted: 22th September 2011[How to Cite: Ahmmed S. Ibrehem. (2011. System Identification for Experimental Study for Polymerization Catalyst Reaction in Fluidized Bed. Bulletin of Chemical Reaction Engineering & Catalysis, 6 (2: 137-146. doi:10.9767/bcrec.6.2.874.137-146][How to Link / DOI: http://dx,doi.org/10.9767/bcrec.6.2.874.137-146 || or local:  http://ejournal.undip.ac.id/index.php/bcrec/article/view/874 ] | View in 

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.

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

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

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.

SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

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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.

Subspace System Identification of the Kalman Filter

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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.

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.

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

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.

a five year review of api20e bacteria identification system's

African Journals Online (AJOL)

The API20E system (API; bioMérieux, France) is a plastic strip with microtubes containing dehydrated substrates, originally designed for the identification of Enterobacteriaceae so that identification of fermenters with the system would be straightforward. The API20E system was extended to include non- fermenters by the ...

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.

Control-based method to identify underlying delays of a nonlinear dynamical system.

Science.gov (United States)

Yu, Dongchuan; Frasca, Mattia; Liu, Fang

2008-10-01

We suggest several stationary state control-based delay identification methods which do not require any structural information about the controlled systems and are applicable to systems described by delayed ordinary differential equations. This proposed technique includes three steps: (i) driving a system to a steady state; (ii) perturbing the control signal for shifting the steady state; and (iii) identifying all delays by detecting the time that the system is abruptly drawn out of stationarity. Some aspects especially important for applications are discussed as well, including interaction delay identification, stationary state convergence speed, performance comparison, and the influence of noise on delay identification. Several examples are presented to illustrate the reliability and robustness of all delay identification methods suggested.

Load Identification for a Cantilever Beam Based on Fiber Bragg Grating Sensors

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Xuegang Song

2017-07-01

Full Text Available Load identification plays an important role in structural health monitoring, which aims at preventing structural failures. In order to identify load for linear systems and nonlinear systems, this paper presents methods to identify load for a cantilever beam based on dynamic strain measurement by Fiber Bragg Grating (FBG sensors. For linear systems, the proposed inverse method consists of Kalman filter with no load terms and a linear estimator. For nonlinear systems, the proposed inverse method consists of cubature Kalman filter (CKF with no load terms and a nonlinear estimator. In the process of load identification, the state equations of the beam structures are constructed by using the finite element method (FEM. Kalman filter or CKF is used to suppress noise. The residual innovation sequences, gain matrix, and innovation covariance generated by Kalman filter or CKF are used to identify a load. To prove the effectiveness of the proposed method, numerical simulations and experiments of the beam structures are employed and the results show that the method has an excellent performance.

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)

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

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Ángel Jesús Molina-Viedma

2018-02-01

Full Text Available The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC.

Science.gov (United States)

Molina-Viedma, Ángel Jesús; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A

2018-02-05

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

Science.gov (United States)

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Contribute to quantitative identification of casting defects based on computer analysis of X-ray images

Directory of Open Access Journals (Sweden)

Z. Ignaszak

2007-12-01

Full Text Available The forecast of structure and properties of casting is based on results of computer simulation of physical processes which are carried out during the casting processes. For the effective using of simulation system it is necessary to validate mathematica-physical models describing process of casting formation and the creation of local discontinues, witch determinate the casting properties.In the paper the proposition for quantitative validation of VP system using solidification casting defects by information sources of II group (methods of NDT was introduced. It was named the VP/RT validation (virtual prototyping/radiographic testing validation. Nowadays identification of casting defects noticeable on X-ray images bases on comparison of X-ray image of casting with relates to the ASTM. The results of this comparison are often not conclusive because based on operator’s subjective assessment. In the paper the system of quantitative identification of iron casting defects on X-ray images and classification this defects to ASTM class is presented. The methods of pattern recognition and machine learning were applied.

