WorldWideScience

Sample records for boundary recognition system

  1. Recognition of boundary feedback systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1989-01-01

    A system that has been the object of intense research is outlined. In view of that and recent progress of the theory of pseudodifferential boundary operator calculus, the author describes some features that could prove to be interesting in connection with the problems of boundary feedback...... stabilizability. It is shown that it is possible to use the calculus to consider more general feedback systems in a variational setup....

  2. Wood Species Recognition System

    OpenAIRE

    Bremananth R; Nithya B; Saipriya R

    2009-01-01

    The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing te...

  3. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

    This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const

  4. Video Shot Boundary Recognition Based on Adaptive Locality Preserving Projections

    Directory of Open Access Journals (Sweden)

    Yongliang Xiao

    2013-01-01

    Full Text Available A novel video shot boundary recognition method is proposed, which includes two stages of video feature extraction and shot boundary recognition. Firstly, we use adaptive locality preserving projections (ALPP to extract video feature. Unlike locality preserving projections, we define the discriminating similarity with mode prior probabilities and adaptive neighborhood selection strategy which make ALPP more suitable to preserve the local structure and label information of the original data. Secondly, we use an optimized multiple kernel support vector machine to classify video frames into boundary and nonboundary frames, in which the weights of different types of kernels are optimized with an ant colony optimization method. Experimental results show the effectiveness of our method.

  5. Efficient object recognition using boundary representation and wavelet neural network.

    Science.gov (United States)

    Pan, Hong; Xia, Liang-Zheng

    2008-12-01

    Wavelet neural networks combine the functions of time-frequency localization from the wavelet transform and of self-studying from the neural network, which make them particularly suitable for the classification of complex patterns. In this paper, an efficient object recognition method using boundary representation and the wavelet neural network is proposed. The method employs a wavelet neural network (WNN) to characterize the singularities of the object curvature representation and to perform the object classification at the same time and in an automatic way. The local time-frequency attributes of the singularities on the object boundary are detected by making a preliminary wavelet analysis of the curvature representation. Then, the discriminative scale-translation features of the singularities are stored as the initial scale-translation parameters of the wavelet nodes in the WNN. These parameters are trained to their optimum status during the learning stage. With our approach, as opposed to matching features by convolving the signal with wavelet functions at a large number of scales, the computational burden is significantly reduced. Only a few convolutions are performed at the optimum scale-translation grids during the classification, which makes it suitable for real-time recognition tasks. Compared with the artificial-neural-network-based approaches preceded by wavelet filter banks with fixed scale-translation parameters, the support vector machine (SVM) using traditional Fourier descriptors and K-nearest-neighbor ( K-NN) classifier based on the state-of-the-art shape descriptors, our scheme demonstrates superior and stable discrimination performance under various noisy and affine conditions.

  6. Ear recognition: a complete system

    Science.gov (United States)

    Abaza, Ayman; Harrison, Mary Ann F.

    2013-05-01

    Ear Recognition has recently received significant attention in the literature. Even though current ear recognition systems have reached a certain level of maturity, their success is still limited. This paper presents an efficient complete ear-based biometric system that can process five frames/sec; Hence it can be used for surveillance applications. The ear detection is achieved using Haar features arranged in a cascaded Adaboost classifier. The feature extraction is based on dividing the ear image into several blocks from which Local Binary Pattern feature distributions are extracted. These feature distributions are then fused at the feature level to represent the original ear texture in the classification stage. The contribution of this paper is three fold: (i) Applying a new technique for ear feature extraction, and studying various optimization parameters for that technique; (ii) Presenting a practical ear recognition system and a detailed analysis about error propagation in that system; (iii) Studying the occlusion effect of several ear parts. Detailed experiments show that the proposed ear recognition system achieved better performance (94:34%) compared to other shape-based systems as Scale-invariant feature transform (67:92%). The proposed approach can also handle efficiently hair occlusion. Experimental results show that the proposed system can achieve about (78%) rank-1 identification, even in presence of 60% occlusion.

  7. Automated road marking recognition system

    Science.gov (United States)

    Ziyatdinov, R. R.; Shigabiev, R. R.; Talipov, D. N.

    2017-09-01

    Development of the automated road marking recognition systems in existing and future vehicles control systems is an urgent task. One way to implement such systems is the use of neural networks. To test the possibility of using neural network software has been developed with the use of a single-layer perceptron. The resulting system based on neural network has successfully coped with the task both when driving in the daytime and at night.

  8. The Army word recognition system

    Science.gov (United States)

    Hadden, David R.; Haratz, David

    1977-01-01

    The application of speech recognition technology in the Army command and control area is presented. The problems associated with this program are described as well as as its relevance in terms of the man/machine interactions, voice inflexions, and the amount of training needed to interact with and utilize the automated system.

  9. Combat Systems Department Employee Recognition System

    National Research Council Canada - National Science Library

    1996-01-01

    This handbook contains two types of information: guidelines and instructions. The guidelines provide a foundation of purpose, assumptions, principles, expectations and attributes the Employee Recognition System is designed to reflect...

  10. Boundary controllability of integrodifferential systems in Banach ...

    Indian Academy of Sciences (India)

    [6] discussed the general theory of boundary control systems. Barbu and Precupanu [4] studied a class of convex control problems governed by linear evolution systems covering the principal boundary control systems of parabolic type. In [5] Barbu investigated a class of boundary-distributed linear control systems in ...

  11. Cell boundary fault detection system

    Science.gov (United States)

    Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

    2009-05-05

    A method determines a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

  12. Integrability and boundary conditions of supersymmetric systems

    International Nuclear Information System (INIS)

    Yue Ruihong; Liang Hong

    1996-01-01

    By studying the solutions of the reflection equations, we find out a series of integrable supersymmetric systems with different boundary conditions. The Hamiltonian contains four free parameters which describe the contribution of the boundary terms

  13. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

    Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis

    2016-01-01

    recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...... that can be connected to any computer on the market. The paper proposes an equation that relates the distance and voltage for a Sharp GP2Y0A21 and GP2D120 sensors in the situation that a hand is used as the reflective object. In the end, the presented system is compared with other audio/video system...

  14. Facial recognition in education system

    Science.gov (United States)

    Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

    2017-11-01

    Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

  15. Kannada character recognition system using neural network

    Science.gov (United States)

    Kumar, Suresh D. S.; Kamalapuram, Srinivasa K.; Kumar, Ajay B. R.

    2013-03-01

    Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.

  16. Working with boundaries in systems psychodynamic consulting

    Directory of Open Access Journals (Sweden)

    Henk Struwig

    2012-03-01

    Research purpose: The purpose of the research was to produce a set of theoretical assumptions about organisational boundaries and boundary management in organisations and, from these, to develop a set of hypotheses as a thinking framework for practising consulting psychologists when they work with boundaries from a systems psychodynamic stance. Motivation for the study: The researcher used the belief that organisational boundaries reflect the essence of organisations. Consulting to boundary managers could facilitate a deep understanding of organisational dynamics. Research design, approach and method: The researcher followed a case study design. He used systems psychodynamic discourse analysis. It led to six working hypotheses. Main findings: The primary task of boundary management is to hold the polarities of integration and differentiation and not allow the system to become fragmented or overly integrated. Boundary management is a primary task and an ongoing activity of entire organisations. Practical/managerial implications: Organisations should work actively at effective boundary management and at balancing integration and differentiation. Leaders should become aware of how effective boundary management leads to good holding environments that, in turn, lead to containing difficult emotions in organisations. Contribution/value-add: The researcher provided a boundary-consulting framework in order to assist consultants to balance the conceptual with the practical when they consult.

  17. A NEURAL NETWORK BASED IRIS RECOGNITION SYSTEM FOR PERSONAL IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    Usham Dias

    2010-10-01

    Full Text Available This paper presents biometric personal identification based on iris recognition using artificial neural networks. Personal identification system consists of localization of the iris region, normalization, enhancement and then iris pattern recognition using neural network. In this paper, through results obtained, we have shown that a person’s left and right eye are unique. In this paper, we also show that the network is sensitive to the initial weights and that over-training gives bad results. We also propose a fast algorithm for the localization of the inner and outer boundaries of the iris region. Results of simulations illustrate the effectiveness of the neural system in personal identification. Finally a hardware iris recognition model is proposed and implementation aspects are discussed.

  18. Mixed basin boundary structures of chaotic systems

    International Nuclear Information System (INIS)

    Rosa, E. Jr.; Ott, E.

    1999-01-01

    Motivated by recent numerical observations on a four-dimensional continuous-time dynamical system, we consider different types of basin boundary structures for chaotic systems. These general structures are essentially mixtures of the previously known types of basin boundaries where the character of the boundary assumes features of the previously known boundary types at different points arbitrarily finely interspersed in the boundary. For example, we discuss situations where an everywhere continuous boundary that is otherwise smooth and differentiable at almost every point has an embedded uncountable, zero Lebesgue measure set of points at which the boundary curve is nondifferentiable. Although the nondifferentiable set is only of zero Lebesgue measure, the curve close-quote s fractal dimension may (depending on parameters) still be greater than one. In addition, we discuss bifurcations from such a mixed boundary to a 'pure' boundary that is a fractal nowhere differentiable curve or surface and to a pure nonfractal boundary that is everywhere smooth. copyright 1999 The American Physical Society

  19. On Mario Bunge's Definition of System and System Boundary

    Science.gov (United States)

    Cavallo, Andrew M.

    2012-01-01

    In this short paper we discuss Mario Bunge's definition of system boundary. It is quickly discovered that Bunge's definition of system and system boundary are both deficient. We thus propose new definitions, which (hopefully) improve the situation. Our definition of system boundary works off the same intuition behind Bunge's.

  20. Automatic TLI recognition system, general description

    Energy Technology Data Exchange (ETDEWEB)

    Lassahn, G.D.

    1997-02-01

    This report is a general description of an automatic target recognition system developed at the Idaho National Engineering Laboratory for the Department of Energy. A user`s manual is a separate volume, Automatic TLI Recognition System, User`s Guide, and a programmer`s manual is Automatic TLI Recognition System, Programmer`s Guide. This system was designed as an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system naturally incorporates image data fusion, and it gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. In addition to its primary function as a trainable target recognition system, this is also a versatile, general-purpose tool for image manipulation and analysis, which can be either keyboard-driven or script-driven. This report includes descriptions of three variants of the computer hardware, a description of the mathematical basis if the training process, and a description with examples of the system capabilities.

  1. Improved pattern recognition systems by hybrid methods

    International Nuclear Information System (INIS)

    Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

    1978-12-01

    This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

  2. Boundary Controllability of Nonlinear Fractional Integrodifferential Systems

    Directory of Open Access Journals (Sweden)

    Ahmed HamdyM

    2010-01-01

    Full Text Available Sufficient conditions for boundary controllability of nonlinear fractional integrodifferential systems in Banach space are established. The results are obtained by using fixed point theorems. We also give an application for integropartial differential equations of fractional order.

  3. Boundary Controllability of Integrodifferential Systems in Banach ...

    Indian Academy of Sciences (India)

    Abstract. Sufficient conditions for boundary controllability of integrodifferential systems in Banach spaces are established. The results are obtained by using the strongly continuous semigroup theory and the Banach contraction principle. Examples are provided to illustrate the theory.

  4. Automatic Door Access System Using Face Recognition

    Directory of Open Access Journals (Sweden)

    Hteik Htar Lwin

    2015-06-01

    Full Text Available Abstract Most doors are controlled by persons with the use of keys security cards password or pattern to open the door. Theaim of this paper is to help users forimprovement of the door security of sensitive locations by using face detection and recognition. Face is a complex multidimensional structure and needs good computing techniques for detection and recognition. This paper is comprised mainly of three subsystems namely face detection face recognition and automatic door access control. Face detection is the process of detecting the region of face in an image. The face is detected by using the viola jones method and face recognition is implemented by using the Principal Component Analysis PCA. Face Recognition based on PCA is generally referred to as the use of Eigenfaces.If a face is recognized it is known else it is unknown. The door will open automatically for the known person due to the command of the microcontroller. On the other hand alarm will ring for the unknown person. Since PCA reduces the dimensions of face images without losing important features facial images for many persons can be stored in the database. Although many training images are used computational efficiency cannot be decreased significantly. Therefore face recognition using PCA can be more useful for door security system than other face recognition schemes.

  5. Connected digit speech recognition system for Malayalam

    Indian Academy of Sciences (India)

    A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual ...

  6. Automated pattern recognition system for noise analysis

    International Nuclear Information System (INIS)

    Sides, W.H. Jr.; Piety, K.R.

    1980-01-01

    A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

  7. Biometric Features in Person Recognition Systems

    Directory of Open Access Journals (Sweden)

    Edgaras Ivanovas

    2011-03-01

    Full Text Available Lately a lot of research effort is devoted for recognition of a human being using his biometric characteristics. Biometric recognition systems are used in various applications, e. g., identification for state border crossing or firearm, which allows only enrolled persons to use it. In this paper biometric characteristics and their properties are reviewed. Development of high accuracy system requires distinctive and permanent characteristics, whereas development of user friendly system requires collectable and acceptable characteristics. It is showed that properties of biometric characteristics do not influence research effort significantly. Properties of biometric characteristic features and their influence are discussed.Article in Lithuanian

  8. Statistical feature extraction based iris recognition system

    Indian Academy of Sciences (India)

    Performance of the proposed iris recognition system (IRS) has been measured by recording false acceptance rate (FAR) and false rejection rate (FRR) at differentthresholds in the distance metric. System performance has been evaluated by computing statistical features along two directions, namely, radial direction of ...

  9. Automatic stereoscopic system for person recognition

    Science.gov (United States)

    Murynin, Alexander B.; Matveev, Ivan A.; Kuznetsov, Victor D.

    1999-06-01

    A biometric access control system based on identification of human face is presented. The system developed performs remote measurements of the necessary face features. Two different scenarios of the system behavior are implemented. The first one assumes the verification of personal data entered by visitor from console using keyboard or card reader. The system functions as an automatic checkpoint, that strictly controls access of different visitors. The other scenario makes it possible to identify visitors without any person identifier or pass. Only person biometrics are used to identify the visitor. The recognition system automatically finds necessary identification information preliminary stored in the database. Two laboratory models of recognition system were developed. The models are designed to use different information types and sources. In addition to stereoscopic images inputted to computer from cameras the models can use voice data and some person physical characteristics such as person's height, measured by imaging system.

  10. Fractal boundaries in chaotic hamiltonian systems

    Science.gov (United States)

    Viana, R. L.; Mathias, A. C.; Marcus, F. A.; Kroetz, T.; Caldas, I. L.

    2017-10-01

    Fractal structures are typically present in the dynamics of chaotic orbits in non-integrable open Hamiltonian systems and result from the extremely complicated nature of the invariant manifolds of unstable periodic orbits. Exit basins, the set of initial conditions leading to orbits escaping through a given exit, have very frequently fractal boundaries. In this work we analyze exit basin boundaries in a dynamical system of physical interest, namely the motion of charged particles in a magnetized plasma subjected to electrostatic drift waves, and characterize in a quantitative way the fractality of these structures and their observable consequences, as the final-state uncertainty.

  11. Statistical feature extraction based iris recognition system

    Indian Academy of Sciences (India)

    Atul Bansal

    features obtained from one's face [1], finger [2], voice [3] and/or iris [4, 5]. Iris recognition system is widely used in high security areas. A number of researchers have proposed various algorithms for feature extraction. A little work [6,. 7] however, has been reported using statistical techniques directly on pixel values in order to ...

  12. Statistical feature extraction based iris recognition system

    Indian Academy of Sciences (India)

    Atul Bansal

    Abstract. Iris recognition systems have been proposed by numerous researchers using different feature extraction techniques for accurate and reliable biometric authentication. In this paper, a statistical feature extraction technique based on correlation between adjacent pixels has been proposed and implemented. Ham-.

  13. Boundary feedback stabilization of distributed parameter systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1988-01-01

    The author introduces the method of pseudo-differential stabilization. He notes that the theory of pseudo-differential boundary operators is a fruitful approach to problems arising in control and stabilization theory of distributed-parameter systems. The basic pseudo-differential calculus can...

  14. Industrial robots with sensors and object recognition systems

    International Nuclear Information System (INIS)

    Koehler, G.W.

    1978-01-01

    The previous development and the present status of industrial robots equipped with sensors and object recognition systems are described. This type of equipment allows flexible automation of many work stations in which industrial robots of the first generation, which are unable to react to changes in their respective environments automatically, apart from their being linked to other machines, could not be used because of the prevailing boundary conditions. A classification system facilitates an overview of the large number of technical solutions now available. The manifold possibilities of application of this equipment are demonstrated by a number of examples. As a result of the present state of development of the components required, and in view also of economic reasons, there is a trend towards special designs for a small number of specific purposes and towards stripped-down object recognition. systems with limited applications. A fitting description is offered of the term 'robot', which is now being used in various contexts, and an indication is made of the capabilities and components a machine to be called robot should have as a minimum. Finally, reference is made to some potential lines of development serving to reduce expediture and accelerate recognition processes. (orig.) [de

  15. Dance recognition system using lower body movement.

    Science.gov (United States)

    Simpson, Travis T; Wiesner, Susan L; Bennett, Bradford C

    2014-02-01

    The current means of locating specific movements in film necessitate hours of viewing, making the task of conducting research into movement characteristics and patterns tedious and difficult. This is particularly problematic for the research and analysis of complex movement systems such as sports and dance. While some systems have been developed to manually annotate film, to date no automated way of identifying complex, full body movement exists. With pattern recognition technology and knowledge of joint locations, automatically describing filmed movement using computer software is possible. This study used various forms of lower body kinematic analysis to identify codified dance movements. We created an algorithm that compares an unknown move with a specified start and stop against known dance moves. Our recognition method consists of classification and template correlation using a database of model moves. This system was optimized to include nearly 90 dance and Tai Chi Chuan movements, producing accurate name identification in over 97% of trials. In addition, the program had the capability to provide a kinematic description of either matched or unmatched moves obtained from classification recognition.

  16. Effect of frequency boundary assignment on vowel recognition with the Nucleus 24 ACE speech coding strategy.

    Science.gov (United States)

    Fourakis, Marios S; Hawks, John W; Holden, Laura K; Skinner, Margaret W; Holden, Timothy A

    2004-04-01

    Two speech processor programs (MAPs) differing only in electrode frequency boundary assignments were created for each of eight Nucleus 24 Cochlear Implant recipients. The default MAPs used typical frequency boundaries, and the experimental MAPs reassigned one additional electrode to vowel formant regions. Four objective speech tests and a questionnaire were used to evaluate speech recognition with the two MAPs. Results for the closed-set vowel test and the formant discrimination test showed small but significant improvement in scores with the experimental MAP. Differences for the Consonant-Vowel Nucleus-Consonant word test and closed-set consonant test were nonsignificant. Feature analysis revealed no significant differences in information transmission. Seven of the eight subjects preferred the experimental MAP, reporting louder, crisper, and clearer sound. The results suggest that Nucleus 24 recipients should be given an opportunity to compare a MAP that assigns more electrodes in vowel formant regions with the default MAP to determine which provides the most benefit in everyday life.

  17. Privacy protection schemes for fingerprint recognition systems

    Science.gov (United States)

    Marasco, Emanuela; Cukic, Bojan

    2015-05-01

    The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechanisms control access to personal information and limit the likelihood of intrusions. In this paper, image- and feature-level schemes for privacy protection in fingerprint recognition systems are reviewed. Storing only key features of a biometric signature can reduce the likelihood of biometric data being used for unintended purposes. In biometric cryptosystems and biometric-based key release, the biometric component verifies the identity of the user, while the cryptographic key protects the communication channel. Transformation-based approaches only a transformed version of the original biometric signature is stored. Different applications can use different transforms. Matching is performed in the transformed domain which enable the preservation of low error rates. Since such templates do not reveal information about individuals, they are referred to as cancelable templates. A compromised template can be re-issued using a different transform. At image-level, de-identification schemes can remove identifiers disclosed for objectives unrelated to the original purpose, while permitting other authorized uses of personal information. Fingerprint images can be de-identified by, for example, mixing fingerprints or removing gender signature. In both cases, degradation of matching performance is minimized.

  18. Euro Banknote Recognition System for Blind People.

    Science.gov (United States)

    Dunai Dunai, Larisa; Chillarón Pérez, Mónica; Peris-Fajarnés, Guillermo; Lengua Lengua, Ismael

    2017-01-20

    This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  19. Euro Banknote Recognition System for Blind People

    Directory of Open Access Journals (Sweden)

    Larisa Dunai Dunai

    2017-01-01

    Full Text Available This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  20. Boundary layer control of rotating convection systems.

    Science.gov (United States)

    King, Eric M; Stellmach, Stephan; Noir, Jerome; Hansen, Ulrich; Aurnou, Jonathan M

    2009-01-15

    Turbulent rotating convection controls many observed features of stars and planets, such as magnetic fields, atmospheric jets and emitted heat flux patterns. It has long been argued that the influence of rotation on turbulent convection dynamics is governed by the ratio of the relevant global-scale forces: the Coriolis force and the buoyancy force. Here, however, we present results from laboratory and numerical experiments which exhibit transitions between rotationally dominated and non-rotating behaviour that are not determined by this global force balance. Instead, the transition is controlled by the relative thicknesses of the thermal (non-rotating) and Ekman (rotating) boundary layers. We formulate a predictive description of the transition between the two regimes on the basis of the competition between these two boundary layers. This transition scaling theory unifies the disparate results of an extensive array of previous experiments, and is broadly applicable to natural convection systems.

  1. Automatic TLI recognition system. Part 1: System description

    Energy Technology Data Exchange (ETDEWEB)

    Partin, J.K.; Lassahn, G.D.; Davidson, J.R.

    1994-05-01

    This report describes an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system uses image data fusion and gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. This volume gives a general description of the ATR system.

  2. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ari Paasio

    2006-12-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  3. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Lahdenoja Olli

    2007-01-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  4. Cross domains Arabic named entity recognition system

    KAUST Repository

    Al-Ahmari, S. Saad

    2016-07-11

    Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  5. Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques

    OpenAIRE

    Miliaresis, George

    2014-01-01

    Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques. PhD Thesis, Remote Sensing & Terrain Pattern Recognition),National Technical University of Athens, Dpt. of Topography (2000).

  6. Emotion recognition and emergent leadership : Unraveling mediating mechanisms and boundary conditions

    NARCIS (Netherlands)

    Walter, F.; Cole, M.S.; van der Vegt, G.S.; Rubin, R.S.; Bommer, W.H.

    2012-01-01

    This study examines the complex connection between individuals' emotion recognition capability and their emergence as leaders. It is hypothesized that emotion recognition and extraversion interactively relate with an individual's task coordination behavior which, in turn, influences the likelihood

  7. Surface free energy for systems with integrable boundary conditions

    International Nuclear Information System (INIS)

    Goehmann, Frank; Bortz, Michael; Frahm, Holger

    2005-01-01

    The surface free energy is the difference between the free energies for a system with open boundary conditions and the same system with periodic boundary conditions. We use the quantum transfer matrix formalism to express the surface free energy in the thermodynamic limit of systems with integrable boundary conditions as a matrix element of certain projection operators. Specializing to the XXZ spin-1/2 chain we introduce a novel 'finite temperature boundary operator' which characterizes the thermodynamical properties of surfaces related to integrable boundary conditions

  8. Developing a Credit Recognition System for Chinese Higher Education Institutions

    Science.gov (United States)

    Li, Fuhui

    2015-01-01

    In recent years, a credit recognition system has been developing in Chinese higher education institutions. Much research has been done on this development, but it has been concentrated on system building, barriers/issues and international practices. The relationship between credit recognition system reforms and democratisation of higher education…

  9. Neural network based facial recognition system

    Science.gov (United States)

    Luebbers, Paul G.; Uwechue, Okechukwu A.; Pandya, Abhijit S.

    1994-03-01

    Researchers have for many years tried to develop machine recognition systems using video images of the human face as the input, with limited success. This paper presents a technique for recognizing individuals based on facial features using a novel multi-layer neural network architecture called `PWRNET'. We envision a real-time version of this technique to be used for high security applications. Two systems are proposed. One involves taking a grayscale video image and using it directly, the other involves decomposing the grayscale image into a series of binary images using the isodensity regions of the image. Isodensity regions are the areas within an image where the intensity is within a certain range. The binary image is produced by setting the pixels inside this intensity range to one, and the rest of the pixels in the image to zero. Features based on moments are subsequently extracted from these grayscale images. These features are then used for classification of the image. The classification is accomplished using an artificial neural network called `PWRNET', which produces a polynomial expression of the trained network. There is one neural network for each individual to be identified, with an output value which is either positive or negative identification. A detailed development of the design is presented, and identification for small population of individuals is presented. It is shown that the system is effective for variations in both scale and translation, which are considered to be reasonable variations for this type of facial identification.

  10. Random-Profiles-Based 3D Face Recognition System

    Directory of Open Access Journals (Sweden)

    Joongrock Kim

    2014-03-01

    Full Text Available In this paper, a noble nonintrusive three-dimensional (3D face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation.

  11. Hybrid gesture recognition system for short-range use

    Science.gov (United States)

    Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun

    2012-03-01

    In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.

  12. Modelling Intention Recognition for Intelligent Agent Systems

    National Research Council Canada - National Science Library

    Heinze, Clint

    2004-01-01

    .... From ecological psychology comes Gibson's theory of visual perception that highlights the importance of the environment in explaining the nature of vision and recognition and claims that higher order...

  13. Embedded palmprint recognition system using OMAP 3530.

    Science.gov (United States)

    Shen, Linlin; Wu, Shipei; Zheng, Songhao; Ji, Zhen

    2012-01-01

    We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.

  14. Embedded Palmprint Recognition System Using OMAP 3530

    Directory of Open Access Journals (Sweden)

    Songhao Zheng

    2012-02-01

    Full Text Available We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.

  15. Iris analysis for biometric recognition systems

    CERN Document Server

    Bodade, Rajesh M

    2014-01-01

    The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

  16. A system boundary identification method for life cycle assessment

    DEFF Research Database (Denmark)

    Li, Tao; Zhang, Hongchao; Liu, Zhichao

    2014-01-01

    Life cycle assessment (LCA) is a useful tool for quantifying the overall environmental impacts of a product, process, or service. The scientific scope and boundary definition are important to ensure the accuracy of LCA results. Defining the boundary in LCA is difficult and there are no commonly...... accepted scientific methods yet. The objective of this research is to present a comprehensive discussion of system boundaries in LCA and to develop an appropriate boundary delimitation method.A product system is partitioned into the primary system and interrelated subsystems. The hierarchical relationship......, 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...

  17. Boundary control of nonlinear coupled heat systems using backstepping

    KAUST Repository

    Bendevis, Paul

    2016-10-20

    A state feedback boundary controller is designed for a 2D coupled PDE system modelling heat transfer in a membrane distillation system for water desalination. Fluid is separated into two compartments with nonlinear coupling at a membrane boundary. The controller sets the temperature on one boundary in order to track a temperature difference across the membrane boundary. The control objective is achieved by an extension of backstepping methods to these coupled equations. Stability of the target system via Lyapunov like methods, and the invertibility of the integral transformation are used to show the stability of the tracking error.

  18. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

    Science.gov (United States)

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  19. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Pavol Partila

    2015-01-01

    Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  20. Increased Efficiency of Face Recognition System using Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Rajani Muraleedharan

    2006-02-01

    Full Text Available This research was inspired by the need of a flexible and cost effective biometric security system. The flexibility of the wireless sensor network makes it a natural choice for data transmission. Swarm intelligence (SI is used to optimize routing in distributed time varying network. In this paper, SI maintains the required bit error rate (BER for varied channel conditions while consuming minimal energy. A specific biometric, the face recognition system, is discussed as an example. Simulation shows that the wireless sensor network is efficient in energy consumption while keeping the transmission accuracy, and the wireless face recognition system is competitive to the traditional wired face recognition system in classification accuracy.

  1. An Evaluation of PC-Based Optical Character Recognition Systems.

    Science.gov (United States)

    Schreier, E. M.; Uslan, M. M.

    1991-01-01

    The review examines six personal computer-based optical character recognition (OCR) systems designed for use by blind and visually impaired people. Considered are OCR components and terms, documentation, scanning and reading, command structure, conversion, unique features, accuracy of recognition, scanning time, speed, and cost. (DB)

  2. UNCONSTRAINED HANDWRITING RECOGNITION : LANGUAGE MODELS, PERPLEXITY, AND SYSTEM PERFORMANCE

    NARCIS (Netherlands)

    Marti, U-V.; Bunke, H.

    2004-01-01

    In this paper we present a number of language models and their behavior in the recognition of unconstrained handwritten English sentences. We use the perplexity to compare the different models and their prediction power, and relate it to the performance of a recognition system under different

  3. A quality integrated spectral minutiae fingerprint recognition system

    NARCIS (Netherlands)

    Xu, H.; Veldhuis, Raymond N.J.; Kevenaar, Tom A.M.; Akkermans, Anton H.M.

    Many fingerprint recognition systems are based on minutiae matching. However, the recognition accuracy of minutiae-based matching algorithms is highly dependent on the fingerprint minutiae quality. Therefore, in this paper, we introduce a quality integrated spectral minutiae algorithm, in which the

  4. A speech recognition system for data collection in precision agriculture

    Science.gov (United States)

    Dux, David Lee

    Agricultural producers have shown interest in collecting detailed, accurate, and meaningful field data through field scouting, but scouting is labor intensive. They use yield monitor attachments to collect weed and other field data while driving equipment. However, distractions from using a keyboard or buttons while driving can lead to driving errors or missed data points. At Purdue University, researchers have developed an ASR system to allow equipment operators to collect georeferenced data while keeping hands and eyes on the machine during harvesting and to ease georeferencing of data collected during scouting. A notebook computer retrieved locations from a GPS unit and displayed and stored data in Excel. A headset microphone with a single earphone collected spoken input while allowing the operator to hear outside sounds. One-, two-, or three-word commands activated appropriate VBA macros. Four speech recognition products were chosen based on hardware requirements and ability to add new terms. After training, speech recognition accuracy was 100% for Kurzweil VoicePlus and Verbex Listen for the 132 vocabulary words tested, during tests walking outdoors or driving an ATV. Scouting tests were performed by carrying the system in a backpack while walking in soybean fields. The system recorded a point or a series of points with each utterance. Boundaries of points showed problem areas in the field and single points marked rocks and field corners. Data were displayed as an Excel chart to show a real-time map as data were collected. The information was later displayed in a GIS over remote sensed field images. Field corners and areas of poor stand matched, with voice data explaining anomalies in the image. The system was tested during soybean harvest by using voice to locate weed patches. A harvester operator with little computer experience marked points by voice when the harvester entered and exited weed patches or areas with poor crop stand. The operator found the

  5. Recognition

    DEFF Research Database (Denmark)

    Gimmler, Antje

    2017-01-01

    In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory must...... be evaluated. In the first section, I will introduce the concept of recognition as a travelling concept playing a role both on the intellectual stage and in real life. In the second section, I will concentrate on the presentation of Honneth’s theory of recognition, emphasizing the construction of the concept...... and its explanatory power. Finally, I will discuss Honneth’s concept in relation to the critique that has been raised, addressing the debate between Honneth and Fraser. In a short conclusion, I will return to the question of the explanatory power of the concept of recognition....

  6. Singular boundary perturbations of distributed systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1990-01-01

    Some problems arising in real-life control applications are addressed--namely, problems concerning non-smooth control inputs on the boundary of the spatial domain. The classical variational approach is extended, and sufficient conditions are given for the solutions to continuous functions of time...

  7. Regularity of pointwise boundary control systems

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1992-01-01

    We will in these notes address some problems arising in "real-life" control application, namely problems concerning distributional control inputs on the boundary of the spatial domain. We extend the classical variational approach and give easily checkable sufficient conditions for the solutions...

  8. Slip systems, lattice rotations and dislocation boundaries

    DEFF Research Database (Denmark)

    Winther, Grethe

    2008-01-01

    of dislocation structure formed, in particular the crystallographic alignment of dislocation boundaries, and the slip pattern are demonstrated. These relations are applied to polycrystals deformed in tension and rolling, producing good agreement with experiment for rolling but less good agreement for tension...

  9. Design and development of an ancient Chinese document recognition system

    Science.gov (United States)

    Peng, Liangrui; Xiu, Pingping; Ding, Xiaoqing

    2003-12-01

    The digitization of ancient Chinese documents presents new challenges to OCR (Optical Character Recognition) research field due to the large character set of ancient Chinese characters, variant font types, and versatile document layout styles, as these documents are historical reflections to the thousands of years of Chinese civilization. After analyzing the general characteristics of ancient Chinese documents, we present a solution for recognition of ancient Chinese documents with regular font-types and layout-styles. Based on the previous work on multilingual OCR in TH-OCR system, we focus on the design and development of two key technologies which include character recognition and page segmentation. Experimental results show that the developed character recognition kernel of 19,635 Chinese characters outperforms our original traditional Chinese recognition kernel; Benchmarked test on printed ancient Chinese books proves that the proposed system is effective for regular ancient Chinese documents.

  10. Visual Recognition System for Cleaning Tasks by Humanoid Robots

    Directory of Open Access Journals (Sweden)

    Muhammad Attamimi

    2013-11-01

    Full Text Available In this study, we present a visual recognition system that enables a robot to clean a tabletop. The proposed system comprises object recognition, material recognition and ungraspable object detection using information acquired from a visual sensor. Multiple cues such as colour, texture and three-dimensional point-clouds are incorporated adaptively for achieving object recognition. Moreover, near-infrared (NIR reflection intensities captured by the visual sensor are used for realizing material recognition. The Gaussian mixture model (GMM is employed for modelling the tabletop surface that is used for detecting ungraspable objects. The proposed system was implemented in a humanoid robot, and tasks such as object and material recognition were performed in various environments. In addition, we evaluated ungraspable object detection using various objects such as dust, grains and paper waste. Finally, we executed the cleaning task to evaluate the proposed system's performance. The results revealed that the proposed system affords high recognition rates and enables humanoid robots to perform domestic service tasks such as cleaning.

  11. A Multi-Modal Person Recognition System for Social Robots

    Directory of Open Access Journals (Sweden)

    Mohammad K. Al-Qaderi

    2018-03-01

    Full Text Available The paper presents a solution to the problem of person recognition by social robots via a novel brain-inspired multi-modal perceptual system. The system employs spiking neural network to integrate face, body features, and voice data to recognize a person in various social human-robot interaction scenarios. We suggest that, by and large, most reported multi-biometric person recognition algorithms require active participation by the subject and as such are not appropriate for social human-robot interactions. However, the proposed algorithm relaxes this constraint. As there are no public datasets for multimodal systems, we designed a hybrid dataset by integration of the ubiquitous FERET, RGB-D, and TIDIGITS datasets for face recognition, person recognition, and speaker recognition, respectively. The combined dataset facilitates association of facial features, body shape, and speech signature for multimodal person recognition in social settings. This multimodal dataset is employed for testing the algorithm. We assess the performance of the algorithm and discuss its merits against related methods. Within the context of the social robotics, the results suggest the superiority of the proposed method over other reported person recognition algorithms.

  12. Optical character recognition systems for different languages with soft computing

    CERN Document Server

    Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

    2017-01-01

    The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

  13. Automatic Number Plate Recognition System for IPhone Devices

    Directory of Open Access Journals (Sweden)

    Călin Enăchescu

    2013-06-01

    Full Text Available This paper presents a system for automatic number plate recognition, implemented for devices running the iOS operating system. The methods used for number plate recognition are based on existing methods, but optimized for devices with low hardware resources. To solve the task of automatic number plate recognition we have divided it into the following subtasks: image acquisition, localization of the number plate position on the image and character detection. The first subtask is performed by the camera of an iPhone, the second one is done using image pre-processing methods and template matching. For the character recognition we are using a feed-forward artificial neural network. Each of these methods is presented along with its results.

  14. Enhancement of Iris Recognition System Based on Phase Only Correlation

    Directory of Open Access Journals (Sweden)

    Nuriza Pramita

    2011-08-01

    Full Text Available Iris recognition system is one of biometric based recognition/identification systems. Numerous techniques have been implemented to achieve a good recognition rate, including the ones based on Phase Only Correlation (POC. Significant and higher correlation peaks suggest that the system recognizes iris images of the same subject (person, while lower and unsignificant peaks correspond to recognition of those of difference subjects. Current POC methods have not investigated minimum iris point that can be used to achieve higher correlation peaks. This paper proposed a method that used only one-fourth of full normalized iris size to achieve higher (or at least the same recognition rate. Simulation on CASIA version 1.0 iris image database showed that averaged recognition rate of the proposed method achieved 67%, higher than that of using one-half (56% and full (53% iris point. Furthermore, all (100% POC peak values of the proposed method was higher than that of the method with full iris points.

  15. Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

    Science.gov (United States)

    Huntsberger, Terry

    2011-01-01

    The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

  16. A Malaysian Vehicle License Plate Localization and Recognition System

    Directory of Open Access Journals (Sweden)

    Ganapathy Velappa

    2008-02-01

    Full Text Available Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services, secure usage of parking houses and also to prevent car theft issues. The proposed license plate localization algorithm is based on a combination of morphological processes with a modified Hough Transform approach and the recognition of the license plates is achieved by the implementation of the feed-forward backpropagation artificial neural network. Experimental results show an average of 95% successful license plate localization and recognition in a total of 589 images captured from a complex outdoor environment.