Time-Efficient Cloning Attacks Identification in Large-Scale RFID Systems

Directory of Open Access Journals (Sweden)

Ju-min Zhao

2017-01-01

Full Text Available Radio Frequency Identification (RFID is an emerging technology for electronic labeling of objects for the purpose of automatically identifying, categorizing, locating, and tracking the objects. But in their current form RFID systems are susceptible to cloning attacks that seriously threaten RFID applications but are hard to prevent. Existing protocols aimed at detecting whether there are cloning attacks in single-reader RFID systems. In this paper, we investigate the cloning attacks identification in the multireader scenario and first propose a time-efficient protocol, called the time-efficient Cloning Attacks Identification Protocol (CAIP to identify all cloned tags in multireaders RFID systems. We evaluate the performance of CAIP through extensive simulations. The results show that CAIP can identify all the cloned tags in large-scale RFID systems fairly fast with required accuracy.

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.

A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

Directory of Open Access Journals (Sweden)

Zhimin Wan

2018-01-01

Full Text Available In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s. Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

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...

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.

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.

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).

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...

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

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.

Metamodel-based inverse method for parameter identification: elastic-plastic damage model

Science.gov (United States)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

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...

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...

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

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

Fundamental limits for privacy-preserving biometric identification systems that support authentication

NARCIS (Netherlands)

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

2015-01-01

In this paper we analyze two types of biometric identification systems with protected templates that also support authentication. In the first system two terminals observe biometric enrollment and identification sequences of a number of individuals. It is the goal of these terminals to form a common

28 CFR 20.36 - Participation in the Interstate Identification Index System.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Participation in the Interstate Identification Index System. 20.36 Section 20.36 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL JUSTICE... in the Interstate Identification Index System. (a) In order to acquire and retain direct access to...

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...

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...

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...

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...

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...

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.

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.

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)

Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home

Directory of Open Access Journals (Sweden)

Mau-Tsuen Yang

2014-08-01

Full Text Available There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home’s entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare.

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.

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.

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....

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....

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.

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.

System Identification for Integrated Aircraft Development and Flight Testing (l’Identification des systemes pour le developpement integre des aeronefs et les essais en vol)

Science.gov (United States)

1999-03-01

aerodynamics to affect load motions. The effects include a load trail angle in proportion to the drag specific force, and modification of the load pendulum...equations algorithm for flight data filtering architeture . and data consistency checking; and SCIDNT 8, an output architecture. error identification...accelerations at the seven sensor locations, identified system is proportional to the number When system identification is performed, as of flexible modes

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...

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

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

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.

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.

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)

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.

A Framework for People Re-Identification in Multi-Camera Surveillance Systems

Science.gov (United States)

Ammar, Sirine; Zaghden, Nizar; Neji, Mahmoud

2017-01-01

People re-identification has been a very active research topic recently in computer vision. It is an important application in surveillance system with disjoint cameras. This paper is focused on the implementation of a human re-identification system. First the face of detected people is divided into three parts and some soft-biometric traits are…

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...

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.)

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

Science.gov (United States)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

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.

Using wavelet multi-resolution nature to accelerate the identification of fractional order system

International Nuclear Information System (INIS)

Li Yuan-Lu; Meng Xiao; Ding Ya-Qing

2017-01-01

Because of the fractional order derivatives, the identification of the fractional order system (FOS) is more complex than that of an integral order system (IOS). In order to avoid high time consumption in the system identification, the least-squares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method. (paper)

The Detection of Subsynchronous Oscillation in HVDC Based on the Stochastic Subspace Identification Method

Directory of Open Access Journals (Sweden)

Chen Shi

2014-01-01

Full Text Available Subsynchronous oscillation (SSO usually caused by series compensation, power system stabilizer (PSS, high voltage direct current transmission (HVDC and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti-noise.

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.