  17. Social context predicts recognition systems in ant queens

    DEFF Research Database (Denmark)

    Dreier, Stéphanie Agnès Jeanine; d'Ettorre, Patrizia

    2009-01-01

    for dominance are costly; but it would not evolve in absence of hierarchies. We previously showed that Pachycondyla co-founding queens, which form dominance hierarchies, have accurate individual recognition based on chemical cues. Here, we used the ant Lasius niger to test the null hypothesis that individual...... recognition does not occur when co-founding queens do not establish dominance hierarchies. Indeed, L. niger queens show a similar level of aggression towards both co-foundresses and intruders, indicating that they are unable of individual recognition, contrary to Pachycondyla. Additionally, the variation...... in chemical profiles of Lasius and Pachycondyla queens is comparable, thus informational constraints are unlikely to apply. We conclude that selection pressure from the social context is of crucial significance for the sophistication of recognition systems....

  18. Coherent digital/optical system for automatic target recognition (Abstract Only)

    Science.gov (United States)

    Derr, John I.; Ghaffari, Tammy G.

    1991-04-01

    Litton Data Systems has developed a hybrid ATR system using DataCube signal processing and imaging boards controlled by a host Sun workstation. The input image preprocessor includes detection algorithms that locate candidate targets in a simulated or real JR scene and segmentation algorithms that generate target outlines which are normalized for recognition processing by Litton's LIGHTMOD optical correlator. Target detection performs a raster scan over the image using nested boxes to find detection pixels based on intesity/variance contrasts. Segmentation operates on windows centered at the centroids of connected components of detection pixels. Optimal thresholds are determined from gray scale histograms. Multimodal optimization seeks to maximize edge/boundary proximities for candidate target and island components obtained by thresholding with respect to the optimal thresholds. Relaxation smooths the boundaries of optimal target components or merged target/island components. Normalization algorithms scale and center the component boundaries in a 128x128 LIGHT-MOD window. The LIGHT_MOD correlates the FT of the normalized outline with the FTs of a reference library of target outlines. Template matching is the basic technique used for recognition.

  19. Neural Mechanisms and Information Processing in Recognition Systems

    Directory of Open Access Journals (Sweden)

    Mamiko Ozaki

    2014-10-01

    Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

  20. Stability and boundary stabilization of 1-D hyperbolic systems

    CERN Document Server

    Bastin, Georges

    2016-01-01

    This monograph explores the modeling of conservation and balance laws of one-dimensional hyperbolic systems using partial differential equations. It presents typical examples of hyperbolic systems for a wide range of physical engineering applications, allowing readers to understand the concepts in whichever setting is most familiar to them. With these examples, it also illustrates how control boundary conditions may be defined for the most commonly used control devices. The authors begin with the simple case of systems of two linear conservation laws and then consider the stability of systems under more general boundary conditions that may be differential, nonlinear, or switching. They then extend their discussion to the case of nonlinear conservation laws and demonstrate the use of Lyapunov functions in this type of analysis. Systems of balance laws are considered next, starting with the linear variety before they move on to more general cases of nonlinear ones. They go on to show how the problem of boundary...

  1. A Malaysian Vehicle License Plate Localization and Recognition System

    OpenAIRE

    Ganapathy Velappa; Dennis LUI Wen Lik

    2008-01-01

    Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services,...

  2. Tuberculosis disease diagnosis using artificial immune recognition system.

    Science.gov (United States)

    Shamshirband, Shahaboddin; Hessam, Somayeh; Javidnia, Hossein; Amiribesheli, Mohsen; Vahdat, Shaghayegh; Petković, Dalibor; Gani, Abdullah; Kiah, Miss Laiha Mat

    2014-01-01

    There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. This study is aimed at diagnosing TB using hybrid machine learning approaches. Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm. Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

  3. Arm Motion Recognition and Exercise Coaching System for Remote Interaction

    Directory of Open Access Journals (Sweden)

    Hong Zeng

    2016-01-01

    Full Text Available Arm motion recognition and its related applications have become a promising human computer interaction modal due to the rapid integration of numerical sensors in modern mobile-phones. We implement a mobile-phone-based arm motion recognition and exercise coaching system that can help people carrying mobile-phones to do body exercising anywhere at any time, especially for the persons that have very limited spare time and are constantly traveling across cities. We first design improved k-means algorithm to cluster the collecting 3-axis acceleration and gyroscope data of person actions into basic motions. A learning method based on Hidden Markov Model is then designed to classify and recognize continuous arm motions of both learners and coaches, which also measures the action similarities between the persons. We implement the system on MIUI 2S mobile-phone and evaluate the system performance and its accuracy of recognition.

  4. Low Energy Physical Activity Recognition System on Smartphones

    Directory of Open Access Journals (Sweden)

    Luis Miguel Soria Morillo

    2015-03-01

    Full Text Available An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy.

  5. Low Energy Physical Activity Recognition System on Smartphones

    Science.gov (United States)

    Morillo, Luis Miguel Soria; Gonzalez-Abril, Luis; Ramirez, Juan Antonio Ortega; de la Concepcion, Miguel Angel Alvarez

    2015-01-01

    An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy. PMID:25742171

  6. Development of a speech recognition system for Spanish broadcast news

    NARCIS (Netherlands)

    Niculescu, A.I.; de Jong, Franciska M.G.

    2008-01-01

    This paper reports on the development process of a speech recognition system for Spanish broadcast news within the MESH FP6 project. The system uses the SONIC recognizer developed at the Center for Spoken Language Research (CSLR), University of Colorado. Acoustic and language models were trained

  7. Exhibits Recognition System for Combining Online Services and Offline Services

    Science.gov (United States)

    Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

    2017-10-01

    In order to achieve a more convenient and accurate digital museum navigation, we have developed a real-time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

  8. Two Systems for Automatic Music Genre Recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2012-01-01

    We re-implement and test two state-of-the-art systems for automatic music genre classification; but unlike past works in this area, we look closer than ever before at their behavior. First, we look at specific instances where each system consistently applies the same wrong label across multiple...... trials of cross-validation. Second, we test the robustness of each system to spectral equalization. Finally, we test how well human subjects recognize the genres of music excerpts composed by each system to be highly genre representative. Our results suggest that neither high-performing system has...... a capacity to recognize music genre....

  9. 9th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzyński, Marek; Woźniak, Michał; Żołnierek, Andrzej

    2016-01-01

    The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.  .

  10. A Context Dependent Automatic Target Recognition System

    Science.gov (United States)

    Kim, J. H.; Payton, D. W.; Olin, K. E.; Tseng, D. Y.

    1984-06-01

    This paper describes a new approach to automatic target recognizer (ATR) development utilizing artificial intelligent techniques. The ATR system exploits contextual information in its detection and classification processes to provide a high degree of robustness and adaptability. In the system, knowledge about domain objects and their contextual relationships is encoded in frames, separating it from low level image processing algorithms. This knowledge-based system demonstrates an improvement over the conventional statistical approach through the exploitation of diverse forms of knowledge in its decision-making process.

  11. Intelligent Facial Recognition Systems: Technology advancements for security applications

    Energy Technology Data Exchange (ETDEWEB)

    Beer, C.L.

    1993-07-01

    Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

  12. Method for secure electronic voting system: face recognition based approach

    Science.gov (United States)

    Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

    2017-06-01

    In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

  13. Auditory signal design for automatic number plate recognition system

    NARCIS (Netherlands)

    Heydra, C.G.; Jansen, R.J.; Van Egmond, R.

    2014-01-01

    This paper focuses on the design of an auditory signal for the Automatic Number Plate Recognition system of Dutch national police. The auditory signal is designed to alert police officers of suspicious cars in their proximity, communicating priority level and location of the suspicious car and

  14. Fuzzy expert system for the intelligent recognition of cerebral palsy ...

    African Journals Online (AJOL)

    This study describes a fuzzy system for intelligent recognition and estimation of possibility of suffering from cerebral palsy (CP) in children between the ages of 3 months and 2 years. The hallmark symptoms of CP are disturbances of movement and/or posture which are manifested as failure to meet appropriate motor ...

  15. A Compact Prototype of an Optical Pattern Recognition System

    Science.gov (United States)

    Jin, Y.; Liu, H. K.; Marzwell, N. I.

    1996-01-01

    In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.

  16. Boundary conditions for open quantum systems driven far from equilibrium

    Science.gov (United States)

    Frensley, William R.

    1990-07-01

    This is a study of simple kinetic models of open systems, in the sense of systems that can exchange conserved particles with their environment. The system is assumed to be one dimensional and situated between two particle reservoirs. Such a system is readily driven far from equilibrium if the chemical potentials of the reservoirs differ appreciably. The openness of the system modifies the spatial boundary conditions on the single-particle Liouville-von Neumann equation, leading to a non-Hermitian Liouville operator. If the open-system boundary conditions are time reversible, exponentially growing (unphysical) solutions are introduced into the time dependence of the density matrix. This problem is avoided by applying time-irreversible boundary conditions to the Wigner distribution function. These boundary conditions model the external environment as ideal particle reservoirs with properties analogous to those of a blackbody. This time-irreversible model may be numerically evaluated in a discrete approximation and has been applied to the study of a resonant-tunneling semiconductor diode. The physical and mathematical properties of the irreversible kinetic model, in both its discrete and its continuum formulations, are examined in detail. The model demonstrates the distinction in kinetic theory between commutator superoperators, which may become non-Hermitian to describe irreversible behavior, and anticommutator superoperators, which remain Hermitian and are used to evaluate physical observables.

  17. A system of automatic speaker recognition on a minicomputer

    International Nuclear Information System (INIS)

    El Chafei, Cherif

    1978-01-01

    This study describes a system of automatic speaker recognition using the pitch of the voice. The pre-treatment consists in the extraction of the speakers' discriminating characteristics taken from the pitch. The programme of recognition gives, firstly, a preselection and then calculates the distance between the speaker's characteristics to be recognized and those of the speakers already recorded. An experience of recognition has been realized. It has been undertaken with 15 speakers and included 566 tests spread over an intermittent period of four months. The discriminating characteristics used offer several interesting qualities. The algorithms concerning the measure of the characteristics on one hand, the speakers' classification on the other hand, are simple. The results obtained in real time with a minicomputer are satisfactory. Furthermore they probably could be improved if we considered other speaker's discriminating characteristics but this was unfortunately not in our possibilities. (author) [fr

  18. Inside Out: Organizations as Service Systems Equipped with Relational Boundaries

    Directory of Open Access Journals (Sweden)

    María Jimena Crespo Garrido

    2017-04-01

    Full Text Available Currently, literature on organizational boundaries is at the center of a heated debate, characterized by a shift from a transactional approach to a broader immaterial perspective centered on the concept of boundless organizations. However, the overestimation of the effects of contemporary dematerialization on business processes can lead to the progressive neglect of the existence of corporate borders. In light of this consideration, the present work aims at proposing a new type of criterion for defining organizational boundaries, halfway between the conception of the firm’s total openness and total closure. To this end, the authors envisage the use of a new interpretive logic defined as “relational”, resulting from the specification of the systemic view (and as the sum of the logic underlying the viable systems approach (VSA. This approach views the definition of boundaries. Therefore, in the large and intricate scenery of the studies dedicated to organizational boundaries, this work contributes to a better understanding of border selection as an interactive and changeable process capable of pushing organizations towards a greater awareness of their strategic dimension. This paper also offers some insights for future research, suggesting that both scholars and professionals investigate, firstly, new frontiers for the identification of organizational boundaries and, secondly, the possible positive repercussions that new organizational redesign modes could determine for a greater competitive success.

  19. MITLL 2015 Language Recognition Evaluation System Description

    Science.gov (United States)

    2016-01-27

    using SDC features BNF2: i-vector classifier trained using the BNF features STATS: i-vector classifier trained using the DNN posteriors and SDC ...features PITCH1: i-vector classifier trained using SDC and pitch features PITCH2: i-vector classifier trained using BNF and pitch features 2.1 CSAIL...The IVEC system used Shifted Delta Cepstra features as input. The SDC features used speech windowing of 20 ms length and 10 ms shift. Window DC was

  20. A Fault Recognition System for Gearboxes of Wind Turbines

    Science.gov (United States)

    Yang, Zhiling; Huang, Haiyue; Yin, Zidong

    2017-12-01

    Costs of maintenance and loss of power generation caused by the faults of wind turbines gearboxes are the main components of operation costs for a wind farm. Therefore, the technology of condition monitoring and fault recognition for wind turbines gearboxes is becoming a hot topic. A condition monitoring and fault recognition system (CMFRS) is presented for CBM of wind turbines gearboxes in this paper. The vibration signals from acceleration sensors at different locations of gearbox and the data from supervisory control and data acquisition (SCADA) system are collected to CMFRS. Then the feature extraction and optimization algorithm is applied to these operational data. Furthermore, to recognize the fault of gearboxes, the GSO-LSSVR algorithm is proposed, combining the least squares support vector regression machine (LSSVR) with the Glowworm Swarm Optimization (GSO) algorithm. Finally, the results show that the fault recognition system used in this paper has a high rate for identifying three states of wind turbines’ gears; besides, the combination of date features can affect the identifying rate and the selection optimization algorithm presented in this paper can get a pretty good date feature subset for the fault recognition.

  1. Application of Video Recognition Technology in Landslide Monitoring System

    Directory of Open Access Journals (Sweden)

    Qingjia Meng

    2018-01-01

    Full Text Available The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.

  2. Self-amplified optical pattern recognition system

    Science.gov (United States)

    Liu, Hua-Kuang (Inventor)

    1994-01-01

    A self amplifying optical pattern recognizer includes a geometric system configuration similar to that of a Vander Lugt holographic matched filter configuration with a photorefractive crystal specifically oriented with respect to the input beams. An extraordinarily polarized, spherically converging object image beam is formed by laser illumination of an input object image and applied through a photorefractive crystal, such as a barium titanite (BaTiO.sub.3) crystal. A volume or thin-film dif ORIGIN OF THE INVENTION The invention described herein was made in the performance of work under a NASA contract, and is subject to the provisions of Public Law 96-517 (35 USC 202) in which the Contractor has elected to retain title.

  3. Fusion of heterogeneous speaker recognition systems in the STBU submission for the NIST Speaker Recognition Evaluation 2006

    NARCIS (Netherlands)

    Brümmer, N.; Burget, L.; Černocký, J.H.; Glembek, O.; Grézl, F.; Karafiát, M.; Leeuwen, D.A. van; Matějka, P.; Schwarz, P.; Strasheim, A.

    2007-01-01

    This paper describes and discusses the "STBU" speaker recognition system, which performed well in the NIST Speaker Recognition Evaluation 2006 (SRE). STBU is a consortium of four partners: Spescom DataVoice (Stellenbosch, South Africa), TNO (Soesterberg, The Netherlands), BUT (Brno, Czech Republic),

  4. Optimal control problems for impulsive systems with integral boundary conditions

    Directory of Open Access Journals (Sweden)

    Allaberen Ashyralyev

    2013-03-01

    Full Text Available In this article, the optimal control problem is considered when the state of the system is described by the impulsive differential equations with integral boundary conditions. Applying the Banach contraction principle the existence and uniqueness of the solution is proved for the corresponding boundary problem by the fixed admissible control. The first and second variation of the functional is calculated. Various necessary conditions of optimality of the first and second order are obtained by the help of the variation of the controls.

  5. The Ablowitz-Ladik system with linearizable boundary conditions

    Science.gov (United States)

    Biondini, Gino; Bui, Anh

    2015-09-01

    The boundary value problem (BVP) for the Ablowitz-Ladik (AL) system on the natural numbers with linearizable boundary conditions is studied. In particular: (i) a discrete analogue is derived of the Bäcklund transformation that was used to solved similar BVPs for the nonlinear Schrödinger equation; (ii) an explicit proof is given that the Bäcklund-transformed solution of AL remains within the class of solutions that can be studied by the inverse scattering transform; (iii) an explicit linearizing transformation for the Bäcklund transformation is provided; (iv) explicit relations are obtained among the norming constants associated with symmetric eigenvalues; (v) conditions for the existence of self-symmetric eigenvalues are obtained. The results are illustrated by several exact soliton solutions, which describe the soliton reflection at the boundary with or without the presence of self-symmetric eigenvalues. This article is dedicated to Mark Ablowitz on the occasion of his seventieth birthday.

  6. Ego boundary as process: a systemic-contextual approach.

    Science.gov (United States)

    Polster, S

    1983-08-01

    This paper examines the ego boundary construct, outlining its origin and development within psychoanalytic theory and demonstrating the ways in which its interpretation and use have been affected and circumscribed by the structural model upon which psychoanalytic theory is based. In particular, I will discuss the sequence of reasoning by which the construct boundary became synonymous with barrier at the expense of consideration of its role in maintaining contact and exchange with the world. The contributions and limitations of the mathematical model of Kurt Lewin are also discussed. An alternative systemic-contextual model is proposed, a model which describes boundary not as barrier but as dialectical processes of separation and inclusion which mediate a person's complex relationship with the world.

  7. Time and timing in the acoustic recognition system of crickets

    Science.gov (United States)

    Hennig, R. Matthias; Heller, Klaus-Gerhard; Clemens, Jan

    2014-01-01

    The songs of many insects exhibit precise timing as the result of repetitive and stereotyped subunits on several time scales. As these signals encode the identity of a species, time and timing are important for the recognition system that analyzes these signals. Crickets are a prominent example as their songs are built from sound pulses that are broadcast in a long trill or as a chirped song. This pattern appears to be analyzed on two timescales, short and long. Recent evidence suggests that song recognition in crickets relies on two computations with respect to time; a short linear-nonlinear (LN) model that operates as a filter for pulse rate and a longer integration time window for monitoring song energy over time. Therefore, there is a twofold role for timing. A filter for pulse rate shows differentiating properties for which the specific timing of excitation and inhibition is important. For an integrator, however, the duration of the time window is more important than the precise timing of events. Here, we first review evidence for the role of LN-models and integration time windows for song recognition in crickets. We then parameterize the filter part by Gabor functions and explore the effects of duration, frequency, phase, and offset as these will correspond to differently timed patterns of excitation and inhibition. These filter properties were compared with known preference functions of crickets and katydids. In a comparative approach, the power for song discrimination by LN-models was tested with the songs of over 100 cricket species. It is demonstrated how the acoustic signals of crickets occupy a simple 2-dimensional space for song recognition that arises from timing, described by a Gabor function, and time, the integration window. Finally, we discuss the evolution of recognition systems in insects based on simple sensory computations. PMID:25161622

  8. Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

    Science.gov (United States)

    Wan, Qianwen; Panetta, Karen; Agaian, Sos

    2017-05-01

    Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

  9. Automated recognition system for ELM classification in JET

    International Nuclear Information System (INIS)

    Duro, N.; Dormido, R.; Vega, J.; Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H.; Murari, A.

    2009-01-01

    Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: Dα, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or Dα shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

  10. Speech recognition systems on the Cell Broadband Engine

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Y; Jones, H; Vaidya, S; Perrone, M; Tydlitat, B; Nanda, A

    2007-04-20

    In this paper we describe our design, implementation, and first results of a prototype connected-phoneme-based speech recognition system on the Cell Broadband Engine{trademark} (Cell/B.E.). Automatic speech recognition decodes speech samples into plain text (other representations are possible) and must process samples at real-time rates. Fortunately, the computational tasks involved in this pipeline are highly data-parallel and can receive significant hardware acceleration from vector-streaming architectures such as the Cell/B.E. Identifying and exploiting these parallelism opportunities is challenging, but also critical to improving system performance. We observed, from our initial performance timings, that a single Cell/B.E. processor can recognize speech from thousands of simultaneous voice channels in real time--a channel density that is orders-of-magnitude greater than the capacity of existing software speech recognizers based on CPUs (central processing units). This result emphasizes the potential for Cell/B.E.-based speech recognition and will likely lead to the future development of production speech systems using Cell/B.E. clusters.

  11. Automated recognition system for ELM classification in JET

    Energy Technology Data Exchange (ETDEWEB)

    Duro, N. [Dpto. de Informatica y Automatica - UNED, C/ Juan del Rosal 16, 28040 Madrid (Spain)], E-mail: nduro@dia.uned.es; Dormido, R. [Dpto. de Informatica y Automatica - UNED, C/ Juan del Rosal 16, 28040 Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avd. Complutense 22, 28040 Madrid (Spain); Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H. [Dpto. de Informatica y Automatica - UNED, C/ Juan del Rosal 16, 28040 Madrid (Spain); Murari, A. [Consorzio RFX-Associazione EURATOM ENEA per la Fusione, I-35127 Padua (Italy)

    2009-06-15

    Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: D{alpha}, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or D{alpha} shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

  12. Electrostatics of solvated systems in periodic boundary conditions

    Science.gov (United States)

    Andreussi, Oliviero; Marzari, Nicola

    2014-12-01

    Continuum solvation methods can provide an accurate and inexpensive embedding of quantum simulations in liquid or complex dielectric environments. Notwithstanding a long history and manifold applications to isolated systems in open boundary conditions, their extension to materials simulations, typically entailing periodic boundary conditions, is very recent, and special care is needed to address correctly the electrostatic terms. We discuss here how periodic boundary corrections developed for systems in vacuum should be modified to take into account solvent effects, using as a general framework the self-consistent continuum solvation model developed within plane-wave density-functional theory [O. Andreussi et al., J. Chem. Phys. 136, 064102 (2012), 10.1063/1.3676407]. A comprehensive discussion of real- and reciprocal-space corrective approaches is presented, together with an assessment of their ability to remove electrostatic interactions between periodic replicas. Numerical results for zero- and two-dimensional charged systems highlight the effectiveness of the different suggestions, and underline the importance of a proper treatment of electrostatic interactions in first-principles studies of charged systems in solution.

  13. Free boundary problems in PDEs and particle systems

    CERN Document Server

    Carinci, Gioia; Giardinà, Cristian; Presutti, Errico

    2016-01-01

    In this volume a theory for models of transport in the presence of a free boundary is developed. Macroscopic laws of transport are described by PDE's. When the system is open, there are several mechanisms to couple the system with the external forces. Here a class of systems where the interaction with the exterior takes place in correspondence of a free boundary is considered. Both continuous and discrete models sharing the same structure are analysed. In Part I a free boundary problem related to the Stefan Problem is worked out in all details. For this model a new notion of relaxed solution is proposed for which global existence and uniqueness is proven. It is also shown that this is the hydrodynamic limit of the empirical mass density of the associated particle system. In Part II several other models are discussed. The expectation is that the results proved for the basic model extend to these other cases. All the models discussed in this volume have an interest in problems arising in several research fields...

  14. System, subsystem, hive: boundary problems in computational theories of consciousness

    Directory of Open Access Journals (Sweden)

    Tomer Fekete

    2016-07-01

    Full Text Available A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i would reveal to what extent a given system is conscious, (ii would make it possible to compare not only different systems, but also the same system at different times, and (iii would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious will do so for some – perhaps most – of its subsystems, as well as for irrelevantly extended systems (e.g., the original system augmented with physical appendages that contribute nothing to the properties supposedly supporting consciousness, and for aggregates of individually conscious systems (e.g., groups of people. This problem suggests that the properties that are being measured are epiphenomenal to consciousness, or else it implies a bizarre proliferation of minds. We propose that a solution to the boundary problem can be found by identifying properties that are intrinsic or systemic: properties that clearly differentiate between systems whose existence is a matter of fact, as opposed to those whose existence is a matter of interpretation (in the eye of the beholder. We argue that if a putative MoC can be shown to be systemic, this ipso facto resolves any associated boundary issues. As test cases, we analyze two recent theories of consciousness in light of our definitions: the Integrated Information Theory and the Geometric Theory of consciousness.

  15. Model-based vision system for automatic recognition of structures in dental radiographs

    Science.gov (United States)

    Acharya, Raj S.; Samarabandu, Jagath K.; Hausmann, E.; Allen, K. A.

    1991-07-01

    X-ray diagnosis of destructive periodontal disease requires assessing serial radiographs by an expert to determine the change in the distance between cemento-enamel junction (CEJ) and the bone crest. To achieve this without the subjectivity of a human expert, a knowledge based system is proposed to automatically locate the two landmarks which are the CEJ and the level of alveolar crest at its junction with the periodontal ligament space. This work is a part of an ongoing project to automatically measure the distance between CEJ and the bone crest along a line parallel to the axis of the tooth. The approach presented in this paper is based on identifying a prominent feature such as the tooth boundary using local edge detection and edge thresholding to establish a reference and then using model knowledge to process sub-regions in locating the landmarks. Segmentation techniques invoked around these regions consists of a neural-network like hierarchical refinement scheme together with local gradient extraction, multilevel thresholding and ridge tracking. Recognition accuracy is further improved by first locating the easily identifiable parts of the bone surface and the interface between the enamel and the dentine and then extending these boundaries towards the periodontal ligament space and the tooth boundary respectively. The system is realized as a collection of tools (or knowledge sources) for pre-processing, segmentation, primary and secondary feature detection and a control structure based on the blackboard model to coordinate the activities of these tools.

  16. Source Separation via Spectral Masking for Speech Recognition Systems

    Directory of Open Access Journals (Sweden)

    Gustavo Fernandes Rodrigues

    2012-12-01

    Full Text Available In this paper we present an insight into the use of spectral masking techniques in time-frequency domain, as a preprocessing step for the speech signal recognition. Speech recognition systems have their performance negatively affected in noisy environments or in the presence of other speech signals. The limits of these masking techniques for different levels of the signal-to-noise ratio are discussed. We show the robustness of the spectral masking techniques against four types of noise: white, pink, brown and human speech noise (bubble noise. The main contribution of this work is to analyze the performance limits of recognition systems  using spectral masking. We obtain an increase of 18% on the speech hit rate, when the speech signals were corrupted by other speech signals or bubble noise, with different signal-to-noise ratio of approximately 1, 10 and 20 dB. On the other hand, applying the ideal binary masks to mixtures corrupted by white, pink and brown noise, results an average growth of 9% on the speech hit rate, with the same different signal-to-noise ratio. The experimental results suggest that the masking spectral techniques are more suitable for the case when it is applied a bubble noise, which is produced by human speech, than for the case of applying white, pink and brown noise.

  17. On the stability of boundary layers in gas mantle systems

    International Nuclear Information System (INIS)

    Ohlsson, D.

    1978-10-01

    In this thesis a systematic investigation of the stability properties of the partially ionized boundary regions of gas mantle systems for a large class of dissipative magneto-hydrodynamic modes is presented. In the partially ionized boundary regions of gas mantle systems several strong stabilizing mechanisms arise due to coupling between various dissipative effects in certain parameter regions. The presence of neutral gas strongly enhances the stabilizing effects in a dual fashion. First in an indirect way by cooling the edge region and second in a direct way by enhancing viscous and heat conduction effects. It has, however, to be pointed out that exceptions from this general picture may be found. The stabilizing influence of neutral gas on a large class of electrostatic as well as electromagnetic modes in the boundary regions of gas blanket systems is contrary to what has been found in low density weakly ionized plasmas. In these latter cases presence of neutral gas has even been found to be responsible for the onset of entirely new classes of instabilities. Thus there is no universal stabilizing or destabilizing effect associated with plasma-neutral gas interaction effects. (author)

  18. Improving emotion recognition systems by embedding cardiorespiratory coupling

    International Nuclear Information System (INIS)

    Valenza, Gaetano; Lanatá, Antonio; Scilingo, Enzo Pasquale

    2013-01-01

    This work aims at showing improved performances of an emotion recognition system embedding information gathered from cardiorespiratory (CR) coupling. Here, we propose a novel methodology able to robustly identify up to 25 regions of a two-dimensional space model, namely the well-known circumplex model of affect (CMA). The novelty of embedding CR coupling information in an autonomic nervous system-based feature space better reveals the sympathetic activations upon emotional stimuli. A CR synchrogram analysis was used to quantify such a coupling in terms of number of heartbeats per respiratory period. Physiological data were gathered from 35 healthy subjects emotionally elicited by means of affective pictures of the international affective picture system database. In this study, we finely detected five levels of arousal and five levels of valence as well as the neutral state, whose combinations were used for identifying 25 different affective states in the CMA plane. We show that the inclusion of the bivariate CR measures in a previously developed system based only on monovariate measures of heart rate variability, respiration dynamics and electrodermal response dramatically increases the recognition accuracy of a quadratic discriminant classifier, obtaining more than 90% of correct classification per class. Finally, we propose a comprehensive description of the CR coupling during sympathetic elicitation adapting an existing theoretical nonlinear model with external driving. The theoretical idea behind this model is that the CR system is comprised of weakly coupled self-sustained oscillators that, when exposed to an external perturbation (i.e. sympathetic activity), becomes synchronized and less sensible to input variations. Given the demonstrated role of the CR coupling, this model can constitute a general tool which is easily embedded in other model-based emotion recognition systems. (paper)

  19. Improving emotion recognition systems by embedding cardiorespiratory coupling.

    Science.gov (United States)

    Valenza, Gaetano; Lanatá, Antonio; Scilingo, Enzo Pasquale

    2013-04-01

    This work aims at showing improved performances of an emotion recognition system embedding information gathered from cardiorespiratory (CR) coupling. Here, we propose a novel methodology able to robustly identify up to 25 regions of a two-dimensional space model, namely the well-known circumplex model of affect (CMA). The novelty of embedding CR coupling information in an autonomic nervous system-based feature space better reveals the sympathetic activations upon emotional stimuli. A CR synchrogram analysis was used to quantify such a coupling in terms of number of heartbeats per respiratory period. Physiological data were gathered from 35 healthy subjects emotionally elicited by means of affective pictures of the international affective picture system database. In this study, we finely detected five levels of arousal and five levels of valence as well as the neutral state, whose combinations were used for identifying 25 different affective states in the CMA plane. We show that the inclusion of the bivariate CR measures in a previously developed system based only on monovariate measures of heart rate variability, respiration dynamics and electrodermal response dramatically increases the recognition accuracy of a quadratic discriminant classifier, obtaining more than 90% of correct classification per class. Finally, we propose a comprehensive description of the CR coupling during sympathetic elicitation adapting an existing theoretical nonlinear model with external driving. The theoretical idea behind this model is that the CR system is comprised of weakly coupled self-sustained oscillators that, when exposed to an external perturbation (i.e. sympathetic activity), becomes synchronized and less sensible to input variations. Given the demonstrated role of the CR coupling, this model can constitute a general tool which is easily embedded in other model-based emotion recognition systems.

  20. Multivariate statistical pattern recognition system for reactor noise analysis

    International Nuclear Information System (INIS)

    Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

    1975-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references

  1. Image analysis in automatic system of pollen recognition

    Directory of Open Access Journals (Sweden)

    Piotr Rapiejko

    2012-12-01

    Full Text Available In allergology practice and research, it would be convenient to receive pollen identification and monitoring results in much shorter time than it comes from human identification. Image based analysis is one of the approaches to an automated identification scheme for pollen grain and pattern recognition on such images is widely used as a powerful tool. The goal of such attempt is to provide accurate, fast recognition and classification and counting of pollen grains by computer system for monitoring. The isolated pollen grain are objects extracted from microscopic image by CCD camera and PC computer under proper conditions for further analysis. The algorithms are based on the knowledge from feature vector analysis of estimated parameters calculated from grain characteristics, including morphological features, surface features and other applicable estimated characteristics. Segmentation algorithms specially tailored to pollen object characteristics provide exact descriptions of pollen characteristics (border and internal features already used by human expert. The specific characteristics and its measures are statistically estimated for each object. Some low level statistics for estimated local and global measures of the features establish the feature space. Some special care should be paid on choosing these feature and on constructing the feature space to optimize the number of subspaces for higher recognition rates in low-level classification for type differentiation of pollen grains.The results of estimated parameters of feature vector in low dimension space for some typical pollen types are presented, as well as some effective and fast recognition results of performed experiments for different pollens. The findings show the ewidence of using proper chosen estimators of central and invariant moments (M21, NM2, NM3, NM8 NM9, of tailored characteristics for good enough classification measures (efficiency > 95%, even for low dimensional classifiers

  2. Human-inspired sound environment recognition system for assistive vehicles

    Science.gov (United States)

    González Vidal, Eduardo; Fredes Zarricueta, Ernesto; Auat Cheein, Fernando

    2015-02-01

    Objective. The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. Approach. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. Main results. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. Significance

  3. Military personnel recognition system using texture, colour, and SURF features

    Science.gov (United States)

    Irhebhude, Martins E.; Edirisinghe, Eran A.

    2014-06-01

    This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

  4. Speech Recognition System For Robotic Control And Movement

    Directory of Open Access Journals (Sweden)

    Biraja Nalini Rout

    2015-08-01

    Full Text Available Abstract In a current scenario voice and data recognition is one of the most sought after field in the area of artificial intelligence and robotic 1 engineering. The idea specializes on deriving a voice to voice intelligent system which operates purely on audiovoice instructions using a specialized voice recognition module a micro controller a set of wheels and a movable arm to operate. The working involves real time voice inputs feeded to the VR module which equivalently processes the audio signals and produces the output in audio format. It consists an IDE for both Windows and UNIX based operating system for manipulating and processing instructions both at software and hardware levels. The system also can perform a basic set of manual operations decides through the expert system. The VR module processes the data using multilayer perceptron to generate the required result. Movable arm operates to pick and place objects as per the given voice instructions. Its usability involves substituting manual work at both personal and professional levels.

  5. Application of robust face recognition in video surveillance systems

    Science.gov (United States)

    Zhang, De-xin; An, Peng; Zhang, Hao-xiang

    2018-03-01

    In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfect fit for searching targeted individuals within the vast amount of video data. However, the performance of such searching depends on the quality of face images recorded in the video signals. Since the surveillance video cameras record videos without fixed postures for the object, face occlusion is very common in everyday video. The proposed system builds a model for occluded faces using fuzzy principal component analysis (FPCA), and reconstructs the human faces with the available information. Experimental results show that the system has very high efficiency in processing the real life videos, and it is very robust to various kinds of face occlusions. Hence it can relieve people reviewers from the front of the monitors and greatly enhances the efficiency as well. The proposed system has been installed and applied in various environments and has already demonstrated its power by helping solving real cases.

  6. Defining System Boundaries of an Institution Nitrogen Footprint.

    Science.gov (United States)

    de la Reguera, Elizabeth; Castner, Elizabeth A; Galloway, James N; Leach, Allison M; Leary, Neil; Tang, Jianwu

    2017-04-01

    A nitrogen (N) footprint quantifies the amount of reactive nitrogen released to the environment and can be measured at different scales. The N footprint of a university includes activities and consumption within its geographic boundaries as well as activities that support the institution. Determining system bounds of an N footprint depends on the institution's mission and provides a common baseline for comparison. A comparison of three scopes of the N footprint, which describe how emissions are directly related to an institution's activities, was conducted for seven institutions. Scopes follow the established definition for the carbon footprint. In this article, the authors propose a new system bounds definition (core campus versus adjunct). Two case studies were explored: how the N footprint of Dickinson College changed with air travel, and how the N footprint of the Marine Biological Laboratory changed with scientific research. Of the three scopes, scope 3 was consistently the largest proportion of the N footprint for all seven institutions. The core campus activities of Dickinson College made up 99 percent of its N footprint, with air travel making up the remaining 1 percent. The Marine Biological Laboratory's core campus activities made up 51 percent of its N footprint and the scientific research made up the remaining 49 percent. Institutions should define system bounds based on their mission and stay consistent with their boundaries following the baseline year. The core campus footprint could be used to compare institution footprints using consistent system bounds. How institutions define their boundaries will impact the recorded amount of nitrogen as well as how the institution will set reduction strategies.

  7. A Development of Hybrid Drug Information System Using Image Recognition

    Directory of Open Access Journals (Sweden)

    HwaMin Lee

    2015-04-01

    Full Text Available In order to prevent drug abuse or misuse cases and avoid over-prescriptions, it is necessary for medicine taker to be provided with detailed information about the medicine. In this paper, we propose a drug information system and develop an application to provide information through drug image recognition using a smartphone. We designed a contents-based drug image search algorithm using the color, shape and imprint of drug. Our convenient application can provide users with detailed information about drugs and prevent drug misuse.

  8. Matrix sentence intelligibility prediction using an automatic speech recognition system.

    Science.gov (United States)

    Schädler, Marc René; Warzybok, Anna; Hochmuth, Sabine; Kollmeier, Birger

    2015-01-01

    The feasibility of predicting the outcome of the German matrix sentence test for different types of stationary background noise using an automatic speech recognition (ASR) system was studied. Speech reception thresholds (SRT) of 50% intelligibility were predicted in seven noise conditions. The ASR system used Mel-frequency cepstral coefficients as a front-end and employed whole-word Hidden Markov models on the back-end side. The ASR system was trained and tested with noisy matrix sentences on a broad range of signal-to-noise ratios. The ASR-based predictions were compared to data from the literature ( Hochmuth et al, 2015 ) obtained with 10 native German listeners with normal hearing and predictions of the speech intelligibility index (SII). The ASR-based predictions showed a high and significant correlation (R² = 0.95, p speech and noise signals. Minimum assumptions were made about human speech processing already incorporated in a reference-free ordinary ASR system.