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)

Consolidity: Stack-based systems change pathway theory elaborated

Directory of Open Access Journals (Sweden)

Hassen Taher Dorrah

2014-06-01

Full Text Available This paper presents an elaborated analysis for investigating the stack-based layering processes during the systems change pathway. The system change pathway is defined as the path resulting from the combinations of all successive changes induced on the system when subjected to varying environments, activities, events, or any excessive internal or external influences and happenings “on and above” its normal stands, situations or set-points during its course of life. The analysis is essentially based on the important overall system paradigm of “Time driven-event driven-parameters change”. Based on this paradigm, it is considered that any affected activity, event or varying environment is intelligently self-recorded inside the system through an incremental consolidity-scaled change in system parameters of the stack-based layering types. Various joint stack-based mathematical and graphical approaches supported by representable case studies are suggested for the identification, extraction, and processing of various stack-based systems changes layering of different classifications and categorizations. Moreover, some selected real life illustrative applications are provided to demonstrate the (infinite stack-based identification and recognition of the change pathway process in the areas of geology, archeology, life sciences, ecology, environmental science, engineering, materials, medicine, biology, sociology, humanities, and other important fields. These case studies and selected applications revealed that there are general similarities of the stack-based layering structures and formations among all the various research fields. Such general similarities clearly demonstrate the global concept of the “fractals-general stacking behavior” of real life systems during their change pathways. Therefore, it is recommended that concentrated efforts should be expedited toward building generic modular stack-based systems or blocks for the mathematical

Structural damage diagnosis based on on-line recursive stochastic subspace identification

International Nuclear Information System (INIS)

Loh, Chin-Hsiung; Weng, Jian-Huang; Liu, Yi-Cheng; Lin, Pei-Yang; Huang, Shieh-Kung

2011-01-01

This paper presents a recursive stochastic subspace identification (RSSI) technique for on-line and almost real-time structural damage diagnosis using output-only measurements. Through RSSI the time-varying natural frequencies of a system can be identified. To reduce the computation time in conducting LQ decomposition in RSSI, the Givens rotation as well as the matrix operation appending a new data set are derived. The relationship between the size of the Hankel matrix and the data length in each shifting moving window is examined so as to extract the time-varying features of the system without loss of generality and to establish on-line and almost real-time system identification. The result from the RSSI technique can also be applied to structural damage diagnosis. Off-line data-driven stochastic subspace identification was used first to establish the system matrix from the measurements of an undamaged (reference) case. Then the RSSI technique incorporating a Kalman estimator is used to extract the dynamic characteristics of the system through continuous monitoring data. The predicted residual error is defined as a damage feature and through the outlier statistics provides an indicator of damage. Verification of the proposed identification algorithm by using the bridge scouring test data and white noise response data of a reinforced concrete frame structure is conducted

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

Science.gov (United States)

Zhong, Chongquan; Lin, Yaoyao

2017-11-01

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

The Development Of Mathematical Model For Automated Fingerprint Identification Systems Analysis

International Nuclear Information System (INIS)

Ardisasmita, M. Syamsa

2001-01-01

Fingerprint has a strong oriented and periodic structure composed of dark lines of raised skin (ridges) and clear lines of lowered skin (furrows)that twist to form a distinct pattern. Although the manner in which the ridges flow is distinctive, other characteristics of the fingerprint called m inutiae a re what are most unique to the individual. These features are particular patterns consisting of terminations or bifurcations of the ridges. To assert if two fingerprints are from the same finger or not, experts detect those minutiae. AFIS (Automated Fingerprint Identification Systems) extract and compare these features for determining a match. The classic methods of fingerprints recognition are not suitable for direct implementation in form of computer algorithms. The creation of a finger's model was however the necessity of development of new, better algorithms of analysis. This paper presents a new numerical methods of fingerprints' simulation based on mathematical model of arrangement of dermatoglyphics and creation of minutiae. This paper describes also the design and implementation of an automated fingerprint identification systems which operates in two stages: minutiae extraction and minutiae matching

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...