  9. PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

    Directory of Open Access Journals (Sweden)

    ANEES ABU SNEINEH

    2017-05-01

    Full Text Available Providing employees with protection and security is one of the key concerns of any organization. This goal can be implemented mainly by managing and protecting employees’ cars in the parking area. Therefore, a parking area must be managed and organized with smart technologies and tools that can be applied and integrated in an intelligent parking system. This paper presents the tools based on image recognition technology that can be used to effectively control various parts of a parking system. An intelligent automotive parking system is effectively implemented by integrating image processing technologies and an Arduino controller. Results show that intelligent parking is successfully implemented based on car ID image capture to meet the need for managing and organizing car parking systems.

  10. Formal Implementation of a Performance Evaluation Model for the Face Recognition System

    Directory of Open Access Journals (Sweden)

    Yong-Nyuo Shin

    2008-01-01

    Full Text Available Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

  11. Boundary control of long waves in nonlinear dispersive systems

    DEFF Research Database (Denmark)

    Hasan, Agus; Foss, Bjarne; Aamo, Ole Morten

    2011-01-01

    orders of the nonlinearity, the equation may have unstable solitary wave solutions. Although it is a one dimensional problem, achieving a global result for this equation is not trivial due to the nonlinearity and the mixed partial derivative. In this paper, two sets of nonlinear boundary control laws......Unidirectional propagation of long waves in nonlinear dispersive systems may be modeled by the Benjamin-Bona-Mahony-Burgers equation, a third order partial differential equation incorporating linear dissipative and dispersive terms, as well as a term covering nonlinear wave phenomena. For higher...... that achieve global exponential stability and semi-global exponential stability are derived for both linear and nonlinear cases....

  12. Traffic Sign Recognition System based on Cambridge Correlator Image Comparator

    Directory of Open Access Journals (Sweden)

    J. Turan

    2012-06-01

    Full Text Available Paper presents basic information about application of Optical Correlator (OC, specifically Cambridge Correlator, in system to recognize of traffic sign. Traffic Sign Recognition System consists of three main blocks, Preprocessing, Optical Correlator and Traffic Sign Identification. The Region of Interest (ROI is defined and chosen in preprocessing block and then goes to Optical Correlator, where is compared with database of Traffic Sign. Output of Optical Correlation is correlation plane, which consist of highly localized intensities, know as correlation peaks. The intensity of spots provides a measure of similarity and position of spots, how images (traffic signs are relatively aligned in the input scene. Several experiments have been done with proposed system and results and conclusion are discussed.

  13. A Chinese Named Entity Recognition System with Neural Networks

    Directory of Open Access Journals (Sweden)

    Yi Hui-Kang

    2017-01-01

    Full Text Available Named entity recognition (NER is a typical sequential labeling problem that plays an important role in natural language processing (NLP systems. In this paper, we discussed the details of applying a comprehensive model aggregating neural networks and conditional random field (CRF on Chinese NER tasks, and how to discovery character level features when implement a NER system in word level. We compared the difference between Chinese and English when modeling the character embeddings. We developed a NER system based on our analysis, it works well on the ACE 2004 and SIGHAN bakeoff 2006 MSRA dataset, and doesn’t rely on any gazetteers or handcraft features. We obtained F1 score of 82.3% on MSRA 2006.

  14. Collocation and Pattern Recognition Effects on System Failure Remediation

    Science.gov (United States)

    Trujillo, Anna C.; Press, Hayes N.

    2007-01-01

    Previous research found that operators prefer to have status, alerts, and controls located on the same screen. Unfortunately, that research was done with displays that were not designed specifically for collocation. In this experiment, twelve subjects evaluated two displays specifically designed for collocating system information against a baseline that consisted of dial status displays, a separate alert area, and a controls panel. These displays differed in the amount of collocation, pattern matching, and parameter movement compared to display size. During the data runs, subjects kept a randomly moving target centered on a display using a left-handed joystick and they scanned system displays to find a problem in order to correct it using the provided checklist. Results indicate that large parameter movement aided detection and then pattern recognition is needed for diagnosis but the collocated displays centralized all the information subjects needed, which reduced workload. Therefore, the collocated display with large parameter movement may be an acceptable display after familiarization because of the possible pattern recognition developed with training and its use.

  15. A novel handwritten character recognition system using gradient ...

    Indian Academy of Sciences (India)

    ing aspect ratio, position of centroid and ratio of pixels on the vertical halves of a character image. The recognition accuracy of 99.78% was achieved with minimum computational and storage requirement. Keywords. Gradient; RLC; handwritten character recognition; quadratic classi- fiers; MLP. 1. Introduction. Recognition ...

  16. Business model for sensor-based fall recognition systems.

    Science.gov (United States)

    Fachinger, Uwe; Schöpke, Birte

    2014-01-01

    AAL systems require, in addition to sophisticated and reliable technology, adequate business models for their launch and sustainable establishment. This paper presents the basic features of alternative business models for a sensor-based fall recognition system which was developed within the context of the "Lower Saxony Research Network Design of Environments for Ageing" (GAL). The models were developed parallel to the R&D process with successive adaptation and concretization. An overview of the basic features (i.e. nine partial models) of the business model is given and the mutual exclusive alternatives for each partial model are presented. The partial models are interconnected and the combinations of compatible alternatives lead to consistent alternative business models. However, in the current state, only initial concepts of alternative business models can be deduced. The next step will be to gather additional information to work out more detailed models.

  17. Pattern-Recognition System for Approaching a Known Target

    Science.gov (United States)

    Huntsberger, Terrance; Cheng, Yang

    2008-01-01

    A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the

  18. Entrance C - New Automatic Number Plate Recognition System

    CERN Multimedia

    2013-01-01

    Entrance C (Satigny) is now equipped with a latest-generation Automatic Number Plate Recognition (ANPR) system and a fast-action road gate.   During the month of August, Entrance C will be continuously open from 7.00 a.m. to 7.00 p.m. (working days only). The security guards will open the gate as usual from 7.00 a.m. to 9.00 a.m. and from 5.00 p.m. to 7.00 p.m. For the rest of the working day (9.00 a.m. to 5.00 p.m.) the gate will operate automatically. Please observe the following points:       Stop at the STOP sign on the ground     Position yourself next to the card reader for optimal recognition     Motorcyclists must use their CERN card     Cyclists may not activate the gate and should use the bicycle turnstile     Keep a safe distance from the vehicle in front of you   If access is denied, please check that your vehicle regist...

  19. Simple test system for single molecule recognition force microscopy

    International Nuclear Information System (INIS)

    Riener, Christian K.; Stroh, Cordula M.; Ebner, Andreas; Klampfl, Christian; Gall, Alex A.; Romanin, Christoph; Lyubchenko, Yuri L.; Hinterdorfer, Peter; Gruber, Hermann J.

    2003-01-01

    We have established an easy-to-use test system for detecting receptor-ligand interactions on the single molecule level using atomic force microscopy (AFM). For this, avidin-biotin, probably the best characterized receptor-ligand pair, was chosen. AFM sensors were prepared containing tethered biotin molecules at sufficiently low surface concentrations appropriate for single molecule studies. A biotin tether, consisting of a 6 nm poly(ethylene glycol) (PEG) chain and a functional succinimide group at the other end, was newly synthesized and covalently coupled to amine-functionalized AFM tips. In particular, PEG 800 diamine was glutarylated, the mono-adduct NH 2 -PEG-COOH was isolated by ion exchange chromatography and reacted with biotin succinimidylester to give biotin-PEG-COOH which was then activated as N-hydroxysuccinimide (NHS) ester to give the biotin-PEG-NHS conjugate which was coupled to the aminofunctionalized AFM tip. The motional freedom provided by PEG allows for free rotation of the biotin molecule on the AFM sensor and for specific binding to avidin which had been adsorbed to mica surfaces via electrostatic interactions. Specific avidin-biotin recognition events were discriminated from nonspecific tip-mica adhesion by their typical unbinding force (∼40 pN at 1.4 nN/s loading rate), unbinding length (<13 nm), the characteristic nonlinear force-distance relation of the PEG linker, and by specific block with excess of free d-biotin. The convenience of the test system allowed to evaluate, and compare, different methods and conditions of tip aminofunctionalization with respect to specific binding and nonspecific adhesion. It is concluded that this system is well suited as calibration or start-up kit for single molecule recognition force microscopy

  20. HMM Adaptation for Improving a Human Activity Recognition System

    Directory of Open Access Journals (Sweden)

    Rubén San-Segundo

    2016-09-01

    Full Text Available When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs. This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity, and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.

  1. Using Face Recognition System in Ship Protection Process

    Directory of Open Access Journals (Sweden)

    Miroslav Bača

    2006-03-01

    Full Text Available The process of security improvement is a huge problem especiallyin large ships. Terrorist attacks and everyday threatsagainst life and property destroy transport and tourist companies,especially large tourist ships. Every person on a ship can berecognized and identified using something that the personknows or by means of something the person possesses. The bestresults will be obtained by using a combination of the person'sknowledge with one biometric characteristic. Analyzing theproblem of biometrics in ITS security we can conclude that facerecognition process supported by one or two traditional biometriccharacteristics can give very good results regarding ship security.In this paper we will describe a biometric system basedon face recognition. Special focus will be given to crew member'sbiometric security in crisis situation like kidnapping, robbelyor illness.

  2. Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2014-01-01

    Full Text Available Degradation diagnosis plays an important role for degraded character processing, which can tell the recognition difficulty of a given degraded character. In this paper, we present a framework for automated degraded character recognition system by statistical syntactic approach using 3D primitive symbol, which is integrated by degradation diagnosis to provide accurate and reliable recognition results. Our contribution is to design the framework to build the character recognition submodels corresponding to degradation subject to camera vibration or out of focus. In each character recognition submodel, statistical syntactic approach using 3D primitive symbol is proposed to improve degraded character recognition performance. In the experiments, we show attractive experimental results, highlighting the system efficiency and recognition performance by statistical syntactic approach using 3D primitive symbol on the degraded character dataset.

  3. Development of a System for Automatic Recognition of Speech

    Directory of Open Access Journals (Sweden)

    Roman Jarina

    2003-01-01

    Full Text Available The article gives a review of a research on processing and automatic recognition of speech signals (ARR at the Department of Telecommunications of the Faculty of Electrical Engineering, University of iilina. On-going research is oriented to speech parametrization using 2-dimensional cepstral analysis, and to an application of HMMs and neural networks for speech recognition in Slovak language. The article summarizes achieved results and outlines future orientation of our research in automatic speech recognition.

  4. Face recognition system and method using face pattern words and face pattern bytes

    Science.gov (United States)

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  5. Poka Yoke system based on image analysis and object recognition

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  6. Human Iris Recognition System using Wavelet Transform and LVQ

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kwan Yong; Lim, Shin Young [Electronics and Telecommunications Research Institute (Korea); Cho, Seong Won [Hongik University (Korea)

    2000-07-01

    The popular methods to check the identity of individuals include passwords and ID cards. These conventional methods for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way. (author). 14 refs., 13 figs., 7 tabs.

  7. Hamiltonian formulation of distributed-parameter systems with boundary energy flow

    NARCIS (Netherlands)

    van der Schaft, A.J.; Maschke, B.M.

    2001-01-01

    A Hamiltonian formulation of classes of distributed-parameter systems is presented, which incorporates the energy flow through the boundary of the spatial domain of the system, and which allows to represent the system as a boundary control Hamiltonian system. The system is Hamiltonian with respect

  8. Hamiltonian formulation of distributed-parameter systems with boundary energy flow

    NARCIS (Netherlands)

    van der Schaft, Arjan; Maschke, B.M.

    A Hamiltonian formulation of classes of distributed-parameter systems is presented, which incorporates the energy flow through the boundary of the spatial domain of the system, and which allows to represent the system as a boundary control Hamiltonian system. The system is Hamiltonian with respect

  9. Hamiltonian formulation of distributed-parameter systems with boundary energy flow

    NARCIS (Netherlands)

    Schaft, A.J. van der; Maschke, B.M.

    2002-01-01

    A Hamiltonian formulation of classes of distributed-parameter systems is presented, which incorporates the energy flow through the boundary of the spatial domain of the system, and which allows to represent the system as a boundary control Hamiltonian system. The system is Hamiltonian with respect

  10. Data Pipeline Development for Grain Boundary Structures Classification

    OpenAIRE

    Li, Bingxi

    2017-01-01

    Grain Boundaries govern many properties of polycrystalline materials, including the vast majority of engineering materials. Evolutionary algorithm can be applied to predict the grain boundary structures in different systems. However, the recognition and classification of thousands of predicted structures is a very challenging work for eye detection in terms of efficiency and accuracy. A data pipeline is developed to accelerate the classification and recognition of grain boundary structures pr...

  11. Evaluation of a voice recognition system for the MOTAS pseudo pilot station function

    Science.gov (United States)

    Houck, J. A.

    1982-01-01

    The Langley Research Center has undertaken a technology development activity to provide a capability, the mission oriented terminal area simulation (MOTAS), wherein terminal area and aircraft systems studies can be performed. An experiment was conducted to evaluate state-of-the-art voice recognition technology and specifically, the Threshold 600 voice recognition system to serve as an aircraft control input device for the MOTAS pseudo pilot station function. The results of the experiment using ten subjects showed a recognition error of 3.67 percent for a 48-word vocabulary tested against a programmed vocabulary of 103 words. After the ten subjects retrained the Threshold 600 system for the words which were misrecognized or rejected, the recognition error decreased to 1.96 percent. The rejection rates for both cases were less than 0.70 percent. Based on the results of the experiment, voice recognition technology and specifically the Threshold 600 voice recognition system were chosen to fulfill this MOTAS function.

  12. Automatic sociophonetics: Exploring corpora with a forensic accent recognition system.

    Science.gov (United States)

    Brown, Georgina; Wormald, Jessica

    2017-07-01

    This paper demonstrates how the Y-ACCDIST system, the York ACCDIST-based automatic accent recognition system [Brown (2015). Proceedings of the International Congress of Phonetic Sciences, Glasgow, UK], can be used to inspect sociophonetic corpora as a preliminary "screening" tool. Although Y-ACCDIST's intended application is to assist with forensic casework, the system can also be exploited in sociophonetic research to begin unpacking variation. Using a subset of the PEBL (Panjabi-English in Bradford and Leicester) corpus, the outputs of Y-ACCDIST are explored, which, it is argued, efficiently and objectively assess speaker similarities across different linguistic varieties. The ways these outputs corroborate with a phonetic analysis of the data are also discovered. First, Y-ACCDIST is used to classify speakers from the corpus based on language background and region. A Y-ACCDIST cluster analysis is then implemented, which groups speakers in ways consistent with more localised networks, providing a means of identifying potential communities of practice. Additionally, the results of a Y-ACCDIST feature selection task that indicates which specific phonemes are most valuable in distinguishing between speaker groups are presented. How Y-ACCDIST outputs can be used to reinforce more traditional sociophonetic analyses and support qualitative interpretations of the data is demonstrated.

  13. Contextual System of Symbol Structural Recognition based on an Object-Process Methodology

    OpenAIRE

    Delalandre, Mathieu

    2005-01-01

    We present in this paper a symbol recognition system for the graphic documents. This one is based on a contextual approach for symbol structural recognition exploiting an Object-Process Methodology. It uses a processing library composed of structural recognition processings and contextual evaluation processings. These processings allow our system to deal with the multi-representation of symbols. The different processings are controlled, in an automatic way, by an inference engine during the r...

  14. Ethical aspects of face recognition systems in public places.

    NARCIS (Netherlands)

    Brey, Philip A.E.

    2004-01-01

    This essay examines ethical aspects of the use of facial recognition technology for surveillance purposes in public and semipublic areas, focusing particularly on the balance between security and privacy and civil liberties. As a case study, the FaceIt facial recognition engine of Identix

  15. On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

    Science.gov (United States)

    Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

    Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

  16. Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems

    Science.gov (United States)

    Ye, Sherry

    2015-01-01

    NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.

  17. Implementation of CT and IHT Processors for Invariant Object Recognition System

    Directory of Open Access Journals (Sweden)

    J. Turan jr.

    2004-12-01

    Full Text Available This paper presents PDL or ASIC implementation of key modules ofinvariant object recognition system based on the combination of theIncremental Hough transform (IHT, correlation and rapid transform(RT. The invariant object recognition system was represented partiallyin C++ language for general-purpose processor on personal computer andpartially described in VHDL code for implementation in PLD or ASIC.

  18. The effect of image resolution on the performance of a face recognition system

    NARCIS (Netherlands)

    Boom, B.J.; Beumer, G.M.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2006-01-01

    In this paper we investigate the effect of image resolution on the error rates of a face verification system. We do not restrict ourselves to the face recognition algorithm only, but we also consider the face registration. In our face recognition system, the face registration is done by finding

  19. A Single-System Account of the Relationship between Priming, Recognition, and Fluency

    Science.gov (United States)

    Berry, Christopher J.; Shanks, David R.; Henson, Richard N. A.

    2008-01-01

    A single-system computational model of priming and recognition was applied to studies that have looked at the relationship between priming, recognition, and fluency in continuous identification paradigms. The model was applied to 3 findings that have been interpreted as evidence for a multiple-systems account: (a) priming can occur for items not…

  20. Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

    Science.gov (United States)

    Fang, Fuming; Shinozaki, Takahiro

    2018-01-01

    Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

  1. Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

    Directory of Open Access Journals (Sweden)

    Fuming Fang

    Full Text Available Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG, and then a hidden Markov model (HMM is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

  2. Recognition of medical errors' reporting system dimensions in educational hospitals.

    Science.gov (United States)

    Yarmohammadian, Mohammad H; Mohammadinia, Leila; Tavakoli, Nahid; Ghalriz, Parvin; Haghshenas, Abbas

    2014-01-01

    Nowadays medical errors are one of the serious issues in the health-care system and carry to account of the patient's safety threat. The most important step for achieving safety promotion is identifying errors and their causes in order to recognize, correct and omit them. Concerning about repeating medical errors and harms, which were received via theses errors concluded to designing and establishing medical error reporting systems for hospitals and centers that are presenting therapeutic services. The aim of this study is the recognition of medical errors' reporting system dimensions in educational hospitals. This research is a descriptive-analytical and qualities' study, which has been carried out in Shahid Beheshti educational therapeutic center in Isfahan during 2012. In this study, relevant information was collected through 15 face to face interviews. That each of interviews take place in about 1hr and creation of five focused discussion groups through 45 min for each section, they were composed of Metron, educational supervisor, health officer, health education, and all of the head nurses. Concluded data interviews and discussion sessions were coded, then achieved results were extracted in the presence of clear-sighted persons and after their feedback perception, they were categorized. In order to make sure of information correctness, tables were presented to the research's interviewers and final the corrections were confirmed based on their view. The extracted information from interviews and discussion groups have been divided into nine main categories after content analyzing and subject coding and their subsets have been completely expressed. Achieved dimensions are composed of nine domains of medical error concept, error cases according to nurses' prospection, medical error reporting barriers, employees' motivational factors for error reporting, purposes of medical error reporting system, error reporting's challenges and opportunities, a desired system

  3. A carbohydrate-anion recognition system in aprotic solvents.

    Science.gov (United States)

    Ren, Bo; Dong, Hai; Ramström, Olof

    2014-05-01

    A carbohydrate-anion recognition system in nonpolar solvents is reported, in which complexes form at the B-faces of β-D-pyranosides with H1-, H3-, and H5-cis patterns similar to carbohydrate-π interactions. The complexation effect was evaluated for a range of carbohydrate structures; it resulted in either 1:1 carbohydrate-anion complexes, or 1:2 complex formation depending on the protection pattern of the carbohydrate. The interaction was also evaluated with different anions and solvents. In both cases it resulted in significant binding differences. The results indicate that complexation originates from van der Waals interactions or weak CH⋅⋅⋅A(-) hydrogen bonds between the binding partners and is related to electron-withdrawing groups of the carbohydrates as well as increased hydrogen-bond-accepting capability of the anions. © 2014 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

  4. Visual object recognition for mobile tourist information systems

    Science.gov (United States)

    Paletta, Lucas; Fritz, Gerald; Seifert, Christin; Luley, Patrick; Almer, Alexander

    2005-03-01

    We describe a mobile vision system that is capable of automated object identification using images captured from a PDA or a camera phone. We present a solution for the enabling technology of outdoors vision based object recognition that will extend state-of-the-art location and context aware services towards object based awareness in urban environments. In the proposed application scenario, tourist pedestrians are equipped with GPS, W-LAN and a camera attached to a PDA or a camera phone. They are interested whether their field of view contains tourist sights that would point to more detailed information. Multimedia type data about related history, the architecture, or other related cultural context of historic or artistic relevance might be explored by a mobile user who is intending to learn within the urban environment. Learning from ambient cues is in this way achieved by pointing the device towards the urban sight, capturing an image, and consequently getting information about the object on site and within the focus of attention, i.e., the users current field of view.

  5. System and method for free-boundary surface extraction

    KAUST Repository

    Algarni, Marei

    2017-10-26

    A method of extracting surfaces in three-dimensional data includes receiving as inputs three-dimensional data and a seed point p located on a surface to be extracted. The method further includes propagating a front outwardly from the seed point p and extracting a plurality of ridge curves based on the propagated front. A surface boundary is detected based on a comparison of distances between adjacent ridge curves and the desired surface is extracted based on the detected surface boundary.

  6. Implementation of age and gender recognition system for intelligent digital signage

    Science.gov (United States)

    Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

    2015-12-01

    Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

  7. Boundary Equations and Regularity Theory for Geometric Variational Systems with Neumann Data

    Science.gov (United States)

    Schikorra, Armin

    2018-02-01

    We study boundary regularity of maps from two-dimensional domains into manifolds which are critical with respect to a generic conformally invariant variational functional and which, at the boundary, intersect perpendicularly with a support manifold. For example, harmonic maps, or H-surfaces, with a partially free boundary condition. In the interior it is known, by the celebrated work of Rivière, that these maps satisfy a system with an antisymmetric potential, from which one can derive the interior regularity of the solution. Avoiding a reflection argument, we show that these maps satisfy along the boundary a system of equations which also exhibits a (nonlocal) antisymmetric potential that combines information from the interior potential and the geometric Neumann boundary condition. We then proceed to show boundary regularity for solutions to such systems.

  8. Multi-font printed Mongolian document recognition system

    Science.gov (United States)

    Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

    2009-01-01

    Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

  9. Animal Recognition System Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Tibor Trnovszky

    2017-01-01

    Full Text Available In this paper, the performances of well-known image recognition methods such as Principal Component Analysis (PCA, Linear Discriminant Analysis (LDA, Local Binary Patterns Histograms (LBPH and Support Vector Machine (SVM are tested and compared with proposed convolutional neural network (CNN for the recognition rate of the input animal images. In our experiments, the overall recognition accuracy of PCA, LDA, LBPH and SVM is demonstrated. Next, the time execution for animal recognition process is evaluated. The all experimental results on created animal database were conducted. This created animal database consist of 500 different subjects (5 classes/ 100 images for each class. The experimental result shows that the PCA features provide better results as LDA and LBPH for large training set. On the other hand, LBPH is better than PCA and LDA for small training data set. For proposed CNN we have obtained a recognition accuracy of 98%. The proposed method based on CNN outperforms the state of the art methods.

  10. Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

    NARCIS (Netherlands)

    Peng, Y.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2016-01-01

    Most face recognition systems deal well with high-resolution facial images, but perform much worse on low-resolution facial images. In low-resolution face recognition, there is a specific but realistic surveillance scenario: a surveillance camera monitoring a large area. In this scenario, usually

  11. Evaluation of Recharge Trench System, North Boundary Containment Treatment System, Rocky Mountain Arsenal, Commerce City, Colorado

    National Research Council Canada - National Science Library

    Corcoran, Maureen K; Patrick, David M; Gaggiani, Neville G; May, James H

    2005-01-01

    ...) at Rocky Mountain Arsenal (RMA), located in Commerce City, CO. The NBCTS is a 6,740-fT (2,054-M)-long multicomponent system that precludes off-site movement of contaminated water at the north boundary of RMA...

  12. Stabilization of infinite dimensional port-Hamiltonian systems by nonlinear dynamic boundary control

    NARCIS (Netherlands)

    Ramirez, Hector; Zwart, Hans; Le Gorrec, Yann

    2017-01-01

    The conditions for existence of solutions and stability, asymptotic and exponential, of a large class of boundary controlled systems on a 1D spatial domain subject to nonlinear dynamic boundary actuation are given. The consideration of such class of control systems is motivated by the use of

  13. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems

    CERN Document Server

    Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

    2016-01-01

    This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

  14. A computer aided treatment event recognition system in radiation therapy

    International Nuclear Information System (INIS)

    Xia, Junyi; Mart, Christopher; Bayouth, John

    2014-01-01

    Purpose: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. Methods: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012–November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors’ clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. Results: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when

  15. An enhanced iris recognition and authentication system using ...

    African Journals Online (AJOL)

    Iris recognition and authentication has a major issue in its code generation and verification accuracy, in order to enhance the authentication process, a binary bit sequence of iris is generated, which contain several vital information that is used to calculate the Mean Energy and Maximum Energy that goes into the eye with an ...

  16. A simple and efficient optical character recognition system for basic ...

    Indian Academy of Sciences (India)

    using Principal component analysis and later classified by Support Vector Machine. 3. Kannada script. Kannada is one of the four popular Dravidian languages of South India. ..... Hu M-K 1962 Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory. IT-8: 179–187. Jawahar C V, Pavan Kumar, Ravi Kiran S S ...

  17. A novel handwritten character recognition system using gradient ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... In this paper, we propose a novel hand written character recognition systemusing a combination of gradient-based features and run length count (GBF–RLC). The performance of the proposed method has been tested on Malayalam script, a South Indian language. The gradient of image is the intensity at ...

  18. Speaker-Adaptation for Hybrid HMM-ANN Continuous Speech Recognition System

    OpenAIRE

    Neto, Joao; Almeida, Luis; Hochberg, Mike; Martins, Ciro; Nunes, Luis; Renals, Steve; Robinson, Tony

    1995-01-01

    It is well known that recognition performance degrades significantly when moving from a speaker-dependent to a speaker-independent system. Traditional hidden Markov model (HMM) systems have successfully applied speaker-adaptation approaches to reduce this degradation. In this paper we present and evaluate some techniques for speaker-adaptation of a hybrid HMM-artificial neural network (ANN) continuous speech recognition system. These techniques are applied to a well trained, speaker-independe...

  19. Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

    Science.gov (United States)

    He, Yuning; Davies, Misty Dawn

    2014-01-01

    The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

  20. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2018-04-01

    Full Text Available Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD method for an iris recognition system (iPAD using a near infrared light (NIR camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED. Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM. Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

  1. Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

    Science.gov (United States)

    Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

    2014-09-01

    Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

  2. Korean anaphora recognition system to develop healthcare dialogue-type agent.

    Science.gov (United States)

    Yang, Junggi; Lee, Youngho

    2014-10-01

    Anaphora recognition is a process to identify exactly which noun has been used previously and relates to a pronoun that is included in a specific sentence later. Therefore, anaphora recognition is an essential element of a dialogue agent system. In the current study, all the merits of rule-based, machine learning-based, semantic-based anaphora recognition systems were combined to design and realize a new hybrid-type anaphora recognition system with an optimum capacity. Anaphora recognition rules were encoded on the basis of the internal traits of referred expressions and adjacent contexts to realize a rule-based system and to serve as a baseline. A semantic database, related to predicate instances of sentences including referred expressions, was constructed to identify semantic co-relationships between the referent candidates (to which semantic tags were attached) and the semantic information of predicates. This approach would upgrade the anaphora recognition system by reducing the number of referent candidates. Additionally, to realize a machine learning-based system, an anaphora recognition model was developed on the basis of training data, which indicated referred expressions and referents. The three methods were further combined to develop a new single hybrid-based anaphora recognition system. The precision rate of the rule-based systems was 54.9%. However, the precision rate of the hybrid-based system was 63.7%, proving it to be the most efficient method. The hybrid-based method, developed by the combination of rule-based and machine learning-based methods, represents a new system with enhanced functional capabilities as compared to other pre-existing individual methods.

  3. Boundary entropy of one-dimensional quantum systems at low temperature

    International Nuclear Information System (INIS)

    Friedan, Daniel; Konechny, Anatoly

    2004-01-01

    The boundary β function generates the renormalization group acting on the universality classes of one-dimensional quantum systems with boundary which are critical in the bulk but not critical at the boundary. We prove a gradient formula for the boundary β function, expressing it as the gradient of the boundary entropy s at fixed nonzero temperature. The gradient formula implies that s decreases under renormalization, except at critical points (where it stays constant). At a critical point, the number exp(s) is the 'ground-state degeneracy', g, of Affleck and Ludwig, so we have proved their long-standing conjecture that g decreases under renormalization, from critical point to critical point. The gradient formula also implies that s decreases with temperature, except at critical points, where it is independent of temperature. It remains open whether the boundary entropy is always bounded below

  4. Morse code recognition system with fuzzy algorithm for disabled persons.

    Science.gov (United States)

    Wu, C-M; Luo, C-H

    2002-01-01

    It is generally known that Morse code is an efficient input method for one or two switches and it is made from long and short sounds separated by silence between the sounds. The long-to-short ratio in the definition is always 3 to 1, but the long-to-short ratio variation for a disabled person is so large that it is difficult to recognize. In the last few years, several Morse code recognition methods have been successfully built on the LMS adaptive algorithms and neural network algorithm. But LMS-related adaptive algorithms need mass computation to infer the characteristic of the controller; also the neural network must learn first, by inputting some data before it is used to recognize the Morse code sequence. In this study, two fuzzy algorithms are used to recognize the unstable Morse code sequences and the result demonstrates a significant improvement of recognition for real time signal processing in a single-chip microprocessor.

  5. Voice Activity Detection. Fundamentals and Speech Recognition System Robustness

    OpenAIRE

    Ramirez, J.; Gorriz, J. M.; Segura, J. C.

    2007-01-01

    This chapter has shown an overview of the main challenges in robust speech detection and a review of the state of the art and applications. VADs are frequently used in a number of applications including speech coding, speech enhancement and speech recognition. A precise VAD extracts a set of discriminative speech features from the noisy speech and formulates the decision in terms of well defined rule. The chapter has summarized three robust VAD methods that yield high speech/non-speech discri...

  6. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  7. Boundary driven phase transitions of the first order for systems of conservation laws

    Science.gov (United States)

    Popkov, Vladislav

    2007-07-01

    We argue that a driven system with two particle species and hardcore interactions generically undergoes at least two different types of boundary-driven first-order phase transitions. One observes them in succession, bringing the system from a state with a small density of right-movers to a fully jammed state, by keeping one boundary fixed and changing gradually conditions at the other boundary. As in one-component systems, the phase transitions are caused by shock motion. Monte Carlo simulations and PDEs numerical integration of a specific model serve as an example.

  8. Molecular recognition at methyl methacrylate/n-butyl acrylate (MMA/nBA) monomer unit boundaries of phospholipids at p-MMA/nBA copolymer surfaces.

    Science.gov (United States)

    Yu, Min; Urban, Marek W; Sheng, Yinghong; Leszczynski, Jerzy

    2008-09-16

    Lipid structural features and their interactions with proteins provide a useful vehicle for further advances in membrane proteins research. To mimic one of potential lipid-protein interactions we synthesized poly(methyl methacrylate/ n-butyl acrylate) (p-MMA/nBA) colloidal particles that were stabilized by phospholipid (PLs). Upon the particle coalescence, PL stratification resulted in the formation of surface localized ionic clusters (SLICs). These entities are capable of recognizing MMA/nBA monomer interfaces along the p-MMA/nBA copolymer backbone and form crystalline SLICs at the monomer interface. By utilizing attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy and selected area electron diffraction (SAD) combined with ab initio calculations, studies were conducted that identified the origin of SLICs as well as their structural features formed on the surface of p-MMA/nBA copolymer films stabilized by 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC) PL. Specific entities responsible for SLIC formation are selective noncovalent bonds of anionic phosphate and cationic quaternary ammonium segments of DLPC that interact with two neighboring carbonyl groups of nBA and MMA monomers of the p-MMA/nBA polymer backbone. To the best of our knowledge this is the first example of molecular recognition facilitated by coalescence of copolymer colloidal particles and the ability of PLs to form SLICs at the boundaries of the neighboring MMA and nBA monomer units of the p-MMA/nBA chain. The dominating noncovalent bonds responsible for the molecular recognition is a combination of H-bonding and electrostatic interactions.

  9. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  10. Multi-agent Systems for Arabic Handwriting Recognition

    Directory of Open Access Journals (Sweden)

    Youssef Boulid

    2017-12-01

    Full Text Available This paper aims to give a presentation of the PhD defended by Boulid Youssef on December 26th, 2016 at University Ibn Tofail, entitled “Arabic handwritten recognition in an offline mode”. The adopted approach is realized under the multi agent paradigm. The dissertation was held in Faculty of Science Kénitra in a publicly open presentation. After the presentation, Boulid was awarded with the highest grade (Très honorable avec félicitations de jury.

  11. Named Entity Recognition in a Hungarian NL Based QA System

    Science.gov (United States)

    Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

    In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

  12. Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

    Directory of Open Access Journals (Sweden)

    Slobodan Beroš

    2012-10-01

    Full Text Available The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.

  13. Container code recognition in information auto collection system of container inspection

    International Nuclear Information System (INIS)

    Su Jianping; Chen Zhiqiang; Zhang Li; Gao Wenhuan; Kang Kejun

    2003-01-01

    Now custom needs electrical application and automatic detection. Container inspection should not only give the image of the goods, but also auto-attain container's code and weight. Its function and track control, information transfer make up the Information Auto Collection system of Container Inspection. Code Recognition is the point. The article is based on model match, the close property of character, and uses it to recognize. Base on checkout rule, design the adjustment arithmetic, form the whole recognition strategy. This strategy can achieve high recognition ratio and robust property

  14. Man-system interface based on automatic speech recognition: integration to a virtual control desk

    International Nuclear Information System (INIS)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C.; Nomiya, Diogo V.

    2009-01-01

    This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

  15. Man-system interface based on automatic speech recognition: integration to a virtual control desk

    Energy Technology Data Exchange (ETDEWEB)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b, E-mail: cmnap@ien.gov.b, E-mail: mag@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Nomiya, Diogo V., E-mail: diogonomiya@gmail.co [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

    2009-07-01

    This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

  16. FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Pasupathi

    2014-05-01

    Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

  17. Agriculture production as a major driver of the Earth system exceeding planetary boundaries

    Directory of Open Access Journals (Sweden)

    Bruce M. Campbell

    2017-12-01

    Full Text Available We explore the role of agriculture in destabilizing the Earth system at the planetary scale, through examining nine planetary boundaries, or "safe limits": land-system change, freshwater use, biogeochemical flows, biosphere integrity, climate change, ocean acidification, stratospheric ozone depletion, atmospheric aerosol loading, and introduction of novel entities. Two planetary boundaries have been fully transgressed, i.e., are at high risk, biosphere integrity and biogeochemical flows, and agriculture has been the major driver of the transgression. Three are in a zone of uncertainty i.e., at increasing risk, with agriculture the major driver of two of those, land-system change and freshwater use, and a significant contributor to the third, climate change. Agriculture is also a significant or major contributor to change for many of those planetary boundaries still in the safe zone. To reduce the role of agriculture in transgressing planetary boundaries, many interventions will be needed, including those in broader food systems.

  18. Integrable systems on so(4) related to XXX spin chains with boundaries

    International Nuclear Information System (INIS)

    Tsiganov, A V; Goremykin, O V

    2004-01-01

    We consider two-site XXX Heisenberg magnets with different boundary conditions, which are integrable systems on so(4) possessing additional cubic and quartic integrals of motion. The separated variables for these models are constructed using the Sklyanin method

  19. SYSTEM DESIGN AND BEHAVIOR OF PATTERN RECOGNITION OF CONTROL CHART USING NEURAL NETWORK

    OpenAIRE

    Justin Yulius Halim

    2003-01-01

    Recognition of unnatural patterns in control charts is important to get more understanding about the process problem. Shewhart control chart can recognize shift pattern only, while the others cannot be detected by this chart. Neural networks were proposed by many researchers to achieve the better recognition of the patterns. A system of neural networks needs to be fitted to this problem by realizing the behaviors of control charts. Each behavior will affect the development of each part of the...

  20. Hand gesture recognition system based in computer vision and machine learning

    OpenAIRE

    Trigueiros, Paulo; Ribeiro, António Fernando; Reis, L. P.

    2015-01-01

    "Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19" Hand gesture recognition is a natural way of human computer interaction and an area of very active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Hum...

  1. Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras.

    Science.gov (United States)

    Nguyen, Dat Tien; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung

    2017-03-16

    The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel in the following three ways compared to previous studies. First, we use the images of human body for recognizing individuals. To overcome the limitations of previous studies on body-based person recognition that use only visible light images for recognition, we use human body images captured by two different kinds of camera, including a visible light camera and a thermal camera. The use of two different kinds of body image helps us to reduce the effects of noise, background, and variation in the appearance of a human body. Second, we apply a state-of-the art method, called convolutional neural network (CNN) among various available methods, for image features extraction in order to overcome the limitations of traditional hand-designed image feature extraction methods. Finally, with the extracted image features from body images, the recognition task is performed by measuring the distance between the input and enrolled samples. The experimental results show that the proposed method is efficient for enhancing recognition accuracy compared to systems that use only visible light or thermal images of the human body.