Pitch Correlogram Clustering for Fast Speaker Identification

Directory of Open Access Journals (Sweden)

Nitin Jhanwar

2004-12-01

Full Text Available Gaussian mixture models (GMMs are commonly used in text-independent speaker identification systems. However, for large speaker databases, their high computational run-time limits their use in online or real-time speaker identification situations. Two-stage identification systems, in which the database is partitioned into clusters based on some proximity criteria and only a single-cluster GMM is run in every test, have been suggested in literature to speed up the identification process. However, most clustering algorithms used have shown limited success, apparently because the clustering and GMM feature spaces used are derived from similar speech characteristics. This paper presents a new clustering approach based on the concept of a pitch correlogram that captures frame-to-frame pitch variations of a speaker rather than short-time spectral characteristics like cepstral coefficient, spectral slopes, and so forth. The effectiveness of this two-stage identification process is demonstrated on the IVIE corpus of 110 speakers. The overall system achieves a run-time advantage of 500% as well as a 10% reduction of error in overall speaker identification.

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

Development of an Effective System Identification and Control Capability for Quad-copter UAVs

Science.gov (United States)

Wei, Wei

. A PID controller and two fuzzy logic controllers were developed based on the validated dynamic models. The controller performances were evaluated and compared in both simulation environment and flight testing. Flight controllers were optimized to comply with US Aeronautical Design Standard Performance Specification Handling Quality Requirements for Military Rotorcraft (ADS-33E-PRF). Results showed a substantial improvement for developed controllers when compared to the nominal controllers based on hand tuning. The scope of this research involves experimental system hardware and software development, flight instrumentation, flight testing, dynamics modeling, system identification, dynamic model validation, control system modeling using PID and fuzzy logic, analysis of handling qualities, flight control optimization and validation. Both closed-loop and open-loop dynamics of the quad-copter system were analyzed. A cost-effective and high quality system identification procedure was applied and results proved in simulations as well as in flight tests.

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

Directory of Open Access Journals (Sweden)

Olympia Roeva

2004-10-01

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

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.

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.

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

Institute of Scientific and Technical Information of China (English)

无

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.

Using Closed-Set Speaker Identification Score Confidence to Enhance Audio-Based Collaborative Filtering for Multiple Users

DEFF Research Database (Denmark)

Shepstone, Sven Ewan; Tan, Zheng-Hua; Kristoffersen, Miklas Strøm

2018-01-01

In this paper, we utilize a closed-set speaker-identification approach to convey the ratings needed for collaborative filtering-based recommendation. Instead of explicitly providing a rating for a given program, users use a speech interface to dictate the desired rating after watching a movie. Due...... to the inaccuracies that may be imposed by a state-of-the-art speaker identification system, it is possible to mistake a user for another user in the household, especially when the users exhibit similar or identical age and gender demographics. This leads to the undesirable effect of injecting unwanted ratings...... into the collaborative rating matrix, and when the users have different tastes, can result in the recommendation of undesirable items. We therefore propose a simple confidence-based heuristic that utilizes the log-likelihood scores from the speaker identification front-end. The algorithm limits the degree to which...

33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

Science.gov (United States)

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Automatic Identification System Shipborne Equipment-Prince William Sound. 164.43 Section 164.43 Navigation and Navigable Waters COAST GUARD... Automatic Identification System Shipborne Equipment—Prince William Sound. (a) Until December 31, 2004, each...

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...

[Measures to prevent patient identification errors in blood collection/physiological function testing utilizing a laboratory information system].

Science.gov (United States)

Shimazu, Chisato; Hoshino, Satoshi; Furukawa, Taiji

2013-08-01

We constructed an integrated personal identification workflow chart using both bar code reading and an all in-one laboratory information system. The information system not only handles test data but also the information needed for patient guidance in the laboratory department. The reception terminals at the entrance, displays for patient guidance and patient identification tools at blood-sampling booths are all controlled by the information system. The number of patient identification errors was greatly reduced by the system. However, identification errors have not been abolished in the ultrasound department. After re-evaluation of the patient identification process in this department, we recognized that the major reason for the errors came from excessive identification workflow. Ordinarily, an ultrasound test requires patient identification 3 times, because 3 different systems are required during the entire test process, i.e. ultrasound modality system, laboratory information system and a system for producing reports. We are trying to connect the 3 different systems to develop a one-time identification workflow, but it is not a simple task and has not been completed yet. Utilization of the laboratory information system is effective, but is not yet perfect for patient identification. The most fundamental procedure for patient identification is to ask a person's name even today. Everyday checks in the ordinary workflow and everyone's participation in safety-management activity are important for the prevention of patient identification errors.