  2. Tracking "Large" or "Smal": Boundaries and their Consequences for Veterinary Students within the Tracking System

    Science.gov (United States)

    Vermilya, Jenny R.

    In this dissertation, I use 42 in-depth qualitative interviews with veterinary medical students to explore the experience of being in an educational program that tracks students based on the species of non-human animals that they wish to treat. Specifically, I examine how tracking produces multiple boundaries for veterinary students. The boundaries between different animal species produce consequences for the treatment of those animals; this has been well documented. Using a symbolic interactionist perspective, my research extends the body of knowledge on species boundaries by revealing other consequences of this boundary work. For example, I analyze the symbolic boundaries involved in the gendering of animals, practitioners, and professions. I also examine how boundaries influence the collective identity of students entering an occupation segmented into various specialties. The collective identity of veterinarian is one characterized by care, thus students have to construct different definitions of care to access and maintain the collective identity. The tracking system additionally produces consequences for the knowledge created and reproduced in different areas of animal medicine, creating a system of power and inequality based on whose knowledge is privileged, how, and why. Finally, socially constructed boundaries generated from tracking inevitably lead to cases that do not fit. In particular, horses serve as a "border species" for veterinary students who struggle to place them into the tracking system. I argue that border species, like other metaphorical borders, have the potential to challenge discourses and lead to social change.

  3. A Novel Optical/digital Processing System for Pattern Recognition

    Science.gov (United States)

    Boone, Bradley G.; Shukla, Oodaye B.

    1993-01-01

    This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

  4. Spoof Detection for Finger-Vein Recognition System Using NIR Camera

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-10-01

    Full Text Available Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD, is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor based on the observations of the researchers about the difference between real (live and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR camera-based finger-vein recognition system using convolutional neural network (CNN to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA for dimensionality reduction of feature space and support vector machine (SVM for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared

  5. Spoof Detection for Finger-Vein Recognition System Using NIR Camera

    Science.gov (United States)

    Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

    2017-01-01

    Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN

  6. Automated alignment system for optical wireless communication systems using image recognition.

    Science.gov (United States)

    Brandl, Paul; Weiss, Alexander; Zimmermann, Horst

    2014-07-01

    In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate <10⁻⁹) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s.

  7. From Birdsong to Human Speech Recognition: Bayesian Inference on a Hierarchy of Nonlinear Dynamical Systems

    Science.gov (United States)

    Yildiz, Izzet B.; von Kriegstein, Katharina; Kiebel, Stefan J.

    2013-01-01

    Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents—an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments. PMID:24068902

  8. From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

    Directory of Open Access Journals (Sweden)

    Izzet B Yildiz

    Full Text Available Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

  9. Recognition of a Phase-Sensitivity OTDR Sensing System Based on Morphologic Feature Extraction.

    Science.gov (United States)

    Sun, Qian; Feng, Hao; Yan, Xueying; Zeng, Zhoumo

    2015-06-29

    This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and may lead to inaccuracies due to noise disturbances. The recognition accuracy and speed of current systems cannot meet the requirements of Φ-OTDR online vibration monitoring systems. In the method proposed in this paper, the time-space domain signal is used for feature extraction instead of the time domain signal. Feature vectors are obtained from morphologic features of time-space domain signals. A scatter matrix is calculated for the feature selection. Experiments show that the feature extraction method proposed in this paper can greatly improve recognition accuracies, with a lower computation time than traditional methods, i.e., a recognition accuracy of 97.8% can be achieved with a recognition time of below 1 s, making it is very suitable for Φ-OTDR system online vibration monitoring.

  10. Parametric integral equations system in elasticity problems with uncertainly defined shape of the boundary

    Science.gov (United States)

    Zieniuk, Eugeniusz; Kapturczak, Marta

    2017-07-01

    In recent studies of parametric integral equations system (PIES), the input data, necessary to define the shape of boundary, was defined in precise way. However, it is just assumption for further calculations. In practice even the most accurate measurement instruments generate errors. Therefore, in this paper we decide to propose the method for modelling and solving the boundary value problems with uncertainly defined shape of boundary. In view of advantages in precisely defined problems, we decide to generalize PIES method. To define the uncertainty of the input data we propose the modification of directed interval arithmetic.

  11. Analytic approximations to nonlinear boundary value problems modeling beam-type nano-electromechanical systems

    Energy Technology Data Exchange (ETDEWEB)

    Zou, Li [Dalian Univ. of Technology, Dalian City (China). State Key Lab. of Structural Analysis for Industrial Equipment; Liang, Songxin; Li, Yawei [Dalian Univ. of Technology, Dalian City (China). School of Mathematical Sciences; Jeffrey, David J. [Univ. of Western Ontario, London (Canada). Dept. of Applied Mathematics

    2017-06-01

    Nonlinear boundary value problems arise frequently in physical and mechanical sciences. An effective analytic approach with two parameters is first proposed for solving nonlinear boundary value problems. It is demonstrated that solutions given by the two-parameter method are more accurate than solutions given by the Adomian decomposition method (ADM). It is further demonstrated that solutions given by the ADM can also be recovered from the solutions given by the two-parameter method. The effectiveness of this method is demonstrated by solving some nonlinear boundary value problems modeling beam-type nano-electromechanical systems.

  12. Global existence and blowup for free boundary problems of coupled reaction-diffusion systems

    Directory of Open Access Journals (Sweden)

    Jianping Sun

    2014-05-01

    Full Text Available This article concerns a free boundary problem for a reaction-diffusion system modeling the cooperative interaction of two diffusion biological species in one space dimension. First we show the existence and uniqueness of a local classical solution, then we study the asymptotic behavior of the free boundary problem. Our results show that the free boundary problem admits a global solution if the inter-specific competitions are strong, while, if the inter-specific competitions are weak, there exist the blowup solution and a global fast solution.

  13. An Evolutionary Approach to Driving Tendency Recognition for Advanced Driver Assistance Systems

    Directory of Open Access Journals (Sweden)

    Lee Jong-Hyun

    2016-01-01

    Full Text Available Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS. However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning method using evolutionary computation. We propose a driving tendency recognition method, with consideration of data characteristics. Comparison of our classification system with conventional methods demonstrated the effectiveness and accuracy over 92% in our system. Our proposed evolutionary approach is confirmed that improve the classification accuracy of the learning method through evolution in the experiment.

  14. Scaling of localization length of a quasi 1D system with longitudinal boundary roughness

    International Nuclear Information System (INIS)

    Abhijit Kar Gupta; Sen, A.K.

    1994-08-01

    We introduce irregularities on one of the longitudinal boundaries of a quasi 1D strip which has no bulk disorder. We calculate the localization length of such a system within the scope of tight-binding formalism and see how it behaves with the roughness introduced on the boundary and with the strip-width. We find that localization length scales with a composite one parameter. (author). 6 refs, 4 figs

  15. Framework to Define Structure and Boundaries of Complex Health Intervention Systems: The ALERT Project

    DEFF Research Database (Denmark)

    Boriani, Elena; Esposito, Roberto; Frazzoli, Chiara

    2017-01-01

    with carefully defined system boundaries. Exploring individual components of such systems from different viewpoints gives a wide overview and helps to understand the elements and the relationships that drive actions and consequences within the system. In this study, we present an application and assessment...

  16. Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

    Science.gov (United States)

    Gao, Lei; Bourke, A K; Nelson, John

    2014-06-01

    Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high

  17. Numerical solution of system of boundary value problems using B-spline with free parameter

    Science.gov (United States)

    Gupta, Yogesh

    2017-01-01

    This paper deals with method of B-spline solution for a system of boundary value problems. The differential equations are useful in various fields of science and engineering. Some interesting real life problems involve more than one unknown function. These result in system of simultaneous differential equations. Such systems have been applied to many problems in mathematics, physics, engineering etc. In present paper, B-spline and B-spline with free parameter methods for the solution of a linear system of second-order boundary value problems are presented. The methods utilize the values of cubic B-spline and its derivatives at nodal points together with the equations of the given system and boundary conditions, ensuing into the linear matrix equation.

  18. A Computer-Based Gaming System for Assessing Recognition Performance (RECOG).

    Science.gov (United States)

    Little, Glenn A.; And Others

    This report documents a computer-based gaming system for assessing recognition performance (RECOG). The game management system is programmed in a modular manner to: instruct the student on how to play the game, retrieve and display individual images, keep track of how well individuals play and provide them feedback, and link these components by…

  19. A Freely-Available Authoring System for Browser-Based CALL with Speech Recognition

    Science.gov (United States)

    O'Brien, Myles

    2017-01-01

    A system for authoring browser-based CALL material incorporating Google speech recognition has been developed and made freely available for download. The system provides a teacher with a simple way to set up CALL material, including an optional image, sound or video, which will elicit spoken (and/or typed) answers from the user and check them…

  20. A single-system model predicts recognition memory and repetition priming in amnesia

    NARCIS (Netherlands)

    Berry, C.J.; Kessels, R.P.C.; Wester, A.J.; Shanks, D.R.

    2014-01-01

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with

  1. Unstable Morse Code recognition system with back propagation neural network for person with disabilities.

    Science.gov (United States)

    Fuh, D T; Luo, C H

    2001-01-01

    A Morse code auto-recognition system is limited by stable typing speed and stable typing ratio from long to short intervals. For an unstable Morse code typing pattern, the auto-recognition algorithms in the literature are not good enough for applications. This paper adopted a neural network to recognize unstable Morse codes. From an experiment on a teenager with cerebral palsy, the neural network has an average recognition rate up to 93.2%. The recognition rate from an amputee aged 40, who used a prosthesis for typing, it is 97.2% on average. When we compare this to 99.2% for the recognition rate from a skilled expert, the result is quite promising. The neural network has successfully overcome the difficulty of analysing a severely unstable Morse code time series. Since the human typing speed is quite slow in comparison to signal processing by the computer, it also makes it possible to use a neural network for real-time signal recognition.

  2. Speech Recognition

    Directory of Open Access Journals (Sweden)

    Adrian Morariu

    2009-01-01

    Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

  3. Body posture recognition and turning recording system for the care of bed bound patients.

    Science.gov (United States)

    Hsiao, Rong-Shue; Mi, Zhenqiang; Yang, Bo-Ru; Kau, Lih-Jen; Bitew, Mekuanint Agegnehu; Li, Tzu-Yu

    2015-01-01

    This paper proposes body posture recognition and turning recording system for assisting the care of bed bound patients in nursing homes. The system continuously detects the patient's body posture and records the length of time for each body posture. If the patient remains in the same body posture long enough to develop pressure ulcers, the system notifies caregivers to change the patient's body posture. The objective of recording is to provide the log of body turning for querying of patients' family members. In order to accurately detect patient's body posture, we developed a novel pressure sensing pad which contains force sensing resistor sensors. Based on the proposed pressure sensing pad, we developed a bed posture recognition module which includes a bed posture recognition algorithm. The algorithm is based on fuzzy theory. The body posture recognition algorithm can detect the patient's bed posture whether it is right lateral decubitus, left lateral decubitus, or supine. The detected information of patient's body posture can be then transmitted to the server of healthcare center by the communication module to perform the functions of recording and notification. Experimental results showed that the average posture recognition accuracy for our proposed module is 92%.

  4. A single-system model predicts recognition memory and repetition priming in amnesia.

    Science.gov (United States)

    Berry, Christopher J; Kessels, Roy P C; Wester, Arie J; Shanks, David R

    2014-08-13

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. Copyright © 2014 the authors 0270-6474/14/3410963-12$15.00/0.

  5. SYSTEM DESIGN AND BEHAVIOR OF PATTERN RECOGNITION OF CONTROL CHART USING NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Justin Yulius Halim

    2003-01-01

    Full Text Available Recognition of unnatural patterns in control charts is important to get more understanding about the process problem. Shewhart control chart can recognize shift pattern only, while the others cannot be detected by this chart. Neural networks were proposed by many researchers to achieve the better recognition of the patterns. A system of neural networks needs to be fitted to this problem by realizing the behaviors of control charts. Each behavior will affect the development of each part of the system. Some problem need to be pointed also when dealing with the patterns of the control chart.

  6. A smart pattern recognition system for the automatic identification of aerospace acoustic sources

    Science.gov (United States)

    Cabell, R. H.; Fuller, C. R.

    1989-01-01

    An intelligent air-noise recognition system is described that uses pattern recognition techniques to distinguish noise signatures of five different types of acoustic sources, including jet planes, propeller planes, a helicopter, train, and wind turbine. Information for classification is calculated using the power spectral density and autocorrelation taken from the output of a single microphone. Using this system, as many as 90 percent of test recordings were correctly identified, indicating that the linear discriminant functions developed can be used for aerospace source identification.

  7. FCaZm intelligent recognition system for locating areas prone to strong earthquakes in the Andean and Caucasian mountain belts

    Science.gov (United States)

    Gvishiani, A. D.; Dzeboev, B. A.; Agayan, S. M.

    2016-07-01

    The fuzzy clustering and zoning method (FCAZm) of systems analysis is suggested for recognizing the areas of the probable generation of the epicenters of significant, strong, and the strongest earthquakes. FCAZm is a modified version of the previous FCAZ algorithmic system, which is advanced by the creation of the blocks of artificial intelligence that develop the system-forming algorithms. FCAZm has been applied for recognizing areas where the epicenters of the strongest ( M ≥ 73/4) earthquakes within the Andes mountain belt in the South America and significant earthquakes ( M ≥ 5) in the Caucasus can emerge. The reliability of the obtained results was assessed by the seismic-history type control experiments. The recognized highly seismic zones were compared with the ones previously recognized by the EPA method and by the initial version of the FCAZ system. The modified FCAZm system enabled us to pass from simple pattern recognition in the problem of recognizing the locations of the probable emergence of strong earthquakes to systems analysis. In particular, using FCAZm we managed to uniquely recognize a subsystem of highly seismically active zones from the nonempty complement using the exact boundary.

  8. Development of remote handling system based on 3-D shape recognition technique

    International Nuclear Information System (INIS)

    Tomizuka, Chiaki; Takeuchi, Yutaka

    2006-01-01

    In a nuclear facility, the maintenance and repair activities must be done remotely in a radioactive environment. Fuji Electric Systems Co., Ltd. has developed a remote handling system based on 3-D recognition technique. The system recognizes the pose and position of the target to manipulate, and visualizes the scene with the target in 3-D, enabling an operator to handle it easily. This paper introduces the concept and the key features of this system. (author)

  9. The nuclear fuel rod character recognition system based on neural network technique

    International Nuclear Information System (INIS)

    Kim, Woong-Ki; Park, Soon-Yong; Lee, Yong-Bum; Kim, Seung-Ho; Lee, Jong-Min; Chien, Sung-Il.

    1994-01-01

    The nuclear fuel rods should be discriminated and managed systematically by numeric characters which are printed at the end part of each rod in the process of producing fuel assembly. The characters are used to examine manufacturing process of the fuel rods in the inspection process of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies to establish automatic manufacturing process of fuel assembly. In the developed character recognition system, mesh feature set extracted from each character written in the fuel rod is employed to train a neural network based on back-propagation algorithm as a classifier for character recognition system. Performance evaluation has been achieved on a test set which is not included in a training character set. (author)

  10. A Dental Radiograph Recognition System Using Phase-Only Correlation for Human Identification

    Science.gov (United States)

    Ito, Koichi; Nikaido, Akira; Aoki, Takafumi; Kosuge, Eiko; Kawamata, Ryota; Kashima, Isamu

    In mass disasters such as earthquakes, fire disasters, tsunami, and terrorism, dental records have been used for identifying victims due to their processing time and accuracy. The greater the number of victims, the more time the identification tasks require, since a manual comparison between the dental radiograph records is done by forensic experts. Addressing this problem, this paper presents an efficient dental radiograph recognition system using Phase-Only Correlation (POC) for human identification. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of dental radiograph images makes possible to achieve highly robust image registration and recognition. Experimental evaluation using a set of dental radiographs indicates that the proposed system exhibits efficient recognition performance for low-quality images.

  11. Robot Command Interface Using an Audio-Visual Speech Recognition System

    Science.gov (United States)

    Ceballos, Alexánder; Gómez, Juan; Prieto, Flavio; Redarce, Tanneguy

    In recent years audio-visual speech recognition has emerged as an active field of research thanks to advances in pattern recognition, signal processing and machine vision. Its ultimate goal is to allow human-computer communication using voice, taking into account the visual information contained in the audio-visual speech signal. This document presents a command's automatic recognition system using audio-visual information. The system is expected to control the laparoscopic robot da Vinci. The audio signal is treated using the Mel Frequency Cepstral Coefficients parametrization method. Besides, features based on the points that define the mouth's outer contour according to the MPEG-4 standard are used in order to extract the visual speech information.

  12. A Biometric Face Recognition System Using an Algorithm Based on the Principal Component Analysis Technique

    Directory of Open Access Journals (Sweden)

    Gheorghe Gîlcă

    2015-06-01

    Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.

  13. Enrollment Time as a Requirement for Biometric Hand Recognition Systems

    OpenAIRE

    Carvalho, João; Sá, Vítor; Tenreiro de Magalhães, Sérgio; Santos, Henrique

    2015-01-01

    Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in...

  14. Boundaries of the homologous phases in Sb–Te and Bi–Te binary alloy systems

    Energy Technology Data Exchange (ETDEWEB)

    Kifune, K., E-mail: k.kifune.yw@cc.it-hiroshima.ac.jp [Hiroshima Institute of Technology, Research Center for Condensed Matter Physics, 2-1-1 Miyake, Saeki-ku, Hiroshima 731-5193 (Japan); Tachizawa, T.; Kanaya, H.; Kubota, Y. [Osaka Prefecture University, Graduate School of Science, Osaka 599-8531 (Japan); Yamada, N. [Kyoto University, Department of Materials Science & Engineering, Kyoto 606-8501 (Japan); Matsunaga, T. [Panasonic Corporation, Advanced Research Division, Osaka 571-8501 (Japan)

    2015-10-05

    Highlights: • Phase boundary of the homologous phase in Sb–Te is fixed at Sb{sub 20}Te{sub 3} compound. • Crystal structure of Sb{sub 20}Te{sub 3} is refined by the 4D structure analysis. • Phase boundary of the homologous phase in Bi–Te is fixed at Bi{sub 8}Te{sub 3} compound. • Crystal structure of Bi{sub 8}Te{sub 3} is refined by the 4D structure analysis. • Difference between Sb–Te and Bi–Te systems are proposed. - Abstract: Sb–Te and Bi–Te binary systems have long-period stacking structures called homologous phases. Within these structures, two types of fundamental structural units change their numbers according to their composition, and the stacking periods also change systematically. X-ray powder diffraction data on bulk specimens with different compositions reveal both the phase boundaries of the homologous phases and the structures of the boundary phases. The boundary phases are Sb{sub 20}Te{sub 3} in the Sb–Te system and Bi{sub 8}Te{sub 3} in the Bi–Te system.

  15. Quasilinearization for the periodic boundary value problem for systems of impulsive differential equations

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available The method of generalized quasilinearization for the system of nonlinear impulsive differential equations with periodic boundary conditions is studied. As a byproduct, the result for the system without impulses can be obtained, which is a new result as well.

  16. A laser Doppler system for the remote sensing of boundary layer winds in clear air conditions

    Science.gov (United States)

    Lawrence, T. R.; Krause, M. C.; Craven, C. E.; Morrison, L. K.; Thomson, J. A. L.; Cliff, W. C.; Huffaker, R. M.

    1975-01-01

    The system discussed uses a laser Doppler radar in combination with a velocity azimuth display mode of scanning to determine the three-dimensional wind field in the atmospheric boundary layer. An attractive feature of this CW monostatic system is that the ambient aerosol provides a 'sufficient' scattering target to permit operation under clear air conditions. Spatial resolution is achieved by focusing.

  17. Heat kernel for the elliptic system of linear elasticity with boundary conditions

    Science.gov (United States)

    Taylor, Justin; Kim, Seick; Brown, Russell

    2014-10-01

    We consider the elliptic system of linear elasticity with bounded measurable coefficients in a domain where the second Korn inequality holds. We construct heat kernel of the system subject to Dirichlet, Neumann, or mixed boundary condition under the assumption that weak solutions of the elliptic system are Hölder continuous in the interior. Moreover, we show that if weak solutions of the mixed problem are Hölder continuous up to the boundary, then the corresponding heat kernel has a Gaussian bound. In particular, if the domain is a two dimensional Lipschitz domain satisfying a corkscrew or non-tangential accessibility condition on the set where we specify Dirichlet boundary condition, then we show that the heat kernel has a Gaussian bound. As an application, we construct Green's function for elliptic mixed problem in such a domain.

  18. Neuro-parity pattern recognition system and method

    Science.gov (United States)

    Gross, Kenneth C.; Singer, Ralph M.; Van Alstine, Rollin G.; Wegerich, Stephan W.; Yue, Yong

    2000-01-01

    A method and system for monitoring a process and determining its condition. Initial data is sensed, a first set of virtual data is produced by applying a system state analyzation to the initial data, a second set of virtual data is produced by applying a neural network analyzation to the initial data and a parity space analyzation is applied to the first and second set of virtual data and also to the initial data to provide a parity space decision about the condition of the process. A logic test can further be applied to produce a further system decision about the state of the process.

  19. Data management in pattern recognition and image processing systems

    Science.gov (United States)

    Zobrist, A. L.; Bryant, N. A.

    1976-01-01

    Data management considerations are important to any system which handles large volumes of data or where the manipulation of data is technically sophisticated. A particular problem is the introduction of image-formatted files into the mainstream of data processing application. This report describes a comprehensive system for the manipulation of image, tabular, and graphical data sets which involve conversions between the various data types. A key characteristic is the use of image processing technology to accomplish data management tasks. Because of this, the term 'image-based information system' has been adopted.

  20. Automated Mulitple Object Optical Tracking and Recognition System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  1. Automated Mulitple Object Optical Tracking and Recognition System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  2. Developing a broadband automatic speech recognition system for Afrikaans

    CSIR Research Space (South Africa)

    De Wet, Febe

    2011-08-01

    Full Text Available for Afrikaans, specifically a broadband speech corpus and an extended pronunciation dictionary. Baseline results for an ASR system that was built using these resources are also presented. In addition, the article suggests different strategies to exploit...

  3. A heart disease recognition embedded system with fuzzy cluster algorithm.

    Science.gov (United States)

    de Carvalho, Helton Hugo; Moreno, Robson Luiz; Pimenta, Tales Cleber; Crepaldi, Paulo C; Cintra, Evaldo

    2013-06-01

    This article presents the viability analysis and the development of heart disease identification embedded system. It offers a time reduction on electrocardiogram - ECG signal processing by reducing the amount of data samples, without any significant loss. The goal of the developed system is the analysis of heart signals. The ECG signals are applied into the system that performs an initial filtering, and then uses a Gustafson-Kessel fuzzy clustering algorithm for the signal classification and correlation. The classification indicated common heart diseases such as angina, myocardial infarction and coronary artery diseases. The system uses the European electrocardiogram ST-T Database (EDB) as a reference for tests and evaluation. The results prove the system can perform the heart disease detection on a data set reduced from 213 to just 20 samples, thus providing a reduction to just 9.4% of the original set, while maintaining the same effectiveness. This system is validated in a Xilinx Spartan(®)-3A FPGA. The field programmable gate array (FPGA) implemented a Xilinx Microblaze(®) Soft-Core Processor running at a 50MHz clock rate. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  4. On the System. Boundary Choices, Implications, and Solutions in Telecoupling Land Use Change Research

    Directory of Open Access Journals (Sweden)

    Cecilie Friis

    2017-06-01

    Full Text Available Land-based production provides societies with indispensable goods such as food, feed, fibre, and energy. Yet, with economic globalisation and global population growth, the environmental and social trade-offs of their production are ever more complex. This is particularly so since land use changes are increasingly embedded in networks of long-distance flows of, e.g., material, energy, and information. The resulting scientific and governance challenge is captured in the emerging telecoupling framework addressing socioeconomic and environmental interactions and feedbacks between distal human-environment systems. Understanding telecouplings, however, entails a number of fundamental analytical problems. When dealing with global connectivity, a central question is how and where to draw system boundaries between coupled systems. In this article, we explore the analytical implications of setting system boundaries in the study of a recent telecoupled land use change: the expansion of Chinese banana plantation investments in Luang Namtha Province, Laos. Based on empirical material from fieldwork in Laos in 2014 and 2015, and drawing on key concepts from the ‘systems thinking’ literature, we illustrate how treating the system and its boundaries as epistemological constructs enable us to capture the differentiated involvement of actors, as well as the socio-economic and environmental effects of this land use change. In discussing our results, the need for more explicit attention to the trade-offs and implications of scale and boundary choices when defining systems is emphasised.

  5. USE OF FACIAL EMOTION RECOGNITION IN E-LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Uğur Ayvaz

    2017-09-01

    Full Text Available Since the personal computer usage and internet bandwidth are increasing, e-learning systems are also widely spreading. Although e-learning has some advantages in terms of information accessibility, time and place flexibility compared to the formal learning, it does not provide enough face-to-face interactivity between an educator and learners. In this study, we are proposing a hybrid information system, which is combining computer vision and machine learning technologies for visual and interactive e-learning systems. The proposed information system detects emotional states of the learners and gives feedback to an educator about their instant and weighted emotional states based on facial expressions. In this way, the educator will be aware of the general emotional state of the virtual classroom and the system will create a formal learning-like interactive environment. Herein, several classification algorithms were applied to learn instant emotional state and the best accuracy rates were obtained using kNN and SVM algorithms.

  6. A Cross-Layer Biometric Recognition System for Mobile IoT Devices

    Directory of Open Access Journals (Sweden)

    Shayan Taheri

    2018-02-01

    Full Text Available A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.

  7. Preliminary Design of a Recognition System for Infected Fish Species Using Computer Vision

    OpenAIRE

    Hu, Jing; Li, Daoliang; Duan, Qingling; Chen, Guifen; Si, Xiuli

    2011-01-01

    Part 1: Decision Support Systems, Intelligent Systems and Artificial Intelligence Applications; International audience; For the purpose of classification of fish species, a recognition system was preliminary designed using computer vision. In the first place, pictures were pre-processed by developed programs, dividing into rectangle pieces. Secondly, color and texture features are extracted for those selected texture rectangle fish skin images. Finally, all the images were classified by multi...

  8. Identification of the Color Parameters in Pattern Recognition in Real-time Security Systems

    Directory of Open Access Journals (Sweden)

    A. N. Dronov

    2011-03-01

    Full Text Available Problems of identification of the color parameters of moving raster image objects in pattern recognition in modern security systems, which include real-time video-surveillance systems, are declared in this paper. The description of algorithms of identification of the color parameters in frames coming from real-time video streams is given. The practical application of the developed algorithms in program modules of corresponding video systems is demonstrated.

  9. DEVELOPMENT OF AUTOMATED SPEECH RECOGNITION SYSTEM FOR EGYPTIAN ARABIC PHONE CONVERSATIONS

    Directory of Open Access Journals (Sweden)

    A. N. Romanenko

    2016-07-01

    Full Text Available The paper deals with description of several speech recognition systems for the Egyptian Colloquial Arabic. The research is based on the CALLHOME Egyptian corpus. The description of both systems, classic: based on Hidden Markov and Gaussian Mixture Models, and state-of-the-art: deep neural network acoustic models is given. We have demonstrated the contribution from the usage of speaker-dependent bottleneck features; for their extraction three extractors based on neural networks were trained. For their training three datasets in several languageswere used:Russian, English and differentArabic dialects.We have studied the possibility of application of a small Modern Standard Arabic (MSA corpus to derive phonetic transcriptions. The experiments have shown that application of the extractor obtained on the basis of the Russian dataset enables to increase significantly the quality of the Arabic speech recognition. We have also stated that the usage of phonetic transcriptions based on modern standard Arabic decreases recognition quality. Nevertheless, system operation results remain applicable in practice. In addition, we have carried out the study of obtained models application for the keywords searching problem solution. The systems obtained demonstrate good results as compared to those published before. Some ways to improve speech recognition are offered.

  10. Interactions of the humoral pattern recognition molecule PTX3 with the complement system

    DEFF Research Database (Denmark)

    Doni, Andrea; Garlanda, Cecilia; Bottazzi, Barbara

    2012-01-01

    The innate immune system comprises a cellular and a humoral arm. The long pentraxin PTX3 is a fluid phase pattern recognition molecule, which acts as an essential component of the humoral arm of innate immunity. PTX3 has antibody-like properties including interactions with complement components...

  11. Representation Method of Formal Pattern Classes in Cluster Mode at Building of Recognition Systems

    OpenAIRE

    Rodchenko, V. V.; Rodchenko, V. G.; Zhukevich, A. I.

    2012-01-01

    At building of recognition systems there is a problem of formal representation of pattern classes or standard pattern classes in multidimensional feature space. In the article it is convenient to represent pattern classes in cluster mode and the original algorithm for building such clusters is described.

  12. Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

    Science.gov (United States)

    Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

    2017-03-01

    Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

  13. Predicting Performance of a Face Recognition System Based on Image Quality

    NARCIS (Netherlands)

    Dutta, A.

    2015-01-01

    In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

  14. ISOLATED SPEECH RECOGNITION SYSTEM FOR TAMIL LANGUAGE USING STATISTICAL PATTERN MATCHING AND MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    VIMALA C.

    2015-05-01

    Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

  15. Evaluating Automatic Speech Recognition-Based Language Learning Systems: A Case Study

    Science.gov (United States)

    van Doremalen, Joost; Boves, Lou; Colpaert, Jozef; Cucchiarini, Catia; Strik, Helmer

    2016-01-01

    The purpose of this research was to evaluate a prototype of an automatic speech recognition (ASR)-based language learning system that provides feedback on different aspects of speaking performance (pronunciation, morphology and syntax) to students of Dutch as a second language. We carried out usability reviews, expert reviews and user tests to…

  16. EBSD analysis of subgrain boundaries and dislocation slip systems in Antarctic and Greenland ice

    Science.gov (United States)

    Weikusat, Ilka; Kuiper, Ernst-Jan N.; Pennock, Gill M.; Kipfstuhl, Sepp; Drury, Martyn R.

    2017-09-01

    Ice has a very high plastic anisotropy with easy dislocation glide on basal planes, while glide on non-basal planes is much harder. Basal glide involves dislocations with the Burgers vector b = 〈a〉, while glide on non-basal planes can involve dislocations with b = 〈a〉, b = [c], and b = 〈c + a〉. During the natural ductile flow of polar ice sheets, most of the deformation is expected to occur by basal slip accommodated by other processes, including non-basal slip and grain boundary processes. However, the importance of different accommodating processes is controversial. The recent application of micro-diffraction analysis methods to ice, such as X-ray Laue diffraction and electron backscattered diffraction (EBSD), has demonstrated that subgrain boundaries indicative of non-basal slip are present in naturally deformed ice, although so far the available data sets are limited. In this study we present an analysis of a large number of subgrain boundaries in ice core samples from one depth level from two deep ice cores from Antarctica (EPICA-DML deep ice core at 656 m of depth) and Greenland (NEEM deep ice core at 719 m of depth). EBSD provides information for the characterization of subgrain boundary types and on the dislocations that are likely to be present along the boundary. EBSD analyses, in combination with light microscopy measurements, are presented and interpreted in terms of the dislocation slip systems. The most common subgrain boundaries are indicative of basal 〈a〉 slip with an almost equal occurrence of subgrain boundaries indicative of prism [c] or 〈c + a〉 slip on prism and/or pyramidal planes. A few subgrain boundaries are indicative of prism 〈a〉 slip or slip of 〈a〉 screw dislocations on the basal plane. In addition to these classical polygonization processes that involve the recovery of dislocations into boundaries, alternative mechanisms are discussed for the formation of subgrain boundaries that are not related to the

  17. Disability, Autonomy and Intersubjective Recognition in the Integral National Care System

    Directory of Open Access Journals (Sweden)

    Sharon Carolina Díaz Fernández

    2017-10-01

    Full Text Available This article analyzes the creation of conditions for autonomy and recognition of people in situations of dependency mediated by disability, within Uruguay’s National Integral Care System (SNIC. It analyzes the conceptualizations that take form in the institutional discursive frameworks, and in the daily experience of the subjects involved, who are interviewed (in various regions of the country where the Personal Assistance Program is implemented in pilot form. It proposes to theoretically problematize the implications of forms of recognition and potentiality of individual self-reference (self-confidence, self-respect, self-esteem for people in situations of dependency mediated by disability. It discusses if the form of implementation of the SNIC through the Personal Assistant component offers opportunities for expansion of their spaces of intersubjective recognition and autonomy.

  18. Skin Cancer Recognition by Using a Neuro-Fuzzy System

    Science.gov (United States)

    Salah, Bareqa; Alshraideh, Mohammad; Beidas, Rasha; Hayajneh, Ferial

    2011-01-01

    Skin cancer is the most prevalent cancer in the light-skinned population and it is generally caused by exposure to ultraviolet light. Early detection of skin cancer has the potential to reduce mortality and morbidity. There are many diagnostic technologies and tests to diagnose skin cancer. However many of these tests are extremely complex and subjective and depend heavily on the experience of the clinician. To obviate these problems, image processing techniques, a neural network system (NN) and a fuzzy inference system were used in this study as promising modalities for detection of different types of skin cancer. The accuracy rate of the diagnosis of skin cancer by using the hierarchal neural network was 90.67% while using neuro-fuzzy system yielded a slightly higher rate of accuracy of 91.26% in diagnosis skin cancer type. The sensitivity of NN in diagnosing skin cancer was 95%, while the specificity was 88%. Skin cancer diagnosis by neuro-fuzzy system achieved sensitivity of 98% and a specificity of 89%. PMID:21340020

  19. Connected digit speech recognition system for Malayalam language

    Indian Academy of Sciences (India)

    dictive (PLP) cepstral coefficient for speech parameterization and continuous density. Hidden Markov Model (HMM) in the ... where each speaker is asked to read 20 set of continuous digits. The system obtained .... 2.1a Critical band integration (Bark frequency weighing): Experiments in human perception have shown that ...

  20. BRAF inhibition improves tumor recognition by the immune system

    DEFF Research Database (Denmark)

    Donia, Marco; Fagone, Paolo; Nicoletti, Ferdinando

    2012-01-01

    to be poorly efficient. By characterizing the immunological interactions between T cells and cancer cells in clinical material as well as the influence of the FDA-approved BRAF inhibitor vemurafenib on the immune system, we aimed at unraveling new strategies to expand the efficacy of adoptive T-cell transfer...

  1. Implementation of the vehicle recognition systems using wireless ...

    Indian Academy of Sciences (India)

    This article describes how a new sensor circuit was designed to deliver instantaneous, real-time and novel solutions as a vehicle detection system, which is more powerful than the nodes used in other studies, and gives results with smaller error margins due to its serial communication qualification. With the proposed logic ...

  2. Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs

    Directory of Open Access Journals (Sweden)

    Yan Han

    2015-12-01

    Full Text Available Traffic sign recognition (TSR, taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.

  3. Explicit formulation for natural frequencies of double-beam system with arbitrary boundary conditions

    Energy Technology Data Exchange (ETDEWEB)

    Mirzabeigy, Alborz; Madoliat, Reza [Iran University of Science and Technology, Narmak, Tehran (Iran, Islamic Republic of); Dabbagh, Vahid [University of Malaya, Kuala Lumpur (Malaysia)

    2017-02-15

    In this paper, free transverse vibration of two parallel beams connected through Winkler type elastic layer is investigated. Euler- Bernoulli beam hypothesis has been applied and it is assumed that boundary conditions of upper and lower beams are similar while arbitrary without any limitation even for non-ideal boundary conditions. Material properties and cross-section geometry of beams could be different from each other. The motion of the system is described by a homogeneous set of two partial differential equations, which is solved by using the classical Bernoulli-Fourier method. Explicit expressions are derived for the natural frequencies. In order to verify accuracy of results, the problem once again solved using modified Adomian decomposition method. Comparison between results indicates excellent accuracy of proposed formulation for any arbitrary boundary conditions. Derived explicit formulation is simplest method to determine natural frequencies of double-beam systems with high level of accuracy in comparison with other methods in literature.

  4. AN EFFICIENT SELF-UPDATING FACE RECOGNITION SYSTEM FOR PLASTIC SURGERY FACE

    Directory of Open Access Journals (Sweden)

    A. Devi

    2016-08-01

    Full Text Available Facial recognition system is fundamental a computer application for the automatic identification of a person through a digitized image or a video source. The major cause for the overall poor performance is related to the transformations in appearance of the user based on the aspects akin to ageing, beard growth, sun-tan etc. In order to overcome the above drawback, Self-update process has been developed in which, the system learns the biometric attributes of the user every time the user interacts with the system and the information gets updated automatically. The procedures of Plastic surgery yield a skilled and endurable means of enhancing the facial appearance by means of correcting the anomalies in the feature and then treating the facial skin with the aim of getting a youthful look. When plastic surgery is performed on an individual, the features of the face undergo reconstruction either locally or globally. But, the changes which are introduced new by plastic surgery remain hard to get modeled by the available face recognition systems and they deteriorate the performances of the face recognition algorithm. Hence the Facial plastic surgery produces changes in the facial features to larger extent and thereby creates a significant challenge to the face recognition system. This work introduces a fresh Multimodal Biometric approach making use of novel approaches to boost the rate of recognition and security. The proposed method consists of various processes like Face segmentation using Active Appearance Model (AAM, Face Normalization using Kernel Density Estimate/ Point Distribution Model (KDE-PDM, Feature extraction using Local Gabor XOR Patterns (LGXP and Classification using Independent Component Analysis (ICA. Efficient techniques have been used in each phase of the FRAS in order to obtain improved results.

  5. A novel hybrid biometric electronic voting system: integrating finger print face recognition

    International Nuclear Information System (INIS)

    Najam, S.S.; Shaikh, A.Z.; Naqvi, S.

    2018-01-01

    A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition. (author)

  6. A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition

    Directory of Open Access Journals (Sweden)

    Shahram Najam

    2018-01-01

    Full Text Available A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis and K-NN (K-Nearest Neighbor. It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.

  7. Multimodal System Based on Electrooculography and Voice Recognition to Control a Robot Arm

    Directory of Open Access Journals (Sweden)

    José A. Martínez

    2013-07-01

    Full Text Available People with severe motor disorders cannot use their arms and/or hands to interact with the environment. In such cases, a human-machine interface can be used to allow these people to perform activities of daily life. Voice recognition would be the best method to control a device devoted to help with these tasks, but this method is very dependent on the background noise and, under certain circumstances, it cannot be used successfully. In this sense, other methods must be included in the system to assist the voice recognition module. In this project, electrooculography (EOG has been selected due to its stability and robustness. This way, a multimodal system based on EOG and voice recognition has been developed to control a robotic arm. This paper presents the procedures designed to combine both methods to create a multimodal interface useful for disabled people. Tests presented in this document compare the skills of five different users while controlling the robotic arm to perform pick-and-place tasks. Task duration and accuracy have been measured to obtain specific scores that are used to evaluate both interaction methods independently and the multimodal combination of them. The system works successfully using both methods (EOG and voice recognition. In addition, the multimodal interface improves robustness and reduces the uncertainty generated by the environment when there is background noise.

  8. Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

    Science.gov (United States)

    Nikitaev, V. G.

    2017-01-01

    The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

  9. Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

    NARCIS (Netherlands)

    Susyanto, N.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan; Klaassen, C.A.J.

    2016-01-01

    We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

  10. The Study on Detection Method of Water Vapor on Boundary Layer Based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Xu Dongdong

    2015-01-01

    Full Text Available A method of detecting water vapor on boundary layer based on multiagent system is proposed in this paper. Multiagent system receives electromagnetic signals emitted by the telecommunication base station. Due to the analysis of the actual electromagnetic wave signal propagation path in the atmosphere, atmospheric refraction index and moisture inversion are discussed in this paper. And the feasibility of using electromagnetic detection method is also analyzed. A multiagent system is designed to receive the electromagnetic signals. The composition and function of the multiagent system are clearly described. The atmospheric refractivity is detected by the multiagent system in three weather conditions of sunny, foggy, and rainy days. The results demonstrate the feasibility of water vapor detection method of multiagent system boundary by comparing the result of experiment with traditional method.

  11. A primitive-based 3D object recognition system

    Science.gov (United States)

    Dhawan, Atam P.

    1988-01-01

    An intermediate-level knowledge-based system for decomposing segmented data into three-dimensional primitives was developed to create an approximate three-dimensional description of the real world scene from a single two-dimensional perspective view. A knowledge-based approach was also developed for high-level primitive-based matching of three-dimensional objects. Both the intermediate-level decomposition and the high-level interpretation are based on the structural and relational matching; moreover, they are implemented in a frame-based environment.

  12. Performance Evaluation of Speech Recognition Systems as a Next-Generation Pilot-Vehicle Interface Technology

    Science.gov (United States)

    Arthur, Jarvis J., III; Shelton, Kevin J.; Prinzel, Lawrence J., III; Bailey, Randall E.

    2016-01-01

    During the flight trials known as Gulfstream-V Synthetic Vision Systems Integrated Technology Evaluation (GV-SITE), a Speech Recognition System (SRS) was used by the evaluation pilots. The SRS system was intended to be an intuitive interface for display control (rather than knobs, buttons, etc.). This paper describes the performance of the current "state of the art" Speech Recognition System (SRS). The commercially available technology was evaluated as an application for possible inclusion in commercial aircraft flight decks as a crew-to-vehicle interface. Specifically, the technology is to be used as an interface from aircrew to the onboard displays, controls, and flight management tasks. A flight test of a SRS as well as a laboratory test was conducted.

  13. Visual recognition system of cherry picking robot based on Lab color model

    Science.gov (United States)

    Zhang, Qirong; Zuo, Jianjun; Yu, Tingzhong; Wang, Yan

    2017-12-01

    This paper designs a visual recognition system suitable for cherry picking. First, the system deals with the image using the vector median filter. And then it extracts a channel of Lab color model to divide the cherries and the background. The cherry contour was successfully fitted by the least square method, and the centroid and radius of the cherry were extracted. Finally, the cherry was successfully extracted.

  14. Foundations for a syntatic pattern recognition system for genomic DNA sequences

    Energy Technology Data Exchange (ETDEWEB)

    Searles, D.B.

    1993-03-01

    The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

  15. NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment.

    Science.gov (United States)

    Mezgec, Simon; Koroušić Seljak, Barbara

    2017-06-27

    Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of food images, their recognition is a particularly challenging task, which is why traditional approaches in the field have achieved a low classification accuracy. Deep neural networks have outperformed such solutions, and we present a novel approach to the problem of food and drink image detection and recognition that uses a newly-defined deep convolutional neural network architecture, called NutriNet. This architecture was tuned on a recognition dataset containing 225,953 512 × 512 pixel images of 520 different food and drink items from a broad spectrum of food groups, on which we achieved a classification accuracy of 86 . 72 % , along with an accuracy of 94 . 47 % on a detection dataset containing 130 , 517 images. We also performed a real-world test on a dataset of self-acquired images, combined with images from Parkinson's disease patients, all taken using a smartphone camera, achieving a top-five accuracy of 55 % , which is an encouraging result for real-world images. Additionally, we tested NutriNet on the University of Milano-Bicocca 2016 (UNIMIB2016) food image dataset, on which we improved upon the provided baseline recognition result. An online training component was implemented to continually fine-tune the food and drink recognition model on new images. The model is being used in practice as part of a mobile app for the dietary assessment of Parkinson's disease patients.

  16. Eigenvalue Problems for Systems of Nonlinear Boundary Value Problems on Time Scales

    Directory of Open Access Journals (Sweden)

    Henderson J

    2007-01-01

    Full Text Available Values of λ are determined for which there exist positive solutions of the system of dynamic equations, , , for , satisfying the boundary conditions, , where is a time scale. A Guo-Krasnosel'skii fixed point-theorem is applied.

  17. On the warm nearshore bias in Pathfinder monthly SST products over Eastern Boundary upwelling systems

    CSIR Research Space (South Africa)

    Dufois, F

    2012-01-01

    Full Text Available Using in situ sea surface temperature (SST) data and MODIS/TERRA SST, the monthly AVHRR Pathfinder (version 5.0 and 5.2) SST product was evaluated within the four main Eastern Boundary Upwelling Systems. A warm bias in the monthly Pathfinder data...

  18. Initial boundary value problem for a system in elastodynamics with viscosity

    Directory of Open Access Journals (Sweden)

    Kayyunnapara Thomas Joseph

    2005-12-01

    Full Text Available In this paper we prove existence of global solutions to boundary-value problems for two systems with a small viscosity coefficient and derive estimates uniform in the viscosity parameter. We do not assume any smallness conditions on the data.

  19. Trigonometric series adapted for the study of Neumann boundary-value problems of Lame systems

    Directory of Open Access Journals (Sweden)

    Boubakeur Merouani

    2017-06-01

    Full Text Available In this article, we study the solutions to Neumann boundary-value problems of Lame system in a sectorial domains. We study directly this problem, by using trigonometric series, without going through the Airy functions. Results using the Airy function are given in [11].

  20. Partially solved differential systems with two-point non-linear boundary conditions

    Czech Academy of Sciences Publication Activity Database

    Rontó, András; Rontó, M.; Varga, I.

    2017-01-01

    Roč. 18, č. 2 (2017), s. 1001-1014 ISSN 1787-2405 Institutional support: RVO:67985840 Keywords : implicit differential systems * non-linear two-point boundary conditions * parametrization technique Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 0.388, year: 2016 http://mat76.mat.uni-miskolc.hu/mnotes/article/2491

  1. Security and matching of partial fingerprint recognition systems

    Science.gov (United States)

    Jea, Tsai-Yang; Chavan, Viraj S.; Govindaraju, Venu; Schneider, John K.

    2004-08-01

    Despite advances in fingerprint identification techniques, matching incomplete or partial fingerprints still poses a difficult challenge. While the introduction of compact silicon chip-based sensors that capture only a part of the fingerprint area have made this problem important from a commercial perspective, there is also considerable interest on the topic for processing partial and latent fingerprints obtained at crime scenes. Attempts to match partial fingerprints using singular ridge structures-based alignment techniques fail when the partial print does not include such structures (e.g., core or delta). We present a multi-path fingerprint matching approach that utilizes localized secondary features derived using only the relative information of minutiae. Since the minutia-based fingerprint representation, is an ANSI-NIST standard, our approach has the advantage of being directly applicable to already existing databases. We also analyze the vulnerability of partial fingerprint identification systems to brute force attacks. The described matching approach has been tested on one of FVC2002"s DB1 database11. The experimental results show that our approach achieves an equal error rate of 1.25% and a total error rate of 1.8% (with FAR at 0.2% and FRR at 1.6%).

  2. The Step-Type Contrast Structure for High Dimensional Tikhonov System with Neumann Boundary Conditions

    Directory of Open Access Journals (Sweden)

    Aifeng Wang

    2016-01-01

    Full Text Available We investigate the step-type contrast structure for high dimensional Tikhonov system with Neumann boundary conditions. We not only propose a key condition with the existence of the number of mutually independent first integrals under which there exists a step-type contrast structure, but also determine where an internal transition time is. Using the method of boundary function, we construct the formal asymptotic solution and give the analytical expression for the higher order terms. At the same time, the uniformly valid asymptotic expansion and the existence of such an available step-type contrast structure are obtained by sewing connection method.

  3. Initial-boundary value problems associated with the Ablowitz-Ladik system

    Science.gov (United States)

    Xia, Baoqiang; Fokas, A. S.

    2018-02-01

    We employ the Ablowitz-Ladik system as an illustrative example in order to demonstrate how to analyze initial-boundary value problems for integrable nonlinear differential-difference equations via the unified transform (Fokas method). In particular, we express the solutions of the integrable discrete nonlinear Schrödinger and integrable discrete modified Korteweg-de Vries equations in terms of the solutions of appropriate matrix Riemann-Hilbert problems. We also discuss in detail, for both the above discrete integrable equations, the associated global relations and the process of eliminating of the unknown boundary values.

  4. Stability boundaries analysis of electric power system with DC transmission based on differential-algebraic equation system

    OpenAIRE

    Susuki, Yoshihiko; Hikihara Takashi; Chiang, HD

    2004-01-01

    This paper discusses stability boundaries in an electric power system with dc transmission based on a differential-algebraic equation (DAE) system. The DAE system is derived to analyze transient stability of the ac/dc power system: the differential equation represents the dynamics of the generator and the dc transmission, and the algebraic equation the active and reactive power relationship between the ac system and the dc transmission. In this paper complete characterization of stability bou...

  5. An automatic system for Turkish word recognition using Discrete Wavelet Neural Network based on adaptive entropy

    International Nuclear Information System (INIS)

    Avci, E.

    2007-01-01

    In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of Discrete Wavelet Transform (DWT) and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the used system is evaluated by using noisy Turkish word signals. Test results showing the effectiveness of the proposed automatic system are presented in this paper. The rate of correct recognition is about 92.5% for the sample speech signals. (author)

  6. Pattern-recognition software detecting the onset of failures in complex systems

    International Nuclear Information System (INIS)

    Mott, J.; King, R.

    1987-01-01

    A very general mathematical framework for embodying learned data from a complex system and combining it with a current observation to estimate the true current state of the system has been implemented using nearly universal pattern-recognition algorithms and applied to surveillance of the EBR-II power plant. In this application the methodology can provide signal validation and replacement of faulty signals on a near-real-time basis for hundreds of plant parameters. The mathematical framework, the pattern-recognition algorithms, examples of the learning and estimating process, and plant operating decisions made using this methodology are discussed. The entire methodology has been reduced to a set of FORTRAN subroutines which are small, fast, robust and executable on a personal computer with a serial link to the system's data acquisition computer, or on the data acquisition computer itself

  7. A field study of the accuracy and reliability of a biometric iris recognition system.

    Science.gov (United States)

    Latman, Neal S; Herb, Emily

    2013-06-01

    The iris of the eye appears to satisfy the criteria for a good anatomical characteristic for use in a biometric system. The purpose of this study was to evaluate a biometric iris recognition system: Mobile-Eyes™. The enrollment, verification, and identification applications were evaluated in a field study for accuracy and reliability using both irises of 277 subjects. Independent variables included a wide range of subject demographics, ambient light, and ambient temperature. A sub-set of 35 subjects had alcohol-induced nystagmus. There were 2710 identification and verification attempts, which resulted in 1,501,340 and 5540 iris comparisons respectively. In this study, the system successfully enrolled all subjects on the first attempt. All 277 subjects were successfully verified and identified on the first day of enrollment. None of the current or prior eye conditions prevented enrollment, verification, or identification. All 35 subjects with alcohol-induced nystagmus were successfully verified and identified. There were no false verifications or false identifications. Two conditions were identified that potentially could circumvent the use of iris recognitions systems in general. The Mobile-Eyes™ iris recognition system exhibited accurate and reliable enrollment, verification, and identification applications in this study. It may have special applications in subjects with nystagmus. Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

  8. Development of a Mandarin-English Bilingual Speech Recognition System for Real World Music Retrieval

    Science.gov (United States)

    Zhang, Qingqing; Pan, Jielin; Lin, Yang; Shao, Jian; Yan, Yonghong

    In recent decades, there has been a great deal of research into the problem of bilingual speech recognition-to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language**. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was

  9. Combined Temperature/Momentum Boundary Conditions for Molecular Dynamics Simulations of Flow in Nanofluidic Systems

    Science.gov (United States)

    Templeton, Jeremy; Jones, Reese

    2012-11-01

    Molecular dynamics (MD) is a useful technique for scientific investigations of nanofluidic processes as it explicitly represents the dynamics of every atom in a system. In order to model systems of interest, e.g. nanochannels, it is necessary to constrain atomic motions to conform to conditions corresponding to large-scale information, e.g. thermodynamic variables. However, many engineered configurations involve complex interactions between the system and its environment, and take place in non-trivial geometries. To accurately simulate these phenomena, methods to apply boundary conditions to MD systems are required that simultaneously regulate the temperature (i.e., energy) and momentum of the atoms in a local manner. This work uses an atomistic-to-continuum formulation to generate boundary conditions by using finite elements (FE) and their associated shape functions to define ``boundaries'' for a particle system. By projecting onto the FE basis, coarse-scale observables are identified for regulation based on separating the mean and fluctuating velocity components defining the momentum and temperature. Regulating the MD system is achieved by applying constraints posed on the coarse-grained variables. The method is illustrated by application to several nanofluidic systems. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE.

  10. Adaptive Boundary Iterative Learning Control for an Euler-Bernoulli Beam System With Input Constraint.

    Science.gov (United States)

    He, Wei; Meng, Tingting; Huang, Deqing; Li, Xuefang

    2017-03-15

    This paper addresses the vibration control and the input constraint for an Euler-Bernoulli beam system under aperiodic distributed disturbance and aperiodic boundary disturbance. Hyperbolic tangent functions and saturation functions are adopted to tackle the input constraint. A restrained adaptive boundary iterative learning control (ABILC) law is proposed based on a time-weighted Lyapunov-Krasovskii-like composite energy function. In order to deal with the uncertainty of a system parameter and reject the external disturbances, three adaptive laws are designed and learned in the iteration domain. All the system states of the closed-loop system are proved to be bounded in each iteration. Along the iteration axis, the displacements asymptotically converge toward zero. Simulation results are provided to illustrate the effectiveness of the proposed ABILC scheme.

  11. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood

    2013-08-01

    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  12. Source-to-Sink: An Earth/Mars Comparison of Boundary Conditions for Eolian Dune Systems

    OpenAIRE

    Kocurek, Gary; Ewing, Ryan C.

    2012-01-01

    Eolian dune fields on Earth and Mars evolve as complex systems within a set of boundary conditions. A source-to-sink comparison indicates that although differences exist in sediment production and transport, the systems largely converge at the dune-flow and pattern-development levels, but again differ in modes of accumulation and preservation. On Earth, where winds frequently exceed threshold speeds, dune fields are sourced primarily through deflation of subaqueous deposits as these sediments...

  13. Stability result of the Timoshenko system with delay and boundary feedback

    KAUST Repository

    Said-Houari, Belkacem

    2012-01-06

    Our interest in this paper is to analyse the asymptotic behaviour of a Timoshenko beam system together with two boundary controls, with delay terms in the first and second equation. Assuming the weights of the delay are small enough, we show that the system is well-posed using the semigroup theory. Furthermore, we introduce a Lyapunov functional that gives the exponential decay of the total energy. © 2012 The author.

  14. A Morse-code recognition system with LMS and matching algorithms for persons with disabilities.

    Science.gov (United States)

    Shih, C H; Luo, C H

    1997-05-01

    Single-switch communication is an effective auxiliary method for persons with disabilities. However, it is not easy to recognize the Morse codes typed by them. In our earlier proposed Morse code auto-recognition method, using the Least-Mean-Square (LMS) adaptive algorithm, it was demonstrated that the system could successfully recognize the Morse-coded messages at unstable typing speeds. However, the speed variation had to be limited to a range between 0.67 and two times the present speed. In the case of beginners or those with heavy disabilities, this rule can not always be complied with, producing a low recognition rate of 20%. To address this limitation, this paper offers an advanced recognition method which combines the Least-Mean-Square algorithm with a character-by-character matching technique. The recognition rate for this method from simulated and real data from various sources is as high as 75% or more on average. This practical application of the single-switch method means a step forward toward alternative communication for disabled persons.

  15. Development of Portable Automatic Number Plate Recognition System on Android Mobile Phone

    Science.gov (United States)

    Mutholib, Abdul; Gunawan, Teddy S.; Chebil, Jalel; Kartiwi, Mira

    2013-12-01

    The Automatic Number Plate Recognition (ANPR) System has performed as the main role in various access control and security, such as: tracking of stolen vehicles, traffic violations (speed trap) and parking management system. In this paper, the portable ANPR implemented on android mobile phone is presented. The main challenges in mobile application are including higher coding efficiency, reduced computational complexity, and improved flexibility. Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. ANPR system for mobile phone need to be optimize due to its limited CPU and memory resources, its ability for geo-tagging image captured using GPS coordinates and its ability to access online database to store the vehicle's information. In this paper, the design of portable ANPR on android mobile phone will be described as follows. First, the graphical user interface (GUI) for capturing image using built-in camera was developed to acquire vehicle plate number in Malaysia. Second, the preprocessing of raw image was done using contrast enhancement. Next, character segmentation using fixed pitch and an optical character recognition (OCR) using neural network were utilized to extract texts and numbers. Both character segmentation and OCR were using Tesseract library from Google Inc. The proposed portable ANPR algorithm was implemented and simulated using Android SDK on a computer. Based on the experimental results, the proposed system can effectively recognize the license plate number at 90.86%. The required processing time to recognize a license plate is only 2 seconds on average. The result is consider good in comparison with the results obtained from previous system that was processed in a desktop PC with the range of result from 91.59% to 98% recognition rate and 0.284 second to 1.5 seconds recognition time.

  16. Object Recognition System in Remote Controlled Weapon Station using SIFT and SURF Methods

    Directory of Open Access Journals (Sweden)

    Midriem Mirdanies

    2013-12-01

    Full Text Available Object recognition system using computer vision that is implemented on Remote Controlled Weapon Station (RCWS is discussed. This system will make it easier to identify and shoot targeted object automatically. Algorithm was created to recognize real time multiple objects using two methods i.e. Scale Invariant Feature Transform (SIFT and Speeded Up Robust Features (SURF combined with K-Nearest Neighbors (KNN and Random Sample Consensus (RANSAC for verification. The algorithm is designed to improve object detection to be more robust and to minimize the processing time required. Objects are registered on the system consisting of the armored personnel carrier, tanks, bus, sedan, big foot, and police jeep. In addition, object selection can use mouse to shoot another object that has not been registered on the system. Kinect™ is used to capture RGB images and to find the coordinates x, y, and z of the object. The programming language used is C with visual studio IDE 2010 and opencv libraries. Object recognition program is divided into three parts: 1 reading image from kinect™ and simulation results, 2 object recognition process, and 3 transfer of the object data to the ballistic computer. Communication between programs is performed using shared memory. The detected object data is sent to the ballistic computer via Local Area Network (LAN using winsock for ballistic calculation, and then the motor control system moves the direction of the weapon model to the desired object. The experimental results show that the SIFT method is more suitable because more accurate and faster than SURF with the average processing time to detect one object is 430.2 ms, two object is 618.4 ms, three objects is 682.4 ms, and four objects is 756.2 ms. Object recognition program is able to recognize multi-objects and the data of the identified object can be processed by the ballistic computer in realtime.

  17. Solutions Stability of Initial Boundary Problem, Modeling of Dynamics of Some Discrete Continuum Mechanical System

    Directory of Open Access Journals (Sweden)

    D. A. Eliseev

    2015-01-01

    Full Text Available The solution stability of an initial boundary problem for a linear hybrid system of differential equations, which models the rotation of a rigid body with two elastic rods located in the same plane is studied in the paper. To an axis passing through the mass center of the rigid body perpendicularly to the rods location plane is applied the stabilizing moment proportional to the angle of the system rotation, derivative of the angle, integral of the angle. The external moment provides a feedback. A method of studying the behavior of solutions of the initial boundary problem is proposed. This method allows to exclude from the hybrid system of differential equations partial differential equations, which describe the dynamics of distributed elements of a mechanical system. It allows us to build one equation for an angle of the system rotation. Its characteristic equation defines the stability of solutions of all the system. In the space of feedback-coefficients the areas that provide the asymptotic stability of solutions of the initial boundary problem are built up.

  18. Architecture of top down, parallel pattern recognition system TOPS and its application to the MR head images

    International Nuclear Information System (INIS)

    Matsunoshita, Jun-ichi; Akamatsu, Shigeo; Yamamoto, Shinji.

    1993-01-01

    This paper describes about the system architecture of a new image recognition system TOPS (top-down parallel pattern recognition system), and its application to the automatic extraction of brain organs (cerebrum, cerebellum, brain stem) from 3D-MRI images. Main concepts of TOPS are as follows: (1) TOPS is the top-down type recognition system, which allows parallel models in each level of hierarchy structure. (2) TOPS allows parallel image processing algorithms for one purpose (for example, for extraction of one special organ). This results in multiple candidates for one purpose, and judgment to get unique solution for it will be made at upper level of hierarchy structure. (author)

  19. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Inho [Institute for Human and Machine Cognition (IHMC), Florida (United States); Oh, Jaesung; Oh, Jun-Ho [Korea Advanced Institute of Science and Technology (KAIST), Daejeon (Korea, Republic of); Kim, Inhyeok [NAVER Green Factory, Seongnam (Korea, Republic of)

    2017-06-15

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  20. Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

    International Nuclear Information System (INIS)

    Lee, Inho; Oh, Jaesung; Oh, Jun-Ho; Kim, Inhyeok

    2017-01-01

    This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

  1. A Kinect based sign language recognition system using spatio-temporal features

    Science.gov (United States)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

    This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

  2. A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

    Directory of Open Access Journals (Sweden)

    Alessandro Manzi

    2017-05-01

    Full Text Available Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM, trained with Sequential Minimal Optimization (SMO. The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60 and the Telecommunication Systems Team (TST Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

  3. Intelligent Image Recognition System for Marine Fouling Using Softmax Transfer Learning and Deep Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    C. S. Chin

    2017-01-01

    Full Text Available The control of biofouling on marine vessels is challenging and costly. Early detection before hull performance is significantly affected is desirable, especially if “grooming” is an option. Here, a system is described to detect marine fouling at an early stage of development. In this study, an image of fouling can be transferred wirelessly via a mobile network for analysis. The proposed system utilizes transfer learning and deep convolutional neural network (CNN to perform image recognition on the fouling image by classifying the detected fouling species and the density of fouling on the surface. Transfer learning using Google’s Inception V3 model with Softmax at last layer was carried out on a fouling database of 10 categories and 1825 images. Experimental results gave acceptable accuracies for fouling detection and recognition.

  4. A Real-Time Facial Expression Recognition System for Online Games

    Directory of Open Access Journals (Sweden)

    Ce Zhan

    2008-01-01

    collaboration, communication, and interaction. However, compared with ordinary human communication, MOG still has several limitations, especially in communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. In this paper, we propose an automatic expression recognition system that can be integrated into an MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, improved, and extended. In particular, Viola and Jones face-detection method is extended to detect small-scale key facial components; and fixed facial landmarks are used to reduce the computational load with little performance degradation in the recognition accuracy.

  5. Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

    Science.gov (United States)

    Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

    2014-11-01

    A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

  6. Implementing an excellence in teaching recognition system: needs analysis and recommendations.

    Science.gov (United States)

    Schindler, Nancy; Corcoran, Julia C; Miller, Megan; Wang, Chih-Hsiung; Roggin, Kevin; Posner, Mitchell; Fryer, Jonathan; DaRosa, Debra A

    2013-01-01

    Teaching awards have been suggested to serve a variety of purposes. The specific characteristics of teaching awards and the associated effectiveness at achieving planned purposes are poorly understood. A needs analysis was performed to inform recommendations for an Excellence in Teaching Recognition System to meet the needs of surgical education leadership. We performed a 2-part needs analysis beginning with a review of the literature. We then, developed, piloted, and administered a survey instrument to General Surgery program leaders. The survey examined the features and perceived effectiveness of existing teaching awards systems. A multi-institution committee of program directors, clerkship directors, and Vice-Chairs of education then met to identify goals and develop recommendations for implementation of an "Excellence in Teaching Recognition System." There is limited evidence demonstrating effectiveness of existing teaching awards in medical education. Evidence supports the ability of such awards to demonstrate value placed on teaching, to inspire faculty to teach, and to contribute to promotion. Survey findings indicate that existing awards strive to achieve these purposes and that educational leaders believe awards have the potential to do this and more. Leaders are moderately satisfied with existing awards for providing recognition and demonstrating value placed on teaching, but they are less satisfied with awards for motivating faculty to participate in teaching or for contributing to promotion. Most departments and institutions honor only a few recipients annually. There is a paucity of literature addressing teaching recognition systems in medical education and little evidence to support the success of such systems in achieving their intended purposes. The ability of awards to affect outcomes such as participation in teaching and promotion may be limited by the small number of recipients for most existing awards. We propose goals for a Teaching Recognition

  7. A system level boundary scan controller board for VME applications [to CERN experiments

    CERN Document Server

    Cardoso, N; Da Silva, J C

    2000-01-01

    This work is the result of a collaboration between INESC and LIP in the CMS experiment being conducted at CERN. The collaboration addresses the application of boundary scan test at system level namely the development of a VME boundary scan controller (BSC) board prototype and the corresponding software. This prototype uses the MTM bus existing in the VME64* backplane to apply the 1149.1 test vectors to a system composed of nineteen boards, called here units under test (UUTs). A top-down approach is used to describe our work. The paper begins with some insights about the experiment being conducted at CERN, proceed with system level considerations concerning our work and with some details about the BSC board. The results obtained so far and the proposed work is reviewed in the end of this contribution. (11 refs).

  8. Conservation Laws and Nonlocally Related Systems of Two-Dimensional Boundary Layer Models

    Science.gov (United States)

    Naz, R.; Cheviakov, A. F.

    2017-10-01

    Local conservation laws, potential systems, and nonlocal conservation laws are systematically computed for three-equilibrium two-component boundary layer models that describe different physical situations: a plate flow, a flow parallel to the axis of a circular cylinder, and a radial jet striking a planar wall. First, local conservation laws of each model are computed using the direct method. For each of the three boundary layer models, two local conservation laws are found. The corresponding potential variables are introduced, and nonlocally related potential systems and subsystems are formed. Then nonlocal conservation laws are sought, arising as local conservation laws of nonlocally related systems. For each of the three physical models, similar nonlocal conservation laws arise. Further nonlocal variables that lead to further potential systems are considered. Trees of nonlocally related systems are constructed; their structure coincides for all three models. The three boundary layer models considered in this work provide rich and interesting examples of the construction of trees of nonlocally related systems. In particular, the trees involve spectral potential systems depending on a parameter; these spectral potential systems lead to nonlocal conservation laws. Moreover, potential variables that are not locally related on solution sets of some potential systems become local functions of each other on solution sets of other systems. The point symmetry analysis shows that the plate and radial jet flow models possess infinite-dimensional Lie algebras of point symmetries, whereas the Lie algebra of point symmetries for the cylinder flow model is three-dimensional. The computation of nonlocal symmetries reveals none that arise for the original model equations, which is common for partial differential equations (PDE) systems without constitutive parameters or functions, but does reveal nonlocal symmetries for some nonlocally related PDE systems.

  9. Vibration analysis of multi-span beam system under arbitrary boundary and coupling conditions

    Directory of Open Access Journals (Sweden)

    ZHENG Chaofan

    2017-08-01

    Full Text Available In order to overcome the difficulties of studying the vibration analysis model of a multi-span beam system under various boundary and coupling conditions, this paper constructs a free vibration analysis model of a multi-span beam system on the basis of the Bernoulli-Euler beam theory. The vibration characteristics of a multi-span beam system under arbitrary boundary supports and elastic coupling conditions are investigated using the current analysis model. Unlike most existing techniques, the beam displacement function is generally sought as an improved Fourier cosine series, and four sine terms are introduced to overcome all the relevant discontinuities or jumps of elastic boundary conditions. On this basis, the unknown series coefficients of the displacement function are treated as the generalized coordinates and solved using the Rayleigh-Ritz method, and the vibration problem of multi-span bean systems is converted into a standard eigenvalue problem concerning the unknown displacement expansion coefficient. By comparing the free vibration characteristics of the proposed method with those of the FEA method, the efficiency and accuracy of the present method are validated, providing a reliable and theoretical basis for multi-span beam system structure in engineering applications.

  10. Automatic recognition of fundamental tissues on histology images of the human cardiovascular system.

    Science.gov (United States)

    Mazo, Claudia; Trujillo, Maria; Alegre, Enrique; Salazar, Liliana

    2016-10-01

    Cardiovascular disease is the leading cause of death worldwide. Therefore, techniques for improving diagnosis and treatment in this field have become key areas for research. In particular, approaches for tissue image processing may support education system and medical practice. In this paper, an approach to automatic recognition and classification of fundamental tissues, using morphological information is presented. Taking a 40× or 10× histological image as input, three clusters are created with the k-means algorithm using a structural tensor and the red and the green channels. Loose connective tissue, light regions and cell nuclei are recognised on 40× images. Then, the cell nuclei's features - shape and spatial projection - and light regions are used to recognise and classify epithelial cells and tissue into flat, cubic and cylindrical. In a similar way, light regions, loose connective and muscle tissues are recognised on 10× images. Finally, the tissue's function and composition are used to refine muscle tissue recognition. Experimental validation is then carried out by histologist following expert criteria, along with manually annotated images that are used as a ground-truth. The results revealed that the proposed approach classified the fundamental tissues in a similar way to the conventional method employed by histologists. The proposed automatic recognition approach provides for epithelial tissues a sensitivity of 0.79 for cubic, 0.85 for cylindrical and 0.91 for flat. Furthermore, the experts gave our method an average score of 4.85 out of 5 in the recognition of loose connective tissue and 4.82 out of 5 for muscle tissue recognition. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Estimating anisotropic diffusion of neutrons near the boundary of a pebble bed random system

    Energy Technology Data Exchange (ETDEWEB)

    Vasques, R. [Department of Mathematics, Center for Computational Engineering Science, RWTH Aachen University, Schinkel Strasse 2, D-52062 Aachen (Germany)

    2013-07-01

    Due to the arrangement of the pebbles in a Pebble Bed Reactor (PBR) core, if a neutron is located close to a boundary wall, its path length probability distribution function in directions of flight parallel to the wall is significantly different than in other directions. Hence, anisotropic diffusion of neutrons near the boundaries arises. We describe an analysis of neutron transport in a simplified 3-D pebble bed random system, in which we investigate the anisotropic diffusion of neutrons born near one of the system's boundary walls. While this simplified system does not model the actual physical process that takes place near the boundaries of a PBR core, the present work paves the road to a formulation that may enable more accurate diffusion simulations of such problems to be performed in the future. Monte Carlo codes have been developed for (i) deriving realizations of the 3-D random system, and (ii) performing 3-D neutron transport inside the heterogeneous model; numerical results are presented for three different choices of parameters. These numerical results are used to assess the accuracy of estimates for the mean-squared displacement of neutrons obtained with the diffusion approximations of the Atomic Mix Model and of the recently introduced [1] Non-Classical Theory with angular-dependent path length distribution. The Non-Classical Theory makes use of a Generalized Linear Boltzmann Equation in which the locations of the scattering centers in the system are correlated and the distance to collision is not exponentially distributed. We show that the results predicted using the Non-Classical Theory successfully model the anisotropic behavior of the neutrons in the random system, and more closely agree with experiment than the results predicted by the Atomic Mix Model. (authors)

  12. Multimodal Biometric System Based on the Recognition of Face and Both Irises

    Directory of Open Access Journals (Sweden)

    Yeong Gon Kim

    2012-09-01

    Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

  13. Sign Language Recognition System using Neural Network for Digital Hardware Implementation

    International Nuclear Information System (INIS)

    Vargas, Lorena P; Barba, Leiner; Torres, C O; Mattos, L

    2011-01-01

    This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

  14. The effect of system boundaries on the mean free path for confined gases

    Directory of Open Access Journals (Sweden)

    Sooraj K. Prabha

    2013-10-01

    Full Text Available The mean free path of rarefied gases is accurately determined using Molecular Dynamics simulations. The simulations are carried out on isothermal argon gas (Lennard-Jones fluid over a range of rarefaction levels under various confinements (unbounded gas, parallel reflective wall and explicit solid platinum wall bounded gas in a nanoscale domain. The system is also analyzed independently in constitutive sub-systems to calculate the corresponding local mean free paths. Our studies which predominate in the transition regime substantiate the boundary limiting effect on mean free paths owing to the sharp diminution in molecular free paths near the planar boundaries. These studies provide insight to the transport phenomena of rarefied gases through nanochannels which have established their potential in microscale and nanoscale heat transfer applications.

  15. Existence of Positive Solutions to a Boundary Value Problem for a Delayed Nonlinear Fractional Differential System

    Directory of Open Access Journals (Sweden)

    Chen Yuming

    2011-01-01

    Full Text Available Though boundary value problems for fractional differential equations have been extensively studied, most of the studies focus on scalar equations and the fractional order between 1 and 2. On the other hand, delay is natural in practical systems. However, not much has been done for fractional differential equations with delays. Therefore, in this paper, we consider a boundary value problem of a general delayed nonlinear fractional system. With the help of some fixed point theorems and the properties of the Green function, we establish several sets of sufficient conditions on the existence of positive solutions. The obtained results extend and include some existing ones and are illustrated with some examples for their feasibility.

  16. Blow-up analysis for a system of heat equations coupled through a nonlinear boundary condition

    DEFF Research Database (Denmark)

    Pedersen, M.; Lin, Zhigui

    2001-01-01

    Consider the system of heat equations uit - Δui = 0 (i = 1 , . . . , k, uk+i := u1) in Ω x (0, T) coupled through nonlinear boundary conditions ∂ui/∂η = up1i+1 on ∂Ω x [0, T). The upper and lower bounds of the blow-up rate is derived. © 2000 Elsevier Science Ltd. All rights reserved.......Consider the system of heat equations uit - Δui = 0 (i = 1 , . . . , k, uk+i := u1) in Ω x (0, T) coupled through nonlinear boundary conditions ∂ui/∂η = up1i+1 on ∂Ω x [0, T). The upper and lower bounds of the blow-up rate is derived. © 2000 Elsevier Science Ltd. All rights reserved....

  17. Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

    Science.gov (United States)

    Winda, A.; Sofyan; Sthevany; Vincent, R. S.