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 ...

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.

Location identification of closed crack based on Duffing oscillator transient transition

Science.gov (United States)

Liu, Xiaofeng; Bo, Lin; Liu, Yaolu; Zhao, Youxuan; Zhang, Jun; Deng, Mingxi; Hu, Ning

2018-02-01

The existence of a closed micro-crack in plates can be detected by using the nonlinear harmonic characteristics of the Lamb wave. However, its location identification is difficult. By considering the transient nonlinear Lamb under the noise interference, we proposed a location identification method for the closed crack based on the quantitative measurement of Duffing oscillator transient transfer in the phase space. The sliding short-time window was used to create a window truncation of to-be-detected signal. And then, the periodic extension processing for transient nonlinear Lamb wave was performed to ensure that the Duffing oscillator has adequate response time to reach a steady state. The transient autocorrelation method was used to reduce the occurrence of missed harmonic detection due to the random variable phase of nonlinear Lamb wave. Moreover, to overcome the deficiency in the quantitative analysis of Duffing system state by phase trajectory diagram and eliminate the misjudgment caused by harmonic frequency component contained in broadband noise, logic operation method of oscillator state transition function based on circular zone partition was adopted to establish the mapping relation between the oscillator transition state and the nonlinear harmonic time domain information. Final state transition discriminant function of Duffing oscillator was used as basis for identifying the reflected and transmitted harmonics from the crack. Chirplet time-frequency analysis was conducted to identify the mode of generated harmonics and determine the propagation speed. Through these steps, accurate position identification of the closed crack was achieved.

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

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

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

Directory of Open Access Journals (Sweden)

M. M. Blagoveshchenskaia

2014-01-01

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

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.

Adding Personality to Gifted Identification: Relationships among Traditional and Personality-Based Constructs

Science.gov (United States)

Carman, Carol A.

2011-01-01

One of the underutilized tools in gifted identification is personality-based measures. A multiple confirmatory factor analysis was utilized to examine the relationships between traditional identification methods and personality-based measures. The pattern of correlations indicated this model could be measuring two constructs, one related to…

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...

Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

Directory of Open Access Journals (Sweden)

Zhiqiang GENG

2014-01-01

Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

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...

Single cell adhesion force measurement for cell viability identification using an AFM cantilever-based micro putter

Science.gov (United States)

Shen, Yajing; Nakajima, Masahiro; Kojima, Seiji; Homma, Michio; Kojima, Masaru; Fukuda, Toshio

2011-11-01

Fast and sensitive cell viability identification is a key point for single cell analysis. To address this issue, this paper reports a novel single cell viability identification method based on the measurement of single cell shear adhesion force using an atomic force microscopy (AFM) cantilever-based micro putter. Viable and nonviable yeast cells are prepared and put onto three kinds of substrate surfaces, i.e. tungsten probe, gold and ITO substrate surfaces. A micro putter is fabricated from the AFM cantilever by focused ion beam etching technique. The spring constant of the micro putter is calibrated using the nanomanipulation approach. The shear adhesion force between the single viable or nonviable cell and each substrate is measured using the micro putter based on the nanorobotic manipulation system inside an environmental scanning electron microscope. The adhesion force is calculated based on the deflection of the micro putter beam. The results show that the adhesion force of the viable cell to the substrate is much larger than that of the nonviable cell. This identification method is label free, fast, sensitive and can give quantitative results at the single cell level.