    2017-12-01

    Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

  18. Development of a written music-recognition system using Java and open source technologies

    Science.gov (United States)

    Loibner, Gernot; Schwarzl, Andreas; Kovač, Matthias; Paulus, Dietmar; Pölzleitner, Wolfgang

    2005-10-01

    We report on the development of a software system to recognize and interpret printed music. The overall goal is to scan printed music sheets, analyze and recognize the notes, timing, and written text, and derive the all necessary information to use the computers MIDI sound system to play the music. This function is primarily useful for musicians who want to digitize printed music for editing purposes. There exist a number of commercial systems that offer such a functionality. However, on testing these systems, we were astonished on how weak they behave in their pattern recognition parts. Although we submitted very clear and rather flawless scanning input, none of these systems was able to e.g. recognize all notes, staff lines, and systems. They all require a high degree of interaction, post-processing, and editing to get a decent digital version of the hard copy material. In this paper we focus on the pattern recognition area. In a first approach we tested more or less standard methods of adaptive thresholding, blob detection, line detection, and corner detection to find the notes, staff lines, and candidate objects subject to OCR. Many of the objects on this type of material can be learned in a training phase. None of the commercial systems we saw offers the option to train special characters or unusual signatures. A second goal in this project is to use a modern software engineering platform. We were interested in how well Java and open source technologies are suitable for pattern recognition and machine vision. The scanning of music served as a case-study.

  19. Face Detection and Recognition

    National Research Council Canada - National Science Library

    Jain, Anil K

    2004-01-01

    This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...

  20. Parallel System Architecture (PSA): An efficient approach for automatic recognition of volcano-seismic events

    Science.gov (United States)

    Cortés, Guillermo; García, Luz; Álvarez, Isaac; Benítez, Carmen; de la Torre, Ángel; Ibáñez, Jesús

    2014-02-01

    Automatic recognition of volcano-seismic events is becoming one of the most demanded features in the early warning area at continuous monitoring facilities. While human-driven cataloguing is time-consuming and often an unreliable task, an appropriate machine framework allows expert technicians to focus only on result analysis and decision-making. This work presents an alternative to serial architectures used in classic recognition systems introducing a parallel implementation of the whole process: configuration, feature extraction, feature selection and classification stages are independently carried out for each type of events in order to exploit the intrinsic properties of each signal class. The system uses Gaussian Mixture Models (GMMs) to classify the database recorded at Deception Volcano Island (Antarctica) obtaining a baseline recognition rate of 84% with a cepstral-based waveform parameterization in the serial architecture. The parallel approach increases the results to close to 92% using mixture-based parameterization vectors or up to 91% when the vector size is reduced by 19% via the Discriminative Feature Selection (DFS) algorithm. Besides the result improvement, the parallel architecture represents a major step in terms of flexibility and reliability thanks to the class-focused analysis, providing an efficient tool for monitoring observatories which require real-time solutions.

  1. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System

    Directory of Open Access Journals (Sweden)

    Miguel Gavilán

    2012-01-01

    Full Text Available This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM. A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  2. Complete vision-based traffic sign recognition supported by an I2V communication system.

    Science.gov (United States)

    García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  3. Fast and Low-Cost Mechatronic Recognition System for Persian Banknotes

    Directory of Open Access Journals (Sweden)

    Majid Behjat

    2014-03-01

    Full Text Available In this paper, we designed a fast and low-cost mechatronic system for recognition of eight current Persian banknotes in circulation. Firstly, we proposed a mechanical solution for avoiding extra processing time caused by detecting the place of banknote and paper angle correction in an input image. We also defined new parameters for feature extraction, including colour features (RGBR values, size features (LWR and texture features (CRLVR value. Then, we used a Multi-Layer Perceptron (MLP neural network in the recognition phase to reduce the necessary processing time. In this research, we collected a perfect database of Persian banknote images (about 4000 double-sided prevalent images. We reached about 99.06% accuracy (average for each side in final banknote recognition by testing 800 different worn, torn and new banknotes which were not part of the initial learning phase. This accuracy could increase to 99.62% in double-sided decision mode. Finally, we designed an ATmega32 microcontroller-based hardware with 16MHz clock frequency for implementation of our proposed system which can recognize sample banknotes at about 480ms and 560ms for single-sided detection and double-sided detection respectively, after image scanning.

  4. Social Hackers: Integration in the Host Chemical Recognition System by a Paper Wasp Social Parasite

    Science.gov (United States)

    Turillazzi, S.; Sledge, M. F.; Dani, F. R.; Cervo, R.; Massolo, A.; Fondelli, L.

    Obligate social parasites in the social insects have lost the worker caste and the ability to establish nests. As a result, parasites must usurp a host nest, overcome the host recognition system, and depend on the host workers to rear their offspring. We analysed cuticular hydrocarbon profiles of live parasite females of the paper wasp social parasite Polistes sulcifer before and after usurpation of host nests, using the non-destructive technique of solid-phase micro-extraction. Our results reveal that hydrocarbon profiles of parasites change after usurpation of host nests to match the cuticular profile of the host species. Chemical evidence further shows that the parasite queen changes the odour of the nest by the addition of a parasite-specific hydrocarbon. We discuss the possible role of this in the recognition and acceptance of the parasite and its offspring in the host colony.

  5. Novel structure-recognition-based OCR system and its parallel VLSI architecture

    Science.gov (United States)

    Shan, Tie-Jun

    1993-04-01

    We propose a structure pattern recognition based OCR system for printed text recognition. The segmentation algorithm is a raster-scan based one that reduces memory access time a great deal. The feature extract algorithm is a chain-code encoding based graph traversal algorithm. It has an advantage of single memory access for each pixel while most graph traversal algorithms require multiple scans of the entire image. While traversing a thinned character, structural feature is automatically extracted. The classification is a process of tree search in the structure feature space that is created during the training process. The segmentation, thinning, and feature extraction algorithms are all raster-scan based algorithms that can be implemented by a parallel systolic array architecture.

  6. Using speech recognition to enhance the Tongue Drive System functionality in computer access.

    Science.gov (United States)

    Huo, Xueliang; Ghovanloo, Maysam

    2011-01-01

    Tongue Drive System (TDS) is a wireless tongue operated assistive technology (AT), which can enable people with severe physical disabilities to access computers and drive powered wheelchairs using their volitional tongue movements. TDS offers six discrete commands, simultaneously available to the users, for pointing and typing as a substitute for mouse and keyboard in computer access, respectively. To enhance the TDS performance in typing, we have added a microphone, an audio codec, and a wireless audio link to its readily available 3-axial magnetic sensor array, and combined it with a commercially available speech recognition software, the Dragon Naturally Speaking, which is regarded as one of the most efficient ways for text entry. Our preliminary evaluations indicate that the combined TDS and speech recognition technologies can provide end users with significantly higher performance than using each technology alone, particularly in completing tasks that require both pointing and text entry, such as web surfing.

  7. Single-Walled Carbon Nanotubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

    Directory of Open Access Journals (Sweden)

    Venkata K. K. Upadhyayula

    2008-01-01

    Full Text Available The possibility of using single-walled carbon nanotubes (SWCNTs aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies. The Freundlich adsorption equilibrium constant (k for S.aureus and E.coli determined from batch adsorption study was found to be 9×108 and 2×108 ml/g, respectively. The visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen. The results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability. This is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.

  8. Individual recognition of social rank and social memory performance depends on a functional circadian system.

    Science.gov (United States)

    Müller, L; Weinert, D

    2016-11-01

    In a natural environment, social abilities of an animal are important for its survival. Particularly, it must recognize its own social rank and the social rank of a conspecific and have a good social memory. While the role of the circadian system for object and spatial recognition and memory is well known, the impact of the social rank and circadian disruptions on social recognition and memory were not investigated so far. In the present study, individual recognition of social rank and social memory performance of Djungarian hamsters revealing different circadian phenotypes were investigated. Wild type (WT) animals show a clear and well-synchronized daily activity rhythm, whereas in arrhythmic (AR) hamsters, the suprachiasmatic nuclei (SCN) do not generate a circadian signal. The aim of the study was to investigate putative consequences of these deteriorations in the circadian system for animalś cognitive abilities. Hamsters were bred and kept under standardized housing conditions with food and water ad libitum and a 14l/10 D lighting regimen. Experimental animals were assigned to different groups (WT and AR) according to their activity pattern obtained by means of infrared motion sensors. Before the experiments, the animals were given to develop a dominant-subordinate relationship in a dyadic encounter. Experiment 1 dealt with individual recognition of social rank. Subordinate and dominant hamsters were tested in an open arena for their behavioral responses towards a familiar (known from the agonistic encounters) or an unfamiliar hamster (from another agonistic encounter) which had the same or an opposite social rank. The investigation time depended on the social rank of the WT subject hamster and its familiarity with the stimulus animal. Both subordinate and dominant WT hamsters preferred an unfamiliar subordinate stimulus animal. In contrast, neither subordinate nor dominant AR hamsters preferred any of the stimulus animals. Thus, disruptions in circadian

  9. Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Yu Bo

    2017-01-01

    Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

  10. Higher integrability of solutions to generalized Stokes system under perfect slip boundary conditions

    Czech Academy of Sciences Publication Activity Database

    Mácha, Václav; Tichý, J.

    2014-01-01

    Roč. 16, č. 4 (2014), s. 823-845 ISSN 1422-6928 R&D Projects: GA ČR GA201/09/0917 Institutional support: RVO:67985840 Keywords : generalized Stokes system * perfect slip boundary conditions * Lq theory Subject RIV: BA - General Math ematics Impact factor: 1.186, year: 2014 http://link.springer.com/article/10.1007%2Fs00021-014-0190-5

  11. Blow-up analysis for a system of heat equations coupled through a nonlinear boundary condition

    DEFF Research Database (Denmark)

    Pedersen, M.; Lin, Zhigui

    2001-01-01

    Consider the system of heat equations uit - Δui = 0 (i = 1 , . . . , k, uk+i := u1) in Ω x (0, T) coupled through nonlinear boundary conditions ∂ui/∂η = up1i+1 on ∂Ω x [0, T). The upper and lower bounds of the blow-up rate is derived. © 2000 Elsevier Science Ltd. All rights reserved....

  12. Monotone methods for solving a boundary value problem of second order discrete system

    Directory of Open Access Journals (Sweden)

    Wang Yuan-Ming

    1999-01-01

    Full Text Available A new concept of a pair of upper and lower solutions is introduced for a boundary value problem of second order discrete system. A comparison result is given. An existence theorem for a solution is established in terms of upper and lower solutions. A monotone iterative scheme is proposed, and the monotone convergence rate of the iteration is compared and analyzed. The numerical results are given.

  13. Stokes system with solution-dependent threshold slip boundary conditions: Analysis, approximation and implementation

    Czech Academy of Sciences Publication Activity Database

    Haslinger, Jaroslav; Kučera, R.; Šátek, V.

    2017-01-01

    Roč. 22, October 2017 (2017), s. 1-14 ISSN 1081-2865 R&D Projects: GA MŠk LQ1602; GA ČR(CZ) GA17-01747S Institutional support: RVO:68145535 Keywords : Stokes system * threshold slip boundary conditions * solution dependent slip function Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 2.953, year: 2016 http://journals.sagepub.com/doi/abs/10.1177/1081286517716222

  14. Stokes system with solution-dependent threshold slip boundary conditions: Analysis, approximation and implementation

    Czech Academy of Sciences Publication Activity Database

    Haslinger, Jaroslav; Kučera, R.; Šátek, V.

    2017-01-01

    Roč. 22, October 2017 (2017), s. 1-14 ISSN 1081-2865 R&D Projects: GA MŠk LQ1602; GA ČR(CZ) GA17-01747S Institutional support: RVO:68145535 Keywords : Stokes system * threshold slip boundary conditions * solution dependent slip function Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 2.953, year: 2016 http:// journals .sagepub.com/doi/abs/10.1177/1081286517716222

  15. The incompressible limit of the full Navier-Stokes-Fourier system on domains with rough boundaries

    Czech Academy of Sciences Publication Activity Database

    Bucur, D.; Feireisl, Eduard

    2009-01-01

    Roč. 10, č. 5 (2009), s. 3203-3229 ISSN 1468-1218 R&D Projects: GA AV ČR(CZ) IAA100190606; GA MŠk LC06052 Institutional research plan: CEZ:AV0Z10190503 Keywords : low Mach number * Navier-Stokes-Fourier system * rough boundary Subject RIV: BA - General Mathematics Impact factor: 2.381, year: 2009

  16. Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

    Directory of Open Access Journals (Sweden)

    Andreas Maier

    2010-01-01

    Full Text Available In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngectomized patients with cancer of the larynx or hypopharynx and 49 German patients who had suffered from oral cancer. The speech recognition provides the percentage of correctly recognized words of a sequence, that is, the word recognition rate. Automatic evaluation was compared to perceptual ratings by a panel of experts and to an age-matched control group. Both patient groups showed significantly lower word recognition rates than the control group. Automatic speech recognition yielded word recognition rates which complied with experts' evaluation of intelligibility on a significant level. Automatic speech recognition serves as a good means with low effort to objectify and quantify the most important aspect of pathologic speech—the intelligibility. The system was successfully applied to voice and speech disorders.

  17. Analysis of the susceptibility in a fluid system with Neumann – plus boundary conditions

    Directory of Open Access Journals (Sweden)

    Djondjorov Peter

    2018-01-01

    Full Text Available The behaviour of the local and total susceptibilities of a fluid system bounded by different surfaces is studied in the framework of the Ginsburg-Landau Ising type model. The case of a plain geometry, Neumann-infinity boundary conditions under variations of the temperature and an external ordering field is considered. Exact analytic expressions for the order parameter, local and total susceptibilities in such a system are presented. They are used to analyse the phase behaviour of fluids confined in regions close to the bulk critical point of the respective infinite system.

  18. Object Recognition System-on-Chip Using the Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Houzet Dominique

    2005-01-01

    Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

  19. An automatic speech recognition system with speaker-independent identification support

    Science.gov (United States)

    Caranica, Alexandru; Burileanu, Corneliu

    2015-02-01

    The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.

  20. Boundary-equilibrium bifurcations in piecewise-smooth slow-fast systems.

    Science.gov (United States)

    Kowalczyk, P; Glendinning, P

    2011-06-01

    In this paper we study the qualitative dynamics of piecewise-smooth slow-fast systems (singularly perturbed systems) which are everywhere continuous. We consider phase space topology of systems with one-dimensional slow dynamics and one-dimensional fast dynamics. The slow manifold of the reduced system is formed by a piecewise-continuous curve, and the differentiability is lost across the switching surface. In the full system the slow manifold is no longer continuous, and there is an O(ɛ) discontinuity across the switching manifold, but the discontinuity cannot qualitatively alter system dynamics. Revealed phase space topology is used to unfold qualitative dynamics of planar slow-fast systems with an equilibrium point on the switching surface. In this case the local dynamics corresponds to so-called boundary-equilibrium bifurcations, and four qualitative phase portraits are uncovered. Our results are then used to investigate the dynamics of a box model of a thermohaline circulation, and the presence of a boundary-equilibrium bifurcation of a fold type is shown.

  1. Boundary-spanning actors in complex adaptive governance systems: The case of multisectoral nutrition.

    Science.gov (United States)

    Pelletier, David; Gervais, Suzanne; Hafeez-Ur-Rehman, Hajra; Sanou, Dia; Tumwine, Jackson

    2017-10-10

    A growing literature highlights complexity of policy implementation and governance in global health and argues that the processes and outcomes of policies could be improved by explicitly taking this complexity into account. Yet there is a paucity of studies exploring how this can be achieved in everyday practice. This study documents the strategies, tactics, and challenges of boundary-spanning actors working in 4 Sub-Saharan Africa countries who supported the implementation of multisectoral nutrition as part of the African Nutrition Security Partnership in Burkina Faso, Mali, Ethiopia, and Uganda. Three action researchers were posted to these countries during the final 2 years of the project to help the government and its partners implement multisectoral nutrition and document the lessons. Prospective data were collected through participant observation, end-line semistructured interviews, and document analysis. All 4 countries made significant progress despite a wide range of challenges at the individual, organizational, and system levels. The boundary-spanning actors and their collaborators deployed a wide range of strategies but faced significant challenges in playing these unconventional roles. The study concludes that, under the right conditions, intentional boundary spanning can be a feasible and acceptable practice within a multisectoral, complex adaptive system in low- and middle-income countries. © 2017 The Authors. The International Journal of Health Planning and Management Published by John Wiley & Sons Ltd.

  2. Computer versus paper system for recognition and management of sepsis in surgical intensive care.

    Science.gov (United States)

    Croft, Chasen A; Moore, Frederick A; Efron, Philip A; Marker, Peggy S; Gabrielli, Andrea; Westhoff, Lynn S; Lottenberg, Lawrence; Jordan, Janeen; Klink, Victoria; Sailors, R Matthew; McKinley, Bruce A

    2014-02-01

    A system to provide surveillance, diagnosis, and protocolized management of surgical intensive care unit (SICU) sepsis was undertaken as a performance improvement project. A system for sepsis management was implemented for SICU patients using paper followed by a computerized system. The hypothesis was that the computerized system would be associated with improved process and outcomes. A system was designed to provide early recognition and guide patient-specific management of sepsis including (1) modified early warning signs-sepsis recognition score (MEWS-SRS; summative point score of ranges of vital signs, mental status, white blood cell count; after every 4 hours) by bedside nurse; (2) suspected site assessment (vascular access, lung, abdomen, urinary tract, soft tissue, other) at bedside by physician or extender; (3) sepsis management protocol (replicable, point-of-care decisions) at bedside by nurse, physician, and extender. The system was implemented first using paper and then a computerized system. Sepsis severity was defined using standard criteria. In January to May 2012, a paper system was used to manage 77 consecutive sepsis encounters (3.9 ± 0.5 cases per week) in 65 patients (77% male; age, 53 ± 2 years). In June to December 2012, a computerized system was used to manage 132 consecutive sepsis encounters (4.4 ± 0.4 cases per week) in 119 patients (63% male; age, 58 ± 2 years). MEWS-SRS elicited 683 site assessments, and 201 had sepsis diagnosis and protocol management. The predominant site of infection was abdomen (paper, 58%; computer, 53%). Recognition of early sepsis tended to occur more using the computerized system (paper, 23%; computer, 35%). Hospital mortality rate for surgical ICU sepsis (paper, 20%; computer, 14%) was less with the computerized system. A computerized sepsis management system improves care process and outcome. Early sepsis is recognized and managed with greater frequency compared with severe sepsis or septic shock. The system

  3. Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

    Science.gov (United States)

    Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

    2016-10-20

    Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

  4. An Automatic Traffic Sign Detection and Recognition System Based on Colour Segmentation, Shape Matching, and SVM

    Directory of Open Access Journals (Sweden)

    Safat B. Wali

    2015-01-01

    Full Text Available The main objective of this study is to develop an efficient TSDR system which contains an enriched dataset of Malaysian traffic signs. The developed technique is invariant in variable lighting, rotation, translation, and viewing angle and has a low computational time with low false positive rate. The development of the system has three working stages: image preprocessing, detection, and recognition. The system demonstration using a RGB colour segmentation and shape matching followed by support vector machine (SVM classifier led to promising results with respect to the accuracy of 95.71%, false positive rate (0.9%, and processing time (0.43 s. The area under the receiver operating characteristic (ROC curves was introduced to statistically evaluate the recognition performance. The accuracy of the developed system is relatively high and the computational time is relatively low which will be helpful for classifying traffic signs especially on high ways around Malaysia. The low false positive rate will increase the system stability and reliability on real-time application.

  5. Multiresolution stroke sketch adaptive representation and neural network processing system for gray-level image recognition

    Science.gov (United States)

    Meystel, Alexander M.; Rybak, Ilya A.; Bhasin, Sanjay

    1992-11-01

    This paper describes a method for multiresolutional representation of gray-level images as hierarchial sets of strokes characterizing forms of objects with different degrees of generalization depending on the context of the image. This method transforms the original image into a hierarchical graph which allows for efficient coding in order to store, retrieve, and recognize the image. The method which is described is based upon finding the resolution levels for each image which minimizes the computations required. This becomes possible because of the use of a special image representation technique called Multiresolutional Attentional Representation for Recognition, based upon a feature which the authors call a stroke. This feature turns out to be efficient in the process of finding the appropriate system of resolutions and construction of the relational graph. Multiresolutional Attentional Representation for Recognition (MARR) is formed by a multi-layer neural network with recurrent inhibitory connections between neurons, the receptive fields of which are selectively tuned to detect the orientation of local contrasts in parts of the image with appropriate degree of generalization. This method simulates the 'coarse-to-fine' algorithm which an artist usually uses, making at attentional sketch of real images. The method, algorithms, and neural network architecture in this system can be used in many machine-vision systems with AI properties; in particular, robotic vision. We expect that systems with MARR can become a component of intelligent control systems for autonomous robots. Their architectures are mostly multiresolutional and match well with the multiple resolutions of the MARR structure.

  6. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Directory of Open Access Journals (Sweden)

    Jiangyi Qin

    Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  7. A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Shaolong Chen

    2016-01-01

    Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.

  8. Effects from magnetic boundary conditions in superconducting-magnetic proximity systems

    Directory of Open Access Journals (Sweden)

    Thomas E. Baker

    2016-05-01

    Full Text Available A superconductor-magnetic proximity system displays singlet-triplet pair correlations in the magnetization as a function of inhomogeneities of the magnetic profile. We discuss how the magnetic boundary conditions affects differently the curvature and winding number of rotating magnetizations in the three commonly used structures to generate long range triplet components: an exchange spring, a helical structure and a misaligned magnetic multilayer. We conclude that the choice of the system is dictated by the goal one wishes to achieve in designing a spintronic device but note that only the exchange spring presently offers an experimentally realizable magnetic profile that is tunable.

  9. Integration of an industrial robot with the systems for image and voice recognition

    Directory of Open Access Journals (Sweden)

    Tasevski Jovica

    2013-01-01

    Full Text Available The paper reports a solution for the integration of the industrial robot ABB IRB140 with the system for automatic speech recognition (ASR and the system for computer vision. The robot has the task to manipulate the objects placed randomly on a pad lying on a table, and the computer vision system has to recognize their characteristics (shape, dimension, color, position, and orientation. The ASR system has a task to recognize human speech and use it as a command to the robot, so the robot can manipulate the objects. [Projekat Ministarstva nauke Republike Srbije, br. III44008: Design of Robots as Assistive Technology for the Treatment of Children with Developmental Disorders i br. TR32035: Development of Dialogue Systems for Serbian and other South Slavic Languages

  10. Sistema audiovisual para reconocimiento de comandos Audiovisual system for recognition of commands

    Directory of Open Access Journals (Sweden)

    Alexander Ceballos

    2011-08-01

    Full Text Available Se presenta el desarrollo de un sistema automático de reconocimiento audiovisual del habla enfocado en el reconocimiento de comandos. La representación del audio se realizó mediante los coeficientes cepstrales de Mel y las primeras dos derivadas temporales. Para la caracterización del vídeo se hizo seguimiento automático de características visuales de alto nivel a través de toda la secuencia. Para la inicialización automática del algoritmo se emplearon transformaciones de color y contornos activos con información de flujo del vector gradiente ("GVF snakes" sobre la región labial, mientras que para el seguimiento se usaron medidas de similitud entre vecindarios y restricciones morfológicas definidas en el estándar MPEG-4. Inicialmente, se presenta el diseño del sistema de reconocimiento automático del habla, empleando únicamente información de audio (ASR, mediante Modelos Ocultos de Markov (HMMs y un enfoque de palabra aislada; posteriormente, se muestra el diseño de los sistemas empleando únicamente características de vídeo (VSR, y empleando características de audio y vídeo combinadas (AVSR. Al final se comparan los resultados de los tres sistemas para una base de datos propia en español y francés, y se muestra la influencia del ruido acústico, mostrando que el sistema de AVSR es más robusto que ASR y VSR.We present the development of an automatic audiovisual speech recognition system focused on the recognition of commands. Signal audio representation was done using Mel cepstral coefficients and their first and second order time derivatives. In order to characterize the video signal, a set of high-level visual features was tracked throughout the sequences. Automatic initialization of the algorithm was performed using color transformations and active contour models based on Gradient Vector Flow (GVF Snakes on the lip region, whereas visual tracking used similarity measures across neighborhoods and morphological

  11. Challenges and Specifications for Robust Face and Gait Recognition Systems for Surveillance Application

    Directory of Open Access Journals (Sweden)

    BUCIU Ioan

    2014-05-01

    Full Text Available Automated person recognition (APR based on biometric signals addresses the process of automatically recognize a person according to his physiological traits (face, voice, iris, fingerprint, ear shape, body odor, electroencephalogram – EEG, electrocardiogram, or hand geometry, or behavioural patterns (gait, signature, hand-grip, lip movement. The paper aims at briefly presenting the current challenges for two specific non-cooperative biometric approaches, namely face and gait biometrics as well as approaches that consider combination of the two in the attempt of a more robust system for accurate APR, in the context of surveillance application. Open problems from both sides are also pointed out.

  12. Feature Selection Software to Improve Accuracy and Reduce Cost in Automated Recognition Systems

    Czech Academy of Sciences Publication Activity Database

    Somol, Petr

    2011-01-01

    Roč. 2011, č. 84 (2011), s. 54-54 ISSN 0926-4981 R&D Projects: GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection * software library * machine learning Subject RIV: BD - Theory of Information http:// library .utia.cas.cz/separaty/2011/RO/somol-feature selection software to improve accuracy and reduce cost in automated recognition systems.pdf

  13. Multimodal System Based on Electrooculography and Voice Recognition to Control a Robot Arm

    OpenAIRE

    José A. Martínez; Andrés Úbeda; Eduardo Iáñez; Jose M. Azorín; Carlos Perez-Vidal

    2013-01-01

    People with severe motor disorders cannot use their arms and/or hands to interact with the environment. In such cases, a human‐machine interface can be used to allow these people to perform activities of daily life. Voice recognition would be the best method to control a device devoted to help with these tasks, but this method is very dependent on the background noise and, under certain circumstances, it cannot be used successfully. In this sense, other methods must be included in the system ...

  14. An Examination of the Effect of Boundary Layer Ingestion on Turboelectric Distributed Propulsion Systems

    Science.gov (United States)

    Felder, James L.; Kim, Huyn Dae; Brown, Gerald V.; Chu, Julio

    2011-01-01

    A Turboelectric Distributed Propulsion (TeDP) system differs from other propulsion systems by the use of electrical power to transmit power from the turbine to the fan. Electrical power can be efficiently transmitted over longer distances and with complex topologies. Also the use of power inverters allows the generator and motors speeds to be independent of one another. This decoupling allows the aircraft designer to place the core engines and the fans in locations most advantageous for each. The result can be very different installation environments for the different devices. Thus the installation effects on this system can be quite different than conventional turbofans where the fan and core both see the same installed environments. This paper examines a propulsion system consisting of two superconducting generators, each driven by a turboshaft engine located so that their inlets ingest freestream air, superconducting electrical transmission lines, and an array of superconducting motor driven fan positioned across the upper/rear fuselage area of a hybrid wing body aircraft in a continuous nacelle that ingests all of the upper fuselage boundary layer. The effect of ingesting the boundary layer on the design of the system with a range of design pressure ratios is examined. Also the impact of ingesting the boundary layer on off-design performance is examined. The results show that when examining different design fan pressure ratios it is important to recalculate of the boundary layer mass-average Pt and MN up the height for each inlet height during convergence of the design point for each fan design pressure ratio examined. Correct estimation of off-design performance is dependent on the height of the column of air measured from the aircraft surface immediately prior to any external diffusion that will flow through the fan propulsors. The mass-averaged Pt and MN calculated for this column of air determine the Pt and MN seen by the propulsor inlet. Since the height

  15. Design and implementation of a real time and train less eye state recognition system

    Science.gov (United States)

    Dehnavi, Mohammad; Eshghi, Mohammad

    2012-12-01

    Eye state recognition is one of the main stages of many image processing systems such as driver drowsiness detection system and closed-eye photo correction. Driver drowsiness is one of the main causes in the road accidents around the world. In these circumstances, a fast and accurate driver drowsiness detection system can prevent these accidents. In this article, we proposed a fast algorithm for determining the state of an eye, based on the difference between iris/pupil color and white area of the eye. In the proposed method, vertical projection is used to determine the eye state. This method is suitable for hardware implementation to be used in a fast and online drowsiness detection system. The proposed method, along with other needed preprocessing stages, is implemented on Field Programmable Gate Array chips. The results show that the proposed low-complex algorithm has sufficient speed and accuracy, to be used in real-world conditions.

  16. Development of a landmark recognition system for the posture measurement of mobile robots

    International Nuclear Information System (INIS)

    Lee, Sang Ryong; Kwon, Seung Man

    1993-01-01

    A landmark recognition system, consisting of retroreflective landmarks, a CCD camera, a strobe unit, an image processing board, and processing software, has been developed to solve the problem of the posture (position and orientation) identification of mobile robots in manufacturing environments. The binary image processing technique instead of gray image technique has been adapted in this system to perform the fast posture measurement of the robots. The experimental results demonstrated real-time measurement capability of this system while maintaining good reliability and reasonable accuracy. A camera calibration technique has been described to reduce the effects of unwanted measurement error sources. The system after camera calibration procedure has demonstrated enhanced performance in terms of error component in posture measurement. (Author)

  17. A Computationally Efficient Mel-Filter Bank VAD Algorithm for Distributed Speech Recognition Systems

    Directory of Open Access Journals (Sweden)

    Vlaj Damjan

    2005-01-01

    Full Text Available This paper presents a novel computationally efficient voice activity detection (VAD algorithm and emphasizes the importance of such algorithms in distributed speech recognition (DSR systems. When using VAD algorithms in telecommunication systems, the required capacity of the speech transmission channel can be reduced if only the speech parts of the signal are transmitted. A similar objective can be adopted in DSR systems, where the nonspeech parameters are not sent over the transmission channel. A novel approach is proposed for VAD decisions based on mel-filter bank (MFB outputs with the so-called Hangover criterion. Comparative tests are presented between the presented MFB VAD algorithm and three VAD algorithms used in the G.729, G.723.1, and DSR (advanced front-end Standards. These tests were made on the Aurora 2 database, with different signal-to-noise (SNRs ratios. In the speech recognition tests, the proposed MFB VAD outperformed all the three VAD algorithms used in the standards by relative (G.723.1 VAD, by relative (G.729 VAD, and by relative (DSR VAD in all SNRs.

  18. A Computationally Efficient Mel-Filter Bank VAD Algorithm for Distributed Speech Recognition Systems

    Science.gov (United States)

    Vlaj, Damjan; Kotnik, Bojan; Horvat, Bogomir; Kačič, Zdravko

    2005-12-01

    This paper presents a novel computationally efficient voice activity detection (VAD) algorithm and emphasizes the importance of such algorithms in distributed speech recognition (DSR) systems. When using VAD algorithms in telecommunication systems, the required capacity of the speech transmission channel can be reduced if only the speech parts of the signal are transmitted. A similar objective can be adopted in DSR systems, where the nonspeech parameters are not sent over the transmission channel. A novel approach is proposed for VAD decisions based on mel-filter bank (MFB) outputs with the so-called Hangover criterion. Comparative tests are presented between the presented MFB VAD algorithm and three VAD algorithms used in the G.729, G.723.1, and DSR (advanced front-end) Standards. These tests were made on the Aurora 2 database, with different signal-to-noise (SNRs) ratios. In the speech recognition tests, the proposed MFB VAD outperformed all the three VAD algorithms used in the standards by [InlineEquation not available: see fulltext.] relative (G.723.1 VAD), by [InlineEquation not available: see fulltext.] relative (G.729 VAD), and by [InlineEquation not available: see fulltext.] relative (DSR VAD) in all SNRs.

  19. A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.

    Science.gov (United States)

    Wu, Minglin; Zhang, Sheng; Dong, Yuhan

    2016-10-20

    In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

  20. Fluid pipeline system leak detection based on neural network and pattern recognition

    International Nuclear Information System (INIS)

    Tang Xiujia

    1998-01-01

    The mechanism of the stress wave propagation along the pipeline system of NPP, caused by turbulent ejection from pipeline leakage, is researched. A series of characteristic index are described in time domain or frequency domain, and compress numerical algorithm is developed for original data compression. A back propagation neural networks (BPNN) with the input matrix composed by stress wave characteristics in time domain or frequency domain is first proposed to classify various situations of the pipeline, in order to detect the leakage in the fluid flow pipelines. The capability of the new method had been demonstrated by experiments and finally used to design a handy instrument for the pipeline leakage detection. Usually a pipeline system has many inner branches and often in adjusting dynamic condition, it is difficult for traditional pipeline diagnosis facilities to identify the difference between inner pipeline operation and pipeline fault. The author first proposed pipeline wave propagation identification by pattern recognition to diagnose pipeline leak. A series of pattern primitives such as peaks, valleys, horizon lines, capstan peaks, dominant relations, slave relations, etc., are used to extract features of the negative pressure wave form. The context-free grammar of symbolic representation of the negative wave form is used, and a negative wave form parsing system with application to structural pattern recognition based on the representation is first proposed to detect and localize leaks of the fluid pipelines

  1. A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

    Directory of Open Access Journals (Sweden)

    Minglin Wu

    2016-10-01

    Full Text Available In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

  2. A food recognition system for diabetic patients based on an optimized bag-of-features model.

    Science.gov (United States)

    Anthimopoulos, Marios M; Gianola, Lauro; Scarnato, Luca; Diem, Peter; Mougiakakou, Stavroula G

    2014-07-01

    Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the bag-of-features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

  3. Building the School Attendance Boundary Information System (SABINS): Collecting, Processing, and Modeling K to 12 Educational Geography.

    Science.gov (United States)

    Saporito, Salvatore; Van Riper, David; Wakchaure, Ashwini

    2013-01-01

    The School Attendance Boundary Information System is a social science data infrastructure project that assembles, processes, and distributes spatial data delineating K through 12 th grade school attendance boundaries for thousands of school districts in U.S. Although geography is a fundamental organizing feature of K to 12 education, until now school attendance boundary data have not been made readily available on a massive basis and in an easy-to-use format. The School Attendance Boundary Information System removes these barriers by linking spatial data delineating school attendance boundaries with tabular data describing the demographic characteristics of populations living within those boundaries. This paper explains why a comprehensive GIS database of K through 12 school attendance boundaries is valuable, how original spatial information delineating school attendance boundaries is collected from local agencies, and techniques for modeling and storing the data so they provide maximum flexibility to the user community. An important goal of this paper is to share the techniques used to assemble the SABINS database so that local and state agencies apply a standard set of procedures and models as they gather data for their regions.

  4. Framework to Define Structure and Boundaries of Complex Health Intervention Systems: The ALERT Project

    Directory of Open Access Journals (Sweden)

    Elena Boriani

    2017-07-01

    Full Text Available Health intervention systems are complex and subject to multiple variables in different phases of implementation. This constitutes a concrete challenge for the application of translational science in real life. Complex systems as health-oriented interventions call for interdisciplinary approaches with carefully defined system boundaries. Exploring individual components of such systems from different viewpoints gives a wide overview and helps to understand the elements and the relationships that drive actions and consequences within the system. In this study, we present an application and assessment of a framework with focus on systems and system boundaries of interdisciplinary projects. As an example on how to apply our framework, we analyzed ALERT [an integrated sensors and biosensors’ system (BEST aimed at monitoring the quality, health, and traceability of the chain of the bovine milk], a multidisciplinary and interdisciplinary project based on the application of measurable biomarkers at strategic points of the milk chain for improved food security (including safety, human, and ecosystem health (1. In fact, the European food safety framework calls for science-based support to the primary producers’ mandate for legal, scientific, and ethical responsibility in food supply. Because of its multidisciplinary and interdisciplinary approach involving human, animal, and ecosystem health, ALERT can be considered as a One Health project. Within the ALERT context, we identified the need to take into account the main actors, interactions, and relationships of stakeholders to depict a simplified skeleton of the system. The framework can provide elements to highlight how and where to improve the project development when project evaluations are required.

  5. [Research on Multi-Spectral Target Recognition System Based on the Magneto-Optical Modulation].

    Science.gov (United States)

    Yan, Xiao-yan; Qin, Jian-min; Qiao, Ji-pin

    2016-03-01

    The technology of target recognition based on characteristic multi-spectrum has many advantages, such as strong detection capability and discriminating capability of target species. But there are some problems, it requires that you obtain the background spectrum as a priori knowledge, and it requires that the change of background spectrum is small with time. Thereby its application of real-time object recognition is limited in the new environment, or the complex environment. Based on magneto-optical modulation and characteristic multi-spectrum the method is designed, and the target is identified without prior access to the background spectrum. In order to achieve the function of the target information in the one acquisition time for tested, compared to conventional methods in terms of target detection, it's adaptability is better than before on the battlefield, and it is of more practical significance. Meanwhile, the magneto-optical modulator is used to suppress the interference of stray light background, thereby improving the probability of target recognition. Since the magneto-optical modulation provides incremental iterative target spectral information, therefore, even if the unknown background spectrum or background spectrum change is large, it can significantly improve the recognition accuracy of information through an iterative target spectrum. Different test targets back shimmering light intensity and background intensity values were analyzed during experiments, results showed that three targets for linearly polarized reflectance modulation is significantly stronger than the background. And it was of great influence to visible imaging target identification when measured target used camouflage color, but the system of polarization modulation type can still recognize target well. On this basis, the target range within 0.5 km x 2 km multi-wavelength characteristics of the target species were identified. When using three characteristic wavelengths, the

  6. Determining system boundaries on commercial broiler chicken production system using ISO 14040/14044 guideline: A case Study

    Science.gov (United States)

    Sidek, ‘A. A.; Suffian, S. A.; Al-Hazza, M. H. F.; Yusof, H. M.

    2018-01-01

    The demand of poultry product in Malaysia market shows an escalation throughout the year and expected to increase in the future. The expansion of poultry production has led to environmental concern in relation to their operational impact to environmentAt present, assessment of waste management of poultry production in Malaysia is lacking. A case study research was conducted in a commercial broiler farm to identify and assess the system boundaries in the lifecycle supply chain of broiler chicken production using ISO 14040/44 guidelines. ISO 14040/44 standard includes Life Cycle Assessment (LCA) framework guidelines to evaluate environmental influence associated with a product/process throughout its life span. All attributes associated with broiler operation is defined and the system boundaries is determined to identify possible inputs and outputs in the case study. This paper discuss the initial stage in the LCA process, which set the context of the research and prepare for the stage of Life Cycle Inventory.

  7. An optimal control method for fluid structure interaction systems via adjoint boundary pressure

    Science.gov (United States)

    Chirco, L.; Da Vià, R.; Manservisi, S.

    2017-11-01

    In recent year, in spite of the computational complexity, Fluid-structure interaction (FSI) problems have been widely studied due to their applicability in science and engineering. Fluid-structure interaction systems consist of one or more solid structures that deform by interacting with a surrounding fluid flow. FSI simulations evaluate the tensional state of the mechanical component and take into account the effects of the solid deformations on the motion of the interior fluids. The inverse FSI problem can be described as the achievement of a certain objective by changing some design parameters such as forces, boundary conditions and geometrical domain shapes. In this paper we would like to study the inverse FSI problem by using an optimal control approach. In particular we propose a pressure boundary optimal control method based on Lagrangian multipliers and adjoint variables. The objective is the minimization of a solid domain displacement matching functional obtained by finding the optimal pressure on the inlet boundary. The optimality system is derived from the first order necessary conditions by taking the Fréchet derivatives of the Lagrangian with respect to all the variables involved. The optimal solution is then obtained through a standard steepest descent algorithm applied to the optimality system. The approach presented in this work is general and could be used to assess other objective functionals and controls. In order to support the proposed approach we perform a few numerical tests where the fluid pressure on the domain inlet controls the displacement that occurs in a well defined region of the solid domain.

  8. Experiments on the flow field physics of confluent boundary layers for high-lift systems

    Science.gov (United States)

    Nelson, Robert C.; Thomas, F. O.; Chu, H. C.

    1994-01-01

    The use of sub-scale wind tunnel test data to predict the behavior of commercial transport high lift systems at in-flight Reynolds number is limited by the so-called 'inverse Reynolds number effect'. This involves an actual deterioration in the performance of a high lift device with increasing Reynolds number. A lack of understanding of the relevant flow field physics associated with numerous complicated viscous flow interactions that characterize flow over high-lift devices prohibits computational fluid dynamics from addressing Reynolds number effects. Clearly there is a need for research that has as its objective the clarification of the fundamental flow field physics associated with viscous effects in high lift systems. In this investigation, a detailed experimental investigation is being performed to study the interaction between the slat wake and the boundary layer on the primary airfoil which is known as a confluent boundary layer. This little-studied aspect of the multi-element airfoil problem deserves special attention due to its importance in the lift augmentation process. The goal of this research is is to provide an improved understanding of the flow physics associated with high lift generation. This process report will discuss the status of the research being conducted at the Hessert Center for Aerospace Research at the University of Notre Dame. The research is sponsored by NASA Ames Research Center under NASA grant NAG2-905. The report will include a discussion of the models that have been built or that are under construction, a description of the planned experiments, a description of a flow visualization apparatus that has been developed for generating colored smoke for confluent boundary layer studies and some preliminary measurements made using our new 3-component fiber optic LDV system.

  9. Object recognition algorithm based on inexact graph matching and its application in a color vision system for recognition of electronic components on PCBs

    Science.gov (United States)

    Kroupnova, Natalia H.; Korsten, Maarten J.

    1997-04-01

    The paper describes a framework for fast objects recognition and its application in a system for recognition of certain electronic components on printed circuit boards (PCB) for recycling purposes. Objects in the DB and in the image are represented as attributed graph, where vertices are regions with attributes (color, shape) and edges are spatial relations between the regions (adjacent, surrounds). The task of finding model objects in the input data thus becomes a problem of inexact subgraph isomorphism finding. The suggested algorithm finds all the occurrences of all model graphs in the input graph in the presence of the low-level processing errors and model uncertainty. Using the ideas of inexact network algorithm (INA) we build a network from the model graphs, so that in cases when the models share identical substructures these substructures have to be matched only once. Because different models share the same substructures mostly in case when they belong to the same more general class, we incorporate the possibility of attribute refining in our model network. To further speed up the matching, we introduce the notion of a `key' vertex, so that recognition goes from easily recognizable substructures to more ambiguous ones. The algorithm was applied to real images of PCB's. The results show the effectiveness of INA and suggested modifications in this application.

  10. Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

    OpenAIRE

    Andreas Maier; Tino Haderlein; Florian Stelzle; Elmar Nöth; Emeka Nkenke; Frank Rosanowski; Anne Schützenberger; Maria Schuster

    2010-01-01

    In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngect...

  11. Topology of phase boundaries for oil/brine/surfactant systems and its relationship to oil recovery

    Energy Technology Data Exchange (ETDEWEB)

    Bourrel, M.; Chambu, C.; Schechter, R.S.; Wade, W.H.

    1982-02-01

    Surfactant/oil/water phase diagrams have become the most important screening tool used to select microemulsion systems for enhanced oil recovery. It is shown that the phase diagrams can be made to take on different configurations depending on the alcohol cosurfactant, the salinity, the impurities present in the surfactant, and the dispersity of the surfactant mixture. Besides the importance of the phase boundary shape, this study provides further insight into factors determining the height of the binodal surface on the pseudoternary phase diagram. Results show the effect of salinity as well as the surfactant, alcohol, and hydrocarbon types on the height of the binodal surface. 24 refs.

  12. A freely-available authoring system for browser-based CALL with speech recognition

    Directory of Open Access Journals (Sweden)

    Myles O'Brien

    2017-06-01

    Full Text Available A system for authoring browser-based CALL material incorporating Google speech recognition has been developed and made freely available for download. The system provides a teacher with a simple way to set up CALL material, including an optional image, sound or video, which will elicit spoken (and/or typed answers from the user and check them against a list of specified permitted answers, giving feedback with hints when necessary. The teacher needs no HTML or Javascript expertise, just the facilities and ability to edit text files and upload to the Internet. The structure and functioning of the system are explained in detail, and some suggestions are given for practical use. Finally, some of its limitations are described.

  13. An open and configurable embedded system for EMG pattern recognition implementation for artificial arms.

    Science.gov (United States)

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

    Pattern recognition (PR) based on electromyographic (EMG) signals has been developed for multifunctional artificial arms for decades. However, assessment of EMG PR control for daily prosthesis use is still limited. One of the major barriers is the lack of a portable and configurable embedded system to implement the EMG PR control. This paper aimed to design an open and configurable embedded system for EMG PR implementation so that researchers can easily modify and optimize the control algorithms upon our designed platform and test the EMG PR control outside of the lab environments. The open platform was built on an open source embedded Linux Operating System running a high-performance Gumstix board. Both the hardware and software system framework were openly designed. The system was highly flexible in terms of number of inputs/outputs and calibration interfaces used. Such flexibility enabled easy integration of our embedded system with different types of commercialized or prototypic artificial arms. Thus far, our system was portable for take-home use. Additionally, compared with previously reported embedded systems for EMG PR implementation, our system demonstrated improved processing efficiency and high system precision. Our long-term goals are (1) to develop a wearable and practical EMG PR-based control for multifunctional artificial arms, and (2) to quantify the benefits of EMG PR-based control over conventional myoelectric prosthesis control in a home setting.

  14. Evaluation of tunnel sidewall boundary-layer-control systems for high-lift airfoil testing

    Science.gov (United States)

    Paschal, K.; Goodman, W.; Mcghee, R.; Walker, B.; Wilcox, Peter A.

    1991-01-01

    An experimental study was conducted in the NASA Langley Low-Turbulence Pressure Tunnel to evaluate a suction sidewall boundary-layer-control (BLC) technique used in testing 2D high-lift airfoils. Sidewall BLC is required to maintain spanwise two-dimensionality of the flow over the airfoil at large angles of attack. A supercritical-type high-lift air-foil, equipped with a double-slotted flap and a leading-edge slat, was used for the study which was conducted at a Mach number of 0.2 and Reynolds numbers based on chord of 9 and 16 million. The sidewall BLC technique, which features distributed suction through porous endplates connected to a venting system, was able to control sidewall boundary-layer separation and maintain two-dimensional flow over the high-lift configuration for both Reynolds numbers tested. Discussions on porous endplate optimization and effects of suction on section lift are presented. Results obtained with the suction system were also compared with previous data obtained with a tangential blowing BLC system for the same high-lift configuration.

  15. Pattern Recognition via the Toll-Like Receptor System in the Human Female Genital Tract

    Directory of Open Access Journals (Sweden)

    Kaei Nasu

    2010-01-01

    Full Text Available The mucosal surface of the female genital tract is a complex biosystem, which provides a barrier against the outside world and participates in both innate and acquired immune defense systems. This mucosal compartment has adapted to a dynamic, non-sterile environment challenged by a variety of antigenic/inflammatory stimuli associated with sexual intercourse and endogenous vaginal microbiota. Rapid innate immune defenses against microbial infection usually involve the recognition of invading pathogens by specific pattern-recognition receptors recently attributed to the family of Toll-like receptors (TLRs. TLRs recognize conserved pathogen-associated molecular patterns (PAMPs synthesized by microorganisms including bacteria, fungi, parasites, and viruses as well as endogenous ligands associated with cell damage. Members of the TLR family, which includes 10 human TLRs identified to date, recognize distinct PAMPs produced by various bacterial, fungal, and viral pathogens. The available literature regarding the innate immune system of the female genital tract during human reproductive processes was reviewed in order to identify studies specifically related to the expression and function of TLRs under normal as well as pathological conditions. Increased understanding of these molecules may provide insight into site-specific immunoregulatory mechanisms in the female reproductive tract.

  16. Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

    Science.gov (United States)

    Chherawala, Youssouf; Roy, Partha Pratim; Cheriet, Mohamed

    2016-12-01

    The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than a straightforward comparison based on the recognition rate. In this paper, we propose a framework for feature set evaluation based on a collaborative setting. We use a weighted vote combination of recurrent neural network (RNN) classifiers, each trained with a particular feature set. This combination is modeled in a probabilistic framework as a mixture model and two methods for weight estimation are described. The main contribution of this paper is to quantify the importance of feature sets through the combination weights, which reflect their strength and complementarity. We chose the RNN classifier because of its state-of-the-art performance. Also, we provide the first feature set benchmark for this classifier. We evaluated several feature sets on the IFN/ENIT and RIMES databases of Arabic and Latin script, respectively. The resulting combination model is competitive with state-of-the-art systems.

  17. A knowledge-based object recognition system for applications in the space station

    Science.gov (United States)

    Dhawan, Atam P.

    1988-01-01

    A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

  18. Magnetic field structure near the plasma boundary in helical systems and divertor tokamaks

    International Nuclear Information System (INIS)

    Nagasaki, Kazunobu; Itoh, Kimitaka

    1990-02-01

    Magnetic field structure of the scrape off layer (SOL) region in both helical systems and divertor tokamaks is studied numerically by using model fields. The connection length of the field line to the wall is calculated. In helical systems, the connection length, L, has a logarithmic dependence on the distance from the outermost magnetic surface or that from the residual magnetic islands. The effect of axisymmetric fields on the field structure is also determined. In divertor tokamaks, the connection length also has logarithmic properties near the separatrix. Even when the perturbations, which resonate to rational surfaces near the plasma boundary, are added, logarithmic properties still remain. We compare the connection length of torsatron/helical-heliotron systems with that of divertor tokamaks. It is found that the former is shorter than the latter by one order magnitude with similar aspect ratio. (author)

  19. A hybrid neural network system for prediction and recognition of promoter regions in human genome.

    Science.gov (United States)

    Chen, Chuan-Bo; Li, Tao

    2005-05-01

    This paper proposes a high specificity and sensitivity algorithm called PromPredictor for recognizing promoter regions in the human genome. PromPredictor extracts compositional features and CpG islands information from genomic sequence, feeding these features as input for a hybrid neural network system (HNN) and then applies the HNN for prediction. It combines a novel promoter recognition model, coding theory, feature selection and dimensionality reduction with machine learning algorithm. Evaluation on Human chromosome 22 was approximately 66% in sensitivity and approximately 48% in specificity. Comparison with two other systems revealed that our method had superior sensitivity and specificity in predicting promoter regions. PromPredictor is written in MATLAB and requires Matlab to run. PromPredictor is freely available at http://www.whtelecom.com/Prompredictor.htm.

  20. Collaborative non-self recognition system in S-RNase-based self-incompatibility.

    Science.gov (United States)

    Kubo, Ken-ichi; Entani, Tetsuyuki; Takara, Akie; Wang, Ning; Fields, Allison M; Hua, Zhihua; Toyoda, Mamiko; Kawashima, Shin-ichi; Ando, Toshio; Isogai, Akira; Kao, Teh-hui; Takayama, Seiji

    2010-11-05

    Self-incompatibility in flowering plants prevents inbreeding and promotes outcrossing to generate genetic diversity. In Solanaceae, a multiallelic gene, S-locus F-box (SLF), was previously shown to encode the pollen determinant in self-incompatibility. It was postulated that an SLF allelic product specifically detoxifies its non-self S-ribonucleases (S-RNases), allelic products of the pistil determinant, inside pollen tubes via the ubiquitin-26S-proteasome system, thereby allowing compatible pollinations. However, it remained puzzling how SLF, with much lower allelic sequence diversity than S-RNase, might have the capacity to recognize a large repertoire of non-self S-RNases. We used in vivo functional assays and protein interaction assays to show that in Petunia, at least three types of divergent SLF proteins function as the pollen determinant, each recognizing a subset of non-self S-RNases. Our findings reveal a collaborative non-self recognition system in plants.

  1. Contralateral comparison of wavefront-guided LASIK surgery with iris recognition versus without iris recognition using the MEL80 Excimer laser system.

    Science.gov (United States)

    Wu, Fang; Yang, Yabo; Dougherty, Paul J

    2009-05-01

    To compare outcomes in wavefront-guided LASIK performed with iris recognition software versus without iris recognition software in different eyes of the same patient. A randomised, prospective study of 104 myopic eyes of 52 patients undergoing LASIK surgery with the MEL80 excimer laser system was performed. Iris recognition software was used in one eye of each patient (study group) and not used in the other eye (control group). Higher order aberrations (HOAs), contrast sensitivity, uncorrected vision (UCV), visual acuity (VA) and corneal topography were measured and recorded pre-operatively and at one month and three months post-operatively for each eye. The mean post-operative sphere and cylinder between groups was similar, however the post-operative angles of error (AE) by refraction were significantly smaller in the study group compared to the control group both in arithmetic and absolute means (p = 0.03, p = 0.01). The mean logMAR UCV was significantly better in the study group than in the control group at one month (p = 0.01). The mean logMAR VA was significantly better in the study group than in control group at both one and three months (p = 0.01, p = 0.03). In addition, mean trefoil, total third-order aberration, total fourth-order aberration and the total scotopic root-mean-square (RMS) HOAs were significantly less in the study group than those in the control group at the third (p = 0.01, p = 0.05, p = 0.04, p = 0.02). By three months, the contrast sensitivity had recovered in both groups but the study group performed better at 2.6, 4.2 and 6.6 cpd (cycles per degree) than the control group (p = 0.01, p LASIK performed with iris recognition results in better VA, lower mean higher-order aberrations, lower refractive post-operative angles of error and better contrast sensitivity at three months post-operatively than LASIK performed without iris recognition.

  2. Automatic anatomy recognition via multiobject oriented active shape models.

    Science.gov (United States)

    Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

    2010-12-01

    This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a

  3. Facial emotion recognition system for autistic children: a feasible study based on FPGA implementation.

    Science.gov (United States)

    Smitha, K G; Vinod, A P

    2015-11-01

    Children with autism spectrum disorder have difficulty in understanding the emotional and mental states from the facial expressions of the people they interact. The inability to understand other people's emotions will hinder their interpersonal communication. Though many facial emotion recognition algorithms have been proposed in the literature, they are mainly intended for processing by a personal computer, which limits their usability in on-the-move applications where portability is desired. The portability of the system will ensure ease of use and real-time emotion recognition and that will aid for immediate feedback while communicating with caretakers. Principal component analysis (PCA) has been identified as the least complex feature extraction algorithm to be implemented in hardware. In this paper, we present a detailed study of the implementation of serial and parallel implementation of PCA in order to identify the most feasible method for realization of a portable emotion detector for autistic children. The proposed emotion recognizer architectures are implemented on Virtex 7 XC7VX330T FFG1761-3 FPGA. We achieved 82.3% detection accuracy for a word length of 8 bits.

  4. Customized Computer Vision and Sensor System for Colony Recognition and Live Bacteria Counting in Agriculture

    Directory of Open Access Journals (Sweden)

    Gabriel M. ALVES

    2016-06-01

    Full Text Available This paper presents an arrangement based on a dedicated computer and charge-coupled device (CCD sensor system to intelligently allow the counting and recognition of colony formation. Microbes in agricultural environments are important catalysts of global carbon and nitrogen cycles, including the production and consumption of greenhouse gases in soil. Some microbes produce greenhouse gases such as carbon dioxide and nitrous oxide while decomposing organic matter in soil. Others consume methane from the atmosphere, helping to mitigate climate change. The magnitude of each of these processes is influenced by human activities and impacts the warming potential of Earth’s atmosphere. In this context, bacterial colony counting is important and requires sophisticated analysis methods. The method implemented in this study uses digital image processing techniques, including the Hough Transform for circular objects. The visual environment Borland Builder C++ was used for development, and a model for decision making was incorporated to aggregate intelligence. For calibration of the method a prepared illuminated chamber was used to enable analyses of the bacteria Escherichia coli, and Acidithiobacillus ferrooxidans. For validation, a set of comparisons were established between this smart method and the expert analyses. The results show the potential of this method for laboratory applications that involve the quantification and pattern recognition of bacterial colonies in solid culture environments.

  5. Numerical continuation methods for dynamical systems path following and boundary value problems

    CERN Document Server

    Krauskopf, Bernd; Galan-Vioque, Jorge

    2007-01-01

    Path following in combination with boundary value problem solvers has emerged as a continuing and strong influence in the development of dynamical systems theory and its application. It is widely acknowledged that the software package AUTO - developed by Eusebius J. Doedel about thirty years ago and further expanded and developed ever since - plays a central role in the brief history of numerical continuation. This book has been compiled on the occasion of Sebius Doedel''s 60th birthday. Bringing together for the first time a large amount of material in a single, accessible source, it is hoped that the book will become the natural entry point for researchers in diverse disciplines who wish to learn what numerical continuation techniques can achieve. The book opens with a foreword by Herbert B. Keller and lecture notes by Sebius Doedel himself that introduce the basic concepts of numerical bifurcation analysis. The other chapters by leading experts discuss continuation for various types of systems and objects ...

  6. Optimal Boundary Control of a Simplified Ericksen-Leslie System for Nematic Liquid Crystal Flows in 2 D

    Science.gov (United States)

    Cavaterra, Cecilia; Rocca, Elisabetta; Wu, Hao

    2017-06-01

    In this paper, we investigate an optimal boundary control problem for a two dimensional simplified Ericksen-Leslie system modelling the incompressible nematic liquid crystal flows. The hydrodynamic system consists of the Navier-Stokes equations for the fluid velocity coupled with a convective Ginzburg-Landau type equation for the averaged molecular orientation. The fluid velocity is assumed to satisfy a no-slip boundary condition, while the molecular orientation is subject to a time-dependent Dirichlet boundary condition that corresponds to the strong anchoring condition for liquid crystals. We first establish the existence of optimal boundary controls. Then we show that the control-to-state operator is Fréchet differentiable between appropriate Banach spaces and derive first-order necessary optimality conditions in terms of a variational inequality involving the adjoint state variables.

  7. Computational Investigation of a Boundary-Layer Ingestion Propulsion System for the Common Research Model

    Science.gov (United States)

    Blumenthal, Brennan

    2016-01-01

    This thesis will examine potential propulsive and aerodynamic benefits of integrating a boundary-layer ingestion (BLI) propulsion system with a typical commercial aircraft using the Common Research Model geometry and the NASA Tetrahedral Unstructured Software System (TetrUSS). The Numerical Propulsion System Simulation (NPSS) environment will be used to generate engine conditions for CFD analysis. Improvements to the BLI geometry will be made using the Constrained Direct Iterative Surface Curvature (CDISC) design method. Previous studies have shown reductions of up to 25% in terms of propulsive power required for cruise for other axisymmetric geometries using the BLI concept. An analysis of engine power requirements, drag, and lift coefficients using the baseline and BLI geometries coupled with the NPSS model are shown. Potential benefits of the BLI system relating to cruise propulsive power are quantified using a power balance method and a comparison to the baseline case is made. Iterations of the BLI geometric design are shown and any improvements between subsequent BLI designs presented. Simulations are conducted for a cruise flight condition of Mach 0.85 at an altitude of 38,500 feet and an angle of attack of 2deg for all geometries. A comparison between available wind tunnel data, previous computational results, and the original CRM model is presented for model verification purposes along with full results for BLI power savings. Results indicate a 14.3% reduction in engine power requirements at cruise for the BLI configuration over the baseline geometry. Minor shaping of the aft portion of the fuselage using CDISC has been shown to increase the benefit from boundary-layer ingestion further, resulting in a 15.6% reduction in power requirements for cruise as well as a drag reduction of eighteen counts over the baseline geometry.

  8. Computational Investigation of a Boundary-Layer Ingesting Propulsion System for the Common Research Model

    Science.gov (United States)

    Blumenthal, Brennan T.; Elmiligui, Alaa; Geiselhart, Karl A.; Campbell, Richard L.; Maughmer, Mark D.; Schmitz, Sven

    2016-01-01

    The present paper examines potential propulsive and aerodynamic benefits of integrating a Boundary-Layer Ingestion (BLI) propulsion system into a typical commercial aircraft using the Common Research Model (CRM) geometry and the NASA Tetrahedral Unstructured Software System (TetrUSS). The Numerical Propulsion System Simulation (NPSS) environment is used to generate engine conditions for CFD analysis. Improvements to the BLI geometry are made using the Constrained Direct Iterative Surface Curvature (CDISC) design method. Previous studies have shown reductions of up to 25% in terms of propulsive power required for cruise for other axisymmetric geometries using the BLI concept. An analysis of engine power requirements, drag, and lift coefficients using the baseline and BLI geometries coupled with the NPSS model are shown. Potential benefits of the BLI system relating to cruise propulsive power are quantified using a power balance method, and a comparison to the baseline case is made. Iterations of the BLI geometric design are shown and any improvements between subsequent BLI designs presented. Simulations are conducted for a cruise flight condition of Mach 0.85 at an altitude of 38,500 feet and an angle of attack of 2 deg for all geometries. A comparison between available wind tunnel data, previous computational results, and the original CRM model is presented for model verification purposes along with full results for BLI power savings. Results indicate a 14.4% reduction in engine power requirements at cruise for the BLI configuration over the baseline geometry. Minor shaping of the aft portion of the fuselage using CDISC has been shown to increase the benefit from Boundary-Layer Ingestion further, resulting in a 15.6% reduction in power requirements for cruise as well as a drag reduction of eighteen counts over the baseline geometry.

  9. Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

    Science.gov (United States)

    Huang, Yiteng; Chen, Jingdong; Chen, Shaoyan

    2010-01-01

    A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

  10. GAUSSIAN MIXTURE MODELS FOR ADAPTATION OF DEEP NEURAL NETWORK ACOUSTIC MODELS IN AUTOMATIC SPEECH RECOGNITION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Natalia A. Tomashenko

    2016-11-01

    Full Text Available Subject of Research. We study speaker adaptation of deep neural network (DNN acoustic models in automatic speech recognition systems. The aim of speaker adaptation techniques is to improve the accuracy of the speech recognition system for a particular speaker. Method. A novel method for training and adaptation of deep neural network acoustic models has been developed. It is based on using an auxiliary GMM (Gaussian Mixture Models model and GMMD (GMM-derived features. The principle advantage of the proposed GMMD features is the possibility of performing the adaptation of a DNN through the adaptation of the auxiliary GMM. In the proposed approach any methods for the adaptation of the auxiliary GMM can be used, hence, it provides a universal method for transferring adaptation algorithms developed for GMMs to DNN adaptation.Main Results. The effectiveness of the proposed approach was shown by means of one of the most common adaptation algorithms for GMM models – MAP (Maximum A Posteriori adaptation. Different ways of integration of the proposed approach into state-of-the-art DNN architecture have been proposed and explored. Analysis of choosing the type of the auxiliary GMM model is given. Experimental results on the TED-LIUM corpus demonstrate that, in an unsupervised adaptation mode, the proposed adaptation technique can provide, approximately, a 11–18% relative word error reduction (WER on different adaptation sets, compared to the speaker-independent DNN system built on conventional features, and a 3–6% relative WER reduction compared to the SAT-DNN trained on fMLLR adapted features.

  11. Perceived Task-Difficulty Recognition from Log-File Information for the Use in Adaptive Intelligent Tutoring Systems

    Science.gov (United States)

    Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars

    2016-01-01

    Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

  12. Implementation of a Tour Guide Robot System Using RFID Technology and Viterbi Algorithm-Based HMM for Speech Recognition

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2014-01-01

    Full Text Available This paper applied speech recognition and RFID technologies to develop an omni-directional mobile robot into a robot with voice control and guide introduction functions. For speech recognition, the speech signals were captured by short-time processing. The speaker first recorded the isolated words for the robot to create speech database of specific speakers. After the speech pre-processing of this speech database, the feature parameters of cepstrum and delta-cepstrum were obtained using linear predictive coefficient (LPC. Then, the Hidden Markov Model (HMM was used for model training of the speech database, and the Viterbi algorithm was used to find an optimal state sequence as the reference sample for speech recognition. The trained reference model was put into the industrial computer on the robot platform, and the user entered the isolated words to be tested. After processing by the same reference model and comparing with previous reference model, the path of the maximum total probability in various models found using the Viterbi algorithm in the recognition was the recognition result. Finally, the speech recognition and RFID systems were achieved in an actual environment to prove its feasibility and stability, and implemented into the omni-directional mobile robot.

  13. High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

    Science.gov (United States)

    Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

    2005-09-01

    Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

  14. A study of fuzzy logic ensemble system performance on face recognition problem

    Science.gov (United States)

    Polyakova, A.; Lipinskiy, L.

    2017-02-01

    Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

  15. Stereovision-based 3D field recognition for automatic guidance system of off-road vehicle

    Science.gov (United States)

    Zhang, Fangming; Ying, Yibin; Shen, Chuan; Jiang, Huanyu; Zhang, Qin

    2005-11-01

    A stereovision-based disparity evaluation algorithm was developed for rice crop field recognition. The gray level intensities and the correlation relation were integrated to produce the disparities of stereo-images. The surface of ground and rice were though as two rough planes, but their disparities waved in a narrow range. The cut/uncut edges of rice crops were first detected and track through the images. We used a step model to locate those edge positions. The points besides the edges were matched respectively to get disparity values using area correlation method. The 3D camera coordinates were computed based on those disparities. The vehicle coordinates were obtained by multiplying the 3D camera coordinates with a transform formula. It has been implemented on an agricultural robot and evaluated in rice crop field with straight rows. The results indicated that the developed stereovision navigation system is capable of reconstructing the field image.

  16. Semi-automatic parking slot marking recognition for intelligent parking assist systems

    Directory of Open Access Journals (Sweden)

    Ho Gi Jung

    2014-01-01

    Full Text Available This paper proposes a semi-automatic parking slot marking-based target position designation method for parking assist systems in cases where the parking slot markings are of a rectangular type, and its efficient implementation for real-time operation. After the driver observes a rearview image captured by a rearward camera installed at the rear of the vehicle through a touchscreen-based human machine interface, a target parking position is designated by touching the inside of a parking slot. To ensure the proposed method operates in real-time in an embedded environment, access of the bird's-eye view image is made efficient: image-wise batch transformation is replaced with pixel-wise instantaneous transformation. The proposed method showed a 95.5% recognition rate in 378 test cases with 63 test images. Additionally, experiments confirmed that the pixel-wise instantaneous transformation reduced execution time by 92%.

  17. Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

    Science.gov (United States)

    Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

    2015-01-01

    Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant. PMID:25856329

  18. Resolving Phytoplankton Diversity, Growth and Mortality in an Eastern Boundary Upwelling System

    Science.gov (United States)

    Worden, A. Z.; Jimenez, V.

    2015-12-01

    Eastern Boundary Upwelling Systems are highly productive marine regions. Primary production in these systems is performed by a complex array of phytoplankton, many of which are in the picophytoplankton size class (≤2 µM diameter). Because morphological features in these small cells are limited and difficult to visualize, our understanding of their distributions and activities is poor. Even at broad levels, such as cyanobacteria versus picoeukaryotes, contributions to primary production are not well resolved. However, laboratory experiments show that the biology of species within each of these groups is highly differentiated. Hence, to develop predictive understanding of primary production in these regions, its transfer to higher trophic levels and key export terms, it is necessary to understand which taxa are present and their in situ activities. Here, we report results from multi-year expeditions along a transect (Line 67) that extends from Monterey Bay, California (USA) to the North Pacific Gyre and is also part of the California Cooperative Oceanic Fisheries Investigations (CalCOFI). We explore the diversity of phytoplankton in the coastal zone, the upwelling-transition zone and subtropical gyre-like waters to gain insights into controls acting on primary producers in each. Our Line 67 results on primary producer dynamics are underlain by a comprehensive suite of genomic, metagenomic, metatranscriptomic and molecular analyses. Statistical approaches have helped us to define temperature maxima, nutrient thresholds and important remineralization processes that influence dominance by specific eukaryotic algae. First-ever species-specific growth and grazing mortality rates provide an unprecedented view of contributions to biomass production and its consumption by higher trophic levels. Finally, by investigating the entire microbial community including heterotrophic taxa, we are able to establish baselines for community interactions that are affiliated with

  19. IMPROVEMENTS IN WATER SUPPLY SYSTEMS BASED ON OPTIMIZATION AND RECOGNITION OF CONSUMPTION PATTERNS

    Directory of Open Access Journals (Sweden)

    A. M. F. DINIZ

    2015-05-01

    Full Text Available Water supply systems consume large amounts of energy because of the pumping processes involved. The operational strategy of using frequency converters enables the system to work with better adjusted discharge rate to meet demand. In this case, an optimization strategy can establish an optimal procedure in order to schedule the rotational speed of pumps over a period and guarantee a volume of water in the supply tank. This work presents and solves an optimization problem that provides the optimal schedule for the rotational speed of pumps in a real water supply system considering minimizing the use of electricity and the cost thereof and maintenance. The optimization problem is based on two Artificial Neural Networks (ANN models that provide the total power consumption in the pumping system and level of water in the tank. Pattern recognition techniques in univariate time series based on the real data are used to forecast the demand curve according to the season ofthe year. The results show the potential savings generated by the proposed method and show the feasibility of scheduling the rotational speed of the pumps to ensure the minimum energy cost without affecting hourly demand and the security of the supply system.

  20. A distributed automatic target recognition system using multiple low resolution sensors

    Science.gov (United States)

    Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

    2008-04-01

    In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

  1. An Earth system view on boundaries for human perturbation of the N and P cycles

    Science.gov (United States)

    Cornell, Sarah; de Vries, Wim

    2015-04-01

    The appropriation and transformation of land, water, and living resources can alter Earth system functioning, and potentially undermine the basis for the sustainability of our societies. Human activities have greatly increased the flows of reactive forms of nitrogen (N) and phosphorus (P) in the Earth system. These non-substitutable nutrient elements play a fundamental role in the human food system. Furthermore, the current mode of social and economic globalization, and its effect on the present-day energy system, also has large effects including large NOx-N emissions through combustion. Until now, this perturbation of N and P cycles has been treated largely as a local/regional issue, and managed in terms of direct impacts (water, land or air pollution). However, anthropogenic N and P cycle changes affect physical Earth system feedbacks (through greenhouse gas and aerosol changes) and biogeochemical feedbacks (via ecosystem changes, links to the carbon cycle, and altered nutrient limitation) with impacts that can be far removed from the direct sources. While some form of N and P management at the global level seems likely to be needed for continued societal development, the current local-level and sectorial management is often problematically simplistic, as seen in the tensions between divergent N management needs for climate change mitigation, air pollution control, food production, and ecosystem conservation. We require a step change in understanding complex biogeochemical, physical and socio-economic interactions in order to analyse these effects together, and inform policy trade-offs to minimize emergent systemic risks. Planetary boundaries for N and P cycle perturbation have recently been proposed. We discuss the current status of these precautionary boundaries and how we may improve on these preliminary assessments. We present an overview of the human perturbation of the global biogeochemical cycles of N and P and its interaction with the functioning of the

  2. Towards PLDA-RBM based speaker recognition in mobile environment: Designing stacked/deep PLDA-RBM systems

    DEFF Research Database (Denmark)

    Nautsch, Andreas; Hao, Hong; Stafylakis, Themos

    2016-01-01

    The vast majority of text-independent speaker recognition systems rely on intermediate-sized vectors (i-vectors), which are compared by probabilistic linear discriminant analysis (PLDA). This paper proposes a PLDA-alike approach with restricted Boltzmann machines for i-vector based speaker...... for mobile speaker recognition with limited amounts of training data. The experiments show that the proposed system outperforms the baseline i-vector/PLDA approach by relative gains of 31% on female and 9% on male speakers in terms of half total error rate....

  3. The Cottage Grove fault system (Illinois Basin): Late Paleozoic transpression along a Precambrian crustal boundary

    Science.gov (United States)

    Duchek, A.B.; McBride, J.H.; Nelson, W.J.; Leetaru, H.E.

    2004-01-01

    The Cottage Grove fault system in southern Illinois has long been interpreted as an intracratonic dextral strike-slip fault system. We investigated its structural geometry and kinematics in detail using (1) outcrop data, (2) extensive exposures in underground coal mines, (3) abundant borehole data, and (4) a network of industry seismic reflection profiles, including data reprocessed by us. Structural contour mapping delineates distinct monoclines, broad anticlines, and synclines that express Paleozoic-age deformation associated with strike slip along the fault system. As shown on seismic reflection profiles, prominent near-vertical faults that cut the entire Paleozoic section and basement-cover contact branch upward into outward-splaying, high-angle reverse faults. The master fault, sinuous along strike, is characterized along its length by an elongate anticline, ???3 km wide, that parallels the southern side of the master fault. These features signify that the overall kinematic regime was transpressional. Due to the absence of suitable piercing points, the amount of slip cannot be measured, but is constrained at less than 300 m near the ground surface. The Cottage Grove fault system apparently follows a Precambrian terrane boundary, as suggested by magnetic intensity data, the distribution of ultramafic igneous intrusions, and patterns of earthquake activity. The fault system was primarily active during the Alleghanian orogeny of Late Pennsylvanian and Early Permian time, when ultramatic igneous magma intruded along en echelon tensional fractures. ?? 2004 Geological Society of America.

  4. Existence Results for a Coupled System of Nonlinear Fractional Hybrid Differential Equations with Homogeneous Boundary Conditions

    Directory of Open Access Journals (Sweden)

    Josefa Caballero

    2014-01-01

    Full Text Available We study an existence result for the following coupled system of nonlinear fractional hybrid differential equations with homogeneous boundary conditions D0+α[x(t/f(t,x(t,y(t]=g(t,x(t,y(t,D0+αy(t/f(t,y(t,x(t=g(t,y(t,x(t,  0

  5. Eigenvalue Problems for Systems of Nonlinear Boundary Value Problems on Time Scales

    Directory of Open Access Journals (Sweden)

    S. K. Ntouyas

    2008-01-01

    Full Text Available Values of λ are determined for which there exist positive solutions of the system of dynamic equations, uΔΔ(t+λa(tf(v(σ(t=0, vΔΔ(t+λb(tg(u(σ(t=0, for t∈[0,1]T, satisfying the boundary conditions, u(0=0=u(σ2(1, v(0=0=v(σ2(1, where T is a time scale. A Guo-Krasnosel'skii fixed point-theorem is applied.

  6. Modeling quorum sensing trade-offs between bacterial cell density and system extension from open boundaries

    Science.gov (United States)

    Marenda, Mattia; Zanardo, Marina; Trovato, Antonio; Seno, Flavio; Squartini, Andrea

    2016-12-01

    Bacterial communities undergo collective behavioural switches upon producing and sensing diffusible signal molecules; a mechanism referred to as Quorum Sensing (QS). Exemplarily, biofilm organic matrices are built concertedly by bacteria in several environments. QS scope in bacterial ecology has been debated for over 20 years. Different perspectives counterpose the role of density reporter for populations to that of local environment diffusivity probe for individual cells. Here we devise a model system where tubes of different heights contain matrix-embedded producers and sensors. These tubes allow non-limiting signal diffusion from one open end, thereby showing that population spatial extension away from an open boundary can be a main critical factor in QS. Experimental data, successfully recapitulated by a comprehensive mathematical model, demonstrate how tube height can overtake the role of producer density in triggering sensor activation. The biotic degradation of the signal is found to play a major role and to be species-specific and entirely feedback-independent.

  7. Numerical generation of boundary-fitted curvilinear coordinate systems for arbitrarily curved surfaces

    International Nuclear Information System (INIS)

    Takagi, T.; Miki, K.; Chen, B.C.J.; Sha, W.T.

    1985-01-01

    A new method is presented for numerically generating boundary-fitted coordinate systems for arbitrarily curved surfaces. The three-dimensional surface has been expressed by functions of two parameters using the geometrical modeling techniques in computer graphics. This leads to new quasi-one- and two-dimensional elliptic partial differential equations for coordinate transformation. Since the equations involve the derivatives of the surface expressions, the grids geneated by the equations distribute on the surface depending on its slope and curvature. A computer program GRID-CS based on the method was developed and applied to a surface of the second order, a torus and a surface of a primary containment vessel for a nuclear reactor. These applications confirm that GRID-CS is a convenient and efficient tool for grid generation on arbitrarily curved surfaces

  8. Improving bottom-boundary conditions for SVAT simulations in shallow-groundwater systems

    Science.gov (United States)

    Morris, Paul J.; Verhoef, Anne; Macdonald, David M. J.; Gardner, Cate M.; Punalekar, Suvarna M.; Tatarenko, Irina; Gowing, David

    2013-04-01

    A well documented disparity exists between models that simulate: i) groundwater hydrological processes; and ii) soil-vegetation-atmosphere transfers (SVAT) of water and energy. This is particularly pertinent in shallow groundwater systems, such as lowland floodplains, where the domains of surface water and groundwater necessarily overlap. Consideration of either SVAT or groundwater processes in shallow groundwater systems necessitates a robust understanding of their bi-directional interactions. The hydrological bottom-boundary conditions of SVAT models can be driven using continuous groundwater data from dipwells. However, where such data are not available the bottom boundary must be simulated. We sought to develop a simple empirical model of subsurface fluxes of water between a floodplain soil column and its adjoining river, without the additional cost and complication of a fully linked surface water-groundwater model. We conducted our research at Yarnton Mead, a floodplain meadow on the River Thames in Oxfordshire, UK. We used in-situ soil-physical, hydrological and meteorological data to generate an empirical relationship between floodplain water-table position, and rate and direction of subsurface water fluxes between the floodplain soil and the river. We estimated rates of subsurface water flux into and out of our instrumented soil column as the residual term of a water balance equation. We then fitted a linear model to describe the rate and direction of subsurface flux as a function of water-table position. Although the level of explanation of the linear model is not high (r-squared = 0.39), the relationship is highly significant (p validated the model's simulated water tables against dipwell measurements. The simulated water tables fitted well to observed data with root mean square error of 0.13 m and r-squared = 0.71. The fit could be improved further by optimising the slope and intercept of the linear model. Our results are highly promising and suggest

  9. Research on installation quality inspection system of high voltage customer metering device based on image recognition

    Science.gov (United States)

    He, Bei; Yang, Fu-li; Tao, Xue-dan; Chang, Shi-liang; Wu, Kang

    2017-11-01

    With the rapid development of the scale of the power grid, the site construction and the operations environment is more widespread and more complex. The installation work of the high-voltage customer metering device is heavy, which is not standardized. In addition, managers supervise the site construction progress only through the person in charge of each work phrase. It is inefficient and difficult to control the multi-team and multi-unit cross work. Therefore, it is necessary to establish a scientific system to detect the quality of installation and management practices to standardize installation work of the metering device. Based on the research of image recognition and target detection system, this paper presents a high-voltage customer metering device installation quality inspection system based on digital image processing, image feature extraction and SVM classification decision. The experimental results show that the proposed scheme is feasible. And it can be used to accurately extract the metering components in the image, which can be also accurately and quickly classified. Our method is of great significance for the implementation and monitoring of the power system in installation and specification

  10. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition

    Directory of Open Access Journals (Sweden)

    Mohammad Subhi Al-batah

    2014-01-01

    Full Text Available To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL and high-grade squamous intraepithelial lesion (HSIL. The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy.

  11. Human abdomen recognition using camera and force sensor in medical robot system for automatic ultrasound scan.

    Science.gov (United States)

    Bin Mustafa, Ammar Safwan; Ishii, Takashi; Matsunaga, Yoshiki; Nakadate, Ryu; Ishii, Hiroyuki; Ogawa, Kouji; Saito, Akiko; Sugawara, Motoaki; Niki, Kiyomi; Takanishi, Atsuo

    2013-01-01

    Physicians use ultrasound scans to obtain real-time images of internal organs, because such scans are safe and inexpensive. However, people in remote areas face difficulties to be scanned due to aging society and physician's shortage. Hence, it is important to develop an autonomous robotic system to perform remote ultrasound scans. Previously, we developed a robotic system for automatic ultrasound scan focusing on human's liver. In order to make it a completely autonomous system, we present in this paper a way to autonomously localize the epigastric region as the starting position for the automatic ultrasound scan. An image processing algorithm marks the umbilicus and mammary papillae on a digital photograph of the patient's abdomen. Then, we made estimation for the location of the epigastric region using the distances between these landmarks. A supporting algorithm distinguishes rib position from epigastrium using the relationship between force and displacement. We implemented these algorithms with the automatic scanning system into an apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator. Tests on 14 healthy male subjects showed the apparatus located the epigastric region with a success rate of 94%. The results suggest that image recognition was effective in localizing a human body part.

  12. Multiple adaptive neuro-fuzzy inference system with automatic features extraction algorithm for cervical cancer recognition.

    Science.gov (United States)

    Al-batah, Mohammad Subhi; Isa, Nor Ashidi Mat; Klaib, Mohammad Fadel; Al-Betar, Mohammed Azmi

    2014-01-01

    To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy.

  13. An interactive VR system based on full-body tracking and gesture recognition

    Science.gov (United States)

    Zeng, Xia; Sang, Xinzhu; Chen, Duo; Wang, Peng; Guo, Nan; Yan, Binbin; Wang, Kuiru

    2016-10-01

    Most current virtual reality (VR) interactions are realized with the hand-held input device which leads to a low degree of presence. There is other solutions using sensors like Leap Motion to recognize the gestures of users in order to interact in a more natural way, but the navigation in these systems is still a problem, because they fail to map the actual walking to virtual walking only with a partial body of the user represented in the synthetic environment. Therefore, we propose a system in which users can walk around in the virtual environment as a humanoid model, selecting menu items and manipulating with the virtual objects using natural hand gestures. With a Kinect depth camera, the system tracks the joints of the user, mapping them to a full virtual body which follows the move of the tracked user. The movements of the feet can be detected to determine whether the user is in walking state, so that the walking of model in the virtual world can be activated and stopped by means of animation control in Unity engine. This method frees the hands of users comparing to traditional navigation way using hand-held device. We use the point cloud data getting from Kinect depth camera to recognize the gestures of users, such as swiping, pressing and manipulating virtual objects. Combining the full body tracking and gestures recognition using Kinect, we achieve our interactive VR system in Unity engine with a high degree of presence.

  14. Phonological feature-based speech recognition system for pronunciation training in non-native language learning.

    Science.gov (United States)

    Arora, Vipul; Lahiri, Aditi; Reetz, Henning

    2018-01-01

    The authors address the question whether phonological features can be used effectively in an automatic speech recognition (ASR) system for pronunciation training in non-native language (L2) learning. Computer-aided pronunciation training consists of two essential tasks-detecting mispronunciations and providing corrective feedback, usually either on the basis of full words or phonemes. Phonemes, however, can be further disassembled into phonological features, which in turn define groups of phonemes. A phonological feature-based ASR system allows the authors to perform a sub-phonemic analysis at feature level, providing a more effective feedback to reach the acoustic goal and perceptual constancy. Furthermore, phonological features provide a structured way for analysing the types of errors a learner makes, and can readily convey which pronunciations need improvement. This paper presents the authors implementation of such an ASR system using deep neural networks as an acoustic model, and its use for detecting mispronunciations, analysing errors, and rendering corrective feedback. Quantitative as well as qualitative evaluations are carried out for German and Italian learners of English. In addition to achieving high accuracy of mispronunciation detection, the system also provides accurate diagnosis of errors.

  15. Geochemistry and magnetic sediment distribution at the western boundary upwelling system of southwest Atlantic

    Science.gov (United States)

    Cruz, Anna P. S.; Barbosa, Catia F.; Ayres-Neto, Arthur; Munayco, Pablo; Scorzelli, Rosa B.; Amorim, Nívea Santos; Albuquerque, Ana L. S.; Seoane, José C. S.

    2018-02-01

    In order to investigate the chemical and magnetic characteristics of sediments of the western boundary upwelling system of Southwest Atlantic we analyzed magnetic susceptibility, grain size distribution, total organic carbon, heavy mineral abundance, Fe associated with Mössbauer spectra, and Fe and Mn of pore water to evaluate the deposition patterns of sediments. Four box-cores were collected along a cross-shelf transect. Brazil Current and coastal plume exert a primary control at the inner and outer shelf cores, which exhibited similar depositional patterns characterized by a high abundance of heavy minerals (mean 0.21% and 0.08%, respectively) and very fine sand, whereas middle shelf cores presented low abundances of heavy minerals (mean 0.03%) and medium silt. The inner shelf was dominated by sub-angular grains, while in middle and outer shelf cores well-rounded grains were found. The increasing Fe3+:Fe2+ ratio from the inner to the outer shelf reflects farther distance to the sediment source. The outer shelf presented well-rounded minerals, indicating abrasive processes as a result of transport by the Brazil Current from the source areas. In the middle shelf, cold-water intrusion of the South Atlantic Central Water contributes to the primary productivity, resulting in higher deposition of fine sediment and organic carbon accumulation. The high input of organic carbon and the decreased grain size are indicative of changes in the hydrodynamics and primary productivity fueled by the western boundary upwelling system, which promotes loss of magnetization due to the induction of diagenesis of iron oxide minerals.

  16. Structural Basis of Chaperone Recognition of Type III Secretion System Minor Translocator Proteins*

    Science.gov (United States)

    Job, Viviana; Matteï, Pierre-Jean; Lemaire, David; Attree, Ina; Dessen, Andréa

    2010-01-01

    The type III secretion system (T3SS) is a complex nanomachine employed by many Gram-negative pathogens, including the nosocomial agent Pseudomonas aeruginosa, to inject toxins directly into the cytoplasm of eukaryotic cells. A key component of all T3SS is the translocon, a proteinaceous channel that is inserted into the target membrane, which allows passage of toxins into target cells. In most bacterial species, two distinct membrane proteins (the “translocators”) are involved in translocon formation, whereas in the bacterial cytoplasm, however, they remain associated to a common chaperone. To date, the strategy employed by a single chaperone to recognize two distinct translocators is unknown. Here, we report the crystal structure of a complex between the Pseudomonas translocator chaperone PcrH and a short region from the minor translocator PopD. PcrH displays a 7-helical tetratricopeptide repeat fold that harbors the PopD peptide within its concave region, originally believed to be involved in recognition of the major translocator, PopB. Point mutations introduced into the PcrH-interacting region of PopD impede translocator-chaperone recognition in vitro and lead to impairment of bacterial cytotoxicity toward macrophages in vivo. These results indicate that T3SS translocator chaperones form binary complexes with their partner molecules, and the stability of their interaction regions must be strictly maintained to guarantee bacterial infectivity. The PcrH-PopD complex displays homologs among a number of pathogenic strains and could represent a novel, potential target for antibiotic development. PMID:20385547

  17. A high-order doubly asymptotic open boundary for scalar waves in semi-infinite layered systems

    International Nuclear Information System (INIS)

    Prempramote, S; Song, Ch; Birk, C

    2010-01-01

    Wave propagation in semi-infinite layered systems is of interest in earthquake engineering, acoustics, electromagnetism, etc. The numerical modelling of this problem is particularly challenging as evanescent waves exist below the cut-off frequency. Most of the high-order transmitting boundaries are unable to model the evanescent waves. As a result, spurious reflection occurs at late time. In this paper, a high-order doubly asymptotic open boundary is developed for scalar waves propagating in semi-infinite layered systems. It is derived from the equation of dynamic stiffness matrix obtained in the scaled boundary finite-element method in the frequency domain. A continued-fraction solution of the dynamic stiffness matrix is determined recursively by satisfying the scaled boundary finite-element equation at both high- and low-frequency limits. In the time domain, the continued-fraction solution permits the force-displacement relationship to be formulated as a system of first-order ordinary differential equations. Standard time-step schemes in structural dynamics can be directly applied to evaluate the response history. Examples of a semi-infinite homogeneous layer and a semi-infinite two-layered system are investigated herein. The displacement results obtained from the open boundary converge rapidly as the order of continued fractions increases. Accurate results are obtained at early time and late time.

  18. Performance improvement of 64-QAM coherent optical communication system by optimizing symbol decision boundary based on support vector machine

    Science.gov (United States)

    Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang

    2018-03-01

    High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.

  19. A Smart Capsule System for Automated Detection of Intestinal Bleeding Using HSL Color Recognition.

    Directory of Open Access Journals (Sweden)

    Panpan Qiao

    Full Text Available There are no ideal means for the diagnosis of intestinal bleeding diseases as of now, particularly in the small intestine. This study investigated an intelligent intestinal bleeding detection capsule system based on color recognition. After the capsule is swallowed, the bleeding detection module (containing a color-sensitive adsorptive film that changes color when absorbing intestinal juice, is used to identify intestinal bleeding features. A hue-saturation-light color space method can be applied to detect bleeding according to the range of H and S values of the film color. Once bleeding features are recognized, a wireless transmission module is activated immediately to send an alarm signal to the outside; an in vitro module receives the signal and sends an alarm. The average power consumption of the entire capsule system is estimated to be about 2.1mW. Owing to its simplicity, reliability, and effectiveness, this system represents a new approach to the clinical diagnosis of intestinal bleeding diseases.

  20. A Vision-Based Automated Guided Vehicle System with Marker Recognition for Indoor Use

    Science.gov (United States)

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-01-01

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system. PMID:23966180

  1. Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

    Science.gov (United States)

    Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

    1998-02-01

    We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

  2. Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System

    Directory of Open Access Journals (Sweden)

    Jun-Ming Lu

    2011-07-01

    Full Text Available This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.

  3. A vision-based automated guided vehicle system with marker recognition for indoor use.

    Science.gov (United States)

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-08-07

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

  4. Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

    Directory of Open Access Journals (Sweden)

    O'Sullivan Maire

    2010-05-01

    Full Text Available Abstract Background In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN scheme. Results The diagram includes detailed views of the toll-like receptor (TLR pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges. Conclusions The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.

  5. Modeling of drug release from matrix systems involving moving boundaries: approximate analytical solutions.

    Science.gov (United States)

    Lee, Ping I

    2011-10-10

    The purpose of this review is to provide an overview of approximate analytical solutions to the general moving boundary diffusion problems encountered during the release of a dispersed drug from matrix systems. Starting from the theoretical basis of the Higuchi equation and its subsequent improvement and refinement, available approximate analytical solutions for the more complicated cases involving heterogeneous matrix, boundary layer effect, finite release medium, surface erosion, and finite dissolution rate are also discussed. Among various modeling approaches, the pseudo-steady state assumption employed in deriving the Higuchi equation and related approximate analytical solutions appears to yield reasonably accurate results in describing the early stage release of a dispersed drug from matrices of different geometries whenever the initial drug loading (A) is much larger than the drug solubility (C(s)) in the matrix (or A≫C(s)). However, when the drug loading is not in great excess of the drug solubility (i.e. low A/C(s) values) or when the drug loading approaches the drug solubility (A→C(s)) which occurs often with drugs of high aqueous solubility, approximate analytical solutions based on the pseudo-steady state assumption tend to fail, with the Higuchi equation for planar geometry exhibiting a 11.38% error as compared with the exact solution. In contrast, approximate analytical solutions to this problem without making the pseudo-steady state assumption, based on either the double-integration refinement of the heat balance integral method or the direct simplification of available exact analytical solutions, show close agreement with the exact solutions in different geometries, particularly in the case of low A/C(s) values or drug loading approaching the drug solubility (A→C(s)). However, the double-integration heat balance integral approach is generally more useful in obtaining approximate analytical solutions especially when exact solutions are not

  6. The influence of a scaled boundary response on integral system transient behavior

    International Nuclear Information System (INIS)

    Dimenna, R.A.; Kullberg, C.M.

    1989-01-01

    Scaling relationships associated with the thermal-hydraulic response of a closed-loop system are applied to a calculational assessment of a feed-and-bleed recovery in a nuclear reactor integral effects test. The analysis demonstrates both the influence of scale on the system response and the ability of the thermal-hydraulics code to represent those effects. The qualitative response of the fluid is shown to be coupled to the behavior of the bounding walls through the energy equation. The results of the analysis described in this paper influence the determination of computer code applicability. The sensitivity of the code response to scaling variations introduced in the analysis is found to be appropriate with respect to scaling criteria determined from the scaling literature. Differences in the system response associated with different scaling criteria are found to be plausible and easily explained using well-known principles of heat transfer. Therefore, it is concluded that RELAP5/MOD2 can adequately represent the scaled effects of heat transfer boundary conditions of the thermal-hydraulic calculations through the mechanism of communicating walls. The results of the analysis also serve to clarify certain aspects of experiment and facility design

  7. Multi-domain boundary element method for axi-symmetric layered linear acoustic systems

    Science.gov (United States)

    Reiter, Paul; Ziegelwanger, Harald

    2017-12-01

    Homogeneous porous materials like rock wool or synthetic foam are the main tool for acoustic absorption. The conventional absorbing structure for sound-proofing consists of one or multiple absorbers placed in front of a rigid wall, with or without air-gaps in between. Various models exist to describe these so called multi-layered acoustic systems mathematically for incoming plane waves. However, there is no efficient method to calculate the sound field in a half space above a multi layered acoustic system for an incoming spherical wave. In this work, an axi-symmetric multi-domain boundary element method (BEM) for absorbing multi layered acoustic systems and incoming spherical waves is introduced. In the proposed BEM formulation, a complex wave number is used to model absorbing materials as a fluid and a coordinate transformation is introduced which simplifies singular integrals of the conventional BEM to non-singular radial and angular integrals. The radial and angular part are integrated analytically and numerically, respectively. The output of the method can be interpreted as a numerical half space Green's function for grounds consisting of layered materials.

  8. The Ndynamics package—Numerical analysis of dynamical systems and the fractal dimension of boundaries

    Science.gov (United States)

    Avellar, J.; Duarte, L. G. S.; da Mota, L. A. C. P.; de Melo, N.; Skea, J. E. F.

    2012-09-01

    A set of Maple routines is presented, fully compatible with the new releases of Maple (14 and higher). The package deals with the numerical evolution of dynamical systems and provide flexible plotting of the results. The package also brings an initial conditions generator, a numerical solver manager, and a focusing set of routines that allow for better analysis of the graphical display of the results. The novelty that the package presents an optional C interface is maintained. This allows for fast numerical integration, even for the totally inexperienced Maple user, without any C expertise being required. Finally, the package provides the routines to calculate the fractal dimension of boundaries (via box counting). New version program summary Program Title: Ndynamics Catalogue identifier: %Leave blank, supplied by Elsevier. Licensing provisions: no. Programming language: Maple, C. Computer: Intel(R) Core(TM) i3 CPU M330 @ 2.13 GHz. Operating system: Windows 7. RAM: 3.0 GB Keywords: Dynamical systems, Box counting, Fractal dimension, Symbolic computation, Differential equations, Maple. Classification: 4.3. Catalogue identifier of previous version: ADKH_v1_0. Journal reference of previous version: Comput. Phys. Commun. 119 (1999) 256. Does the new version supersede the previous version?: Yes. Nature of problem Computation and plotting of numerical solutions of dynamical systems and the determination of the fractal dimension of the boundaries. Solution method The default method of integration is a fifth-order Runge-Kutta scheme, but any method of integration present on the Maple system is available via an argument when calling the routine. A box counting [1] method is used to calculate the fractal dimension [2] of the boundaries. Reasons for the new version The Ndynamics package met a demand of our research community for a flexible and friendly environment for analyzing dynamical systems. All the user has to do is create his/her own Maple session, with the system to

  9. Effects of resolved boundary layer turbulence on near-ground rotation in simulated quasi-linear convective systems (QLCSs)

    Science.gov (United States)

    Nowotarski, C. J.

    2017-12-01

    Though most strong to violent tornadoes are associated with supercell thunderstorms, quasi-linear convective systems (QLCSs) pose a risk of tornadoes, often at times and locations where supercell tornadoes are less common. Because QLCS low-level mesocyclones and tornado signatures tend to be less coherent, forecasting such tornadoes remains particularly difficult. The majority of simulations of such storms rely on horizontally homogeneous base states lacking resolved boundary layer turbulence and surface fluxes. Previous work has suggested that heterogeneities associated with boundary layer turbulence in the form of horizontal convective rolls can influence the evolution and characteristics of low-level mesocyclones in supercell thunderstorms. This study extends methods for generating boundary layer convection to idealized simulations of QLCSs. QLCS simulations with resolved boundary layer turbulence will be compared against a control simulation with a laminar boundary layer. Effects of turbulence, the resultant heterogeneity in the near-storm environment, and surface friction on bulk storm characteristics and the intensity, morphology, and evolution of low-level rotation will be presented. Although maximum surface vertical vorticity values are similar, when boundary layer turbulence is included, a greater number of miso- and meso-scale vortices develop along the QLCS gust front. The source of this vorticity is analyzed using Eulerian decomposition of vorticity tendency terms and trajectory analysis to delineate the relative importance of surface friction and baroclinicity in generating QLCS vortices. The role of anvil shading in suppressing boundary layer turbulence in the near-storm environment and subsequent effects on QLCS vortices will also be presented. Finally, implications of the results regarding inclusion of more realistic boundary layers in future idealized simulations of deep convection will be discussed.

  10. Control Volume Analysis of Boundary Layer Ingesting Propulsion Systems With or Without Shock Wave Ahead of the Inlet

    Science.gov (United States)

    Kim, Hyun Dae; Felder, James L.

    2011-01-01

    The performance benefit of boundary layer or wake ingestion on marine and air vehicles has been well documented and explored. In this article, a quasi-one-dimensional boundary layer ingestion (BLI) benefit analysis for subsonic and transonic propulsion systems is performed using a control volume of a ducted propulsion system that ingests the boundary layer developed by the external airframe surface. To illustrate the BLI benefit, a relationship between the amount of BLI and the net thrust is established and analyzed for two propulsor types. One propulsor is an electric fan, and the other is a pure turbojet. These engines can be modeled as a turbofan with an infinite bypass ratio for the electric fan, and with a zero bypass ratio for the pure turbojet. The analysis considers two flow processes: a boundary layer being ingested by an aircraft inlet and a shock wave sitting in front of the inlet. Though the two processes are completely unrelated, both represent a loss of total pressure and velocity. In real applications, it is possible to have both processes occurring in front of the inlet of a transonic vehicle. Preliminary analysis indicates that the electrically driven propulsion system benefits most from the boundary layer ingestion and the presence of transonic shock waves, whereas the benefit for the turbojet engine is near zero or negative depending on the amount of total temperature rise across the engine.

  11. A compensation method to improve the performance of IPI-based entity recognition system in body sensor networks.

    Science.gov (United States)

    Bao, Shu-Di; He, Zhong-Kun; Jin, Rong; An, Peng

    2013-01-01

    Security of wireless body sensor networks (BSNs) with telemedicine applications remains a crucial issue. A family of novel biometrics schemes has been recently proposed for node recognition and cryptographic key distribution without any pre-deployment in BSNs, where dynamic entity identifiers (EIs) generated from physiological signals captured by individual sensor nodes are used for nodes to recognize each other. As the recognition performance of EIs determines the maximal performance that can be achieved in such biometric systems, several kinds of EI generation schemes have been proposed. The inter-pulse intervals based EI generation scheme is more promising for such applications in actual scenarios because of its acceptable recognition performance. However, it was found that such generated EIs by true pairs of nodes, i.e. two nodes from the same BSN, have some error pattern which could be considered while doing node recognition or key distribution for an improved success rate. To address the problem, this work proposes an error-correcting code based compensation method which can be easily combined together with the key distribution process to achieve an improved recognition performance. Results of statistical analysis with experimental data collected from 14 subjects show that the bit difference between EIs from true pairs of nodes can be effectively reduced with the proposed method.

  12. Loneliness and the social monitoring system: Emotion recognition and eye gaze in a real-life conversation.

    Science.gov (United States)

    Lodder, Gerine M A; Scholte, Ron H J; Goossens, Luc; Engels, Rutger C M E; Verhagen, Maaike

    2016-02-01

    Based on the belongingness regulation theory (Gardner et al., 2005, Pers. Soc. Psychol. Bull., 31, 1549), this study focuses on the relationship between loneliness and social monitoring. Specifically, we examined whether loneliness relates to performance on three emotion recognition tasks and whether lonely individuals show increased gazing towards their conversation partner's faces in a real-life conversation. Study 1 examined 170 college students (Mage = 19.26; SD = 1.21) who completed an emotion recognition task with dynamic stimuli (morph task) and a micro(-emotion) expression recognition task. Study 2 examined 130 college students (Mage = 19.33; SD = 2.00) who completed the Reading the Mind in the Eyes Test and who had a conversation with an unfamiliar peer while their gaze direction was videotaped. In both studies, loneliness was measured using the UCLA Loneliness Scale version 3 (Russell, 1996, J. Pers. Assess., 66, 20). The results showed that loneliness was unrelated to emotion recognition on all emotion recognition tasks, but that it was related to increased gaze towards their conversation partner's faces. Implications for the belongingness regulation system of lonely individuals are discussed. © 2015 The British Psychological Society.

  13. Neuroscience-inspired computational systems for speech recognition under noisy conditions

    Science.gov (United States)

    Schafer, Phillip B.

    Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes

  14. A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

    Directory of Open Access Journals (Sweden)

    Shu Tian

    2015-01-01

    Full Text Available The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a VidEo-Based Intelligent Recognitionand Decision (VEBIRD system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VEBIRD comprises a robust eye (iris detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VEBIRD’s effectiveness.

  15. A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

    Science.gov (United States)

    Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

    2015-01-01

    The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.

  16. High-Speed Video System for Micro-Expression Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Diana Borza

    2017-12-01

    Full Text Available Micro-expressions play an essential part in understanding non-verbal communication and deceit detection. They are involuntary, brief facial movements that are shown when a person is trying to conceal something. Automatic analysis of micro-expression is challenging due to their low amplitude and to their short duration (they occur as fast as 1/15 to 1/25 of a second. We propose a fully micro-expression analysis system consisting of a high-speed image acquisition setup and a software framework which can detect the frames when the micro-expressions occurred as well as determine the type of the emerged expression. The detection and classification methods use fast and simple motion descriptors based on absolute image differences. The recognition module it only involves the computation of several 2D Gaussian probabilities. The software framework was tested on two publicly available high speed micro-expression databases and the whole system was used to acquire new data. The experiments we performed show that our solution outperforms state of the art works which use more complex and computationally intensive descriptors.

  17. A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles

    Directory of Open Access Journals (Sweden)

    Jae Kyu Suhr

    2018-04-01

    Full Text Available An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision.

  18. Development of Vision Based Multiview Gait Recognition System with MMUGait Database

    Directory of Open Access Journals (Sweden)

    Hu Ng

    2014-01-01

    Full Text Available This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases.

  19. Contribution of pheromones processed by the main olfactory system to mate recognition in female mammals

    Directory of Open Access Journals (Sweden)

    Micheal J. Baum

    2012-06-01

    Full Text Available Until recently it was widely believed that the ability of female mammals (with the likely exception of women to identify and seek out a male breeding partner relied on the detection of non-volatile male pheromones by the female’s vomeronasal organ and their subsequent processing by a neural circuit that includes the accessory olfactory bulb, vomeronasal amygdala, and hypothalamus. Emperical data are reviewed in this paper that demonstrate the detection of volatile pheromones by the main olfactory epithelium of female mice which, in turn, leads to the activation of a population of glomeruli and abutting mitral cells in the main olfactory bulb (MOB. Anatomical results along with functional neuroanatomical data demonstrate that some of these MOB mitral cells project to the vomeronasal amygdala. These particular MOB mitral cells were selectively activated (i.e., expressed Fos protein by exposure to male as opposed to female urinary volatiles. A similar selectivity to opposite sex urinary volatiles was also seen in mitral cells of the accessory olfactory bulb of female mice. Behavioral data from female mouse, ferret, and human are reviewed that implicate the main olfactory system, in some cases interacting with the accessory olfactory system, in mate recognition.

  20. Aptamers as promising molecular recognition elements for diagnostics and therapeutics in the central nervous system.

    Science.gov (United States)

    McConnell, Erin M; Holahan, Matthew R; DeRosa, Maria C

    2014-12-01

    Oligonucleotide aptamers are short, synthetic, single-stranded DNA or RNA able to recognize and bind to a multitude of targets ranging from small molecules to cells. Aptamers have emerged as valuable tools for fundamental research, clinical diagnosis, and therapy. Due to their small size, strong target affinity, lack of immunogenicity, and ease of chemical modification, aptamers are an attractive alternative to other molecular recognition elements, such as antibodies. Although it is a challenging environment, the central nervous system and related molecular targets present an exciting potential area for aptamer research. Aptamers hold promise for targeted drug delivery, diagnostics, and therapeutics. Here we review recent advances in aptamer research for neurotransmitter and neurotoxin targets, demyelinating disease and spinal cord injury, cerebrovascular disorders, pathologies related to protein aggregation (Alzheimer's, Parkinson's, and prions), brain cancer (glioblastomas and gliomas), and regulation of receptor function. Challenges and limitations posed by the blood brain barrier are described. Future perspectives for the application of aptamers to the central nervous system are also discussed.

  1. Boundary Detection and Enhancement Strategy for Power System Bus Bar Stabilization—Investigation under Fault Conditions for Islanding Operation

    Directory of Open Access Journals (Sweden)

    Aref Pouryekta

    2018-04-01

    Full Text Available Distribution systems can form islands when faults occur. Each island represents a subsection with variable boundaries subject to the location of fault(s in the system. A subsection with variable boundaries is referred to as an island in this paper. For operation in autonomous mode, it is imperative to detect the island configurations and stabilize these subsections. This paper presents a novel scheme for the detection of island boundaries and stabilizing the system during autonomous operation. In the first stage, a boundary detection method is proposed to detect the configuration of the island. In the second stage, a dynamic voltage sensitivity factor (DVSF is proposed to assess the dynamic performance of the system. In the third stage, a wide area load shedding program is adopted based on DVSF to shed the load in weak bus-bars and stabilize the system. The proposed scheme is validated and tested on a generic 18-bus system using a combination of EMTDC/PSCAD and MATLAB software’s.

  2. Creation of an Upper Stage Trajectory Capability Boundary to Enable Booster System Trade Space Exploration

    Science.gov (United States)

    Walsh, Ptrick; Coulon, Adam; Edwards, Stephen; Mavris, Dimitri N.

    2012-01-01

    The problem of trajectory optimization is important in all space missions. The solution of this problem enables one to specify the optimum thrust steering program which should be followed to achieve a specified mission objective, simultaneously satisfying the constraints.1 It is well known that whether or not the ascent trajectory is optimal can have a significant impact on propellant usage for a given payload, or on payload weight for the same gross vehicle weight.2 Consequently, ascent guidance commands are usually optimized in some fashion. Multi-stage vehicles add complexity to this analysis process as changes in vehicle properties in one stage propagate to the other stages through gear ratios and changes in the optimal trajectory. These effects can cause an increase in analysis time as more variables are added and convergence of the optimizer to system closure requires more analysis iterations. In this paper, an approach to simplifying this multi-stage problem through the creation of an upper stage capability boundary is presented. This work was completed as part of a larger study focused on trade space exploration for the advanced booster system that will eventually form a part of NASA s new Space Launch System.3 The approach developed leverages Design of Experiments and Surrogate Modeling4 techniques to create a predictive model of the SLS upper stage performance. The design of the SLS core stages is considered fixed for the purposes of this study, which results in trajectory parameters such as staging conditions being the only variables relevant to the upper stage. Through the creation of a surrogate model, which takes staging conditions as inputs and predicts the payload mass delivered by the SLS upper stage to a reference orbit as the response, it is possible to identify a "surface" of staging conditions which all satisfy the SLS requirement of placing 130 metric tons into low-Earth orbit (LEO).3 This identified surface represents the 130 metric ton

  3. Understanding the Effects of Lower Boundary Conditions and Eddy Diffusion on the Ionosphere-Thermosphere System

    Science.gov (United States)

    Malhotra, G.; Ridley, A. J.; Marsh, D. R.; Wu, C.; Paxton, L. J.

    2017-12-01

    The exchange of energy between lower atmospheric regions with the ionosphere-thermosphere (IT) system is not well understood. A number of studies have observed day-to-day and seasonal variabilities in the difference between data and model output of various IT parameters. It is widely speculated that the forcing from the lower atmosphere, variability in weather systems and gravity waves that propagate upward from troposphere into the upper mesosphere and lower thermosphere (MLT) may be responsible for these spatial and temporal variations in the IT region, but their exact nature is unknown. These variabilities can be interpreted in two ways: variations in state (density, temperature, wind) of the upper mesosphere or spatial and temporal changes in the small-scale mixing, or Eddy diffusion that is parameterized within the model.In this study, firstly, we analyze the sensitivity of the thermospheric and ionospheric states - neutral densities, O/N2, total electron content (TEC), peak electron density, and peak electron height - to various lower boundary conditions in the Global Ionosphere Thermosphere Model (GITM). We use WACCM-X and GSWM to drive the lower atmospheric boundary in GITM at 100 km, and compare the results with the current MSIS-driven version of GITM, analyzing which of these simulations match the measurements from GOCE, GUVI, CHAMP, and GPS-derived TEC best. Secondly, we analyze the effect of eddy diffusion in the IT system. The turbulence due to eddy mixing cannot be directly measured and it is a challenge to completely characterize its linear and non-linear effects from other influences, since the eddy diffusion both influences the composition through direct mixing and the temperature structure due to turbulent conduction changes. In this study we input latitudinal and seasonal profiles of eddy diffusion into GITM and then analyze the changes in the thermospheric and ionospheric parameters. These profiles will be derived from both WACC-X simulations

  4. Boundary delineation for regional groundwater flow through geographic information system (Contract research)

    International Nuclear Information System (INIS)

    Yamakawa, Tadashi; Munakata, Masahiro; Kimura, Hideo; Hyodo, Hiroshi

    2007-03-01

    Radionuclide migration toward the human environment is to be assessed as the part of long-term safety assessments of geologic disposal of radioactive waste. Geologic processes, which include volcanic activity, hydrothermal activity, seismicity and deformation, bring about hydrogeologic changes in the regional groundwater flow system around a repository site. Groundwater flow systems in Japan have been studied in several sites such as Tono mine, Kamaishi mine and Horonobe area, but methodology of studies in these sites does not have fully developed. This study was conducted to develop methodologies of boundary delineation for regional groundwater flow systems. Geographic Information System, GIS, was applied using available topographic, hydrologic and geologic data for an area of interest. Miyakoji in the Abukuma Mountains was selected as the area, for the reason of its simple geologic setting formed by granitic rocks and topographically gentle hills of drainage basin. Data used in this study cover topographic sheets, digital elevation model, satellite imagery, geologic maps, topographic classification maps, soil distribution maps and landuse maps. Through the GIS techniques using these data, thematic maps on topographic features, surface conditions, land coverage, geology and geologic structure and weathered crust were developed, and these thematic maps were further applied to extract four factors affecting the regional groundwater flows: topographic condition, precipitation recharge, fracture characteristics and potential flows. The present study revealed that, taking the potential groundwater flows and characteristics of fractured zones in the area into consideration, the groundwater flow system in Miyakoji drainage basin should be bounded by the Otakine Mountain and the northern part of Tokoha Drainage Basin. The delineated area is larger than understood before. (author)

  5. A free boundary problem for a reaction-diffusion system with nonlinear memory

    DEFF Research Database (Denmark)

    Lin, Zhigui; Ling, Zhi; Pedersen, Michael

    2013-01-01

    We consider a integro-partial differential equation with a free boundary which appears in the theory of the nuclear dynamics. First, local existence and uniqueness are obtained by using the contraction mapping theorem. Then, the behavior of the free boundary and the blow-up criteria are obtained...

  6. Effects of translational symmetry breaking induced by the boundaries in a driven diffusive system

    DEFF Research Database (Denmark)

    Andersen, Jørgen Vitting; Leung, Kwan-tai

    1991-01-01

    We study the effects of the boundary conditions in a driven diffusive lattice-gas model which is known to display kinetic phase transitions. We find, in the case of attractive interaction, that a boundary-condition-induced symmetry breaking of the translational invariance, along the direction...

  7. Nonlinear Seismic Behavior of Different Boundary Conditions of Transmission Line Systems under Earthquake Loading

    Directory of Open Access Journals (Sweden)

    Li Tian

    2016-01-01

    Full Text Available Nonlinear seismic behaviors of different boundary conditions of transmission line system under earthquake loading are investigated in this paper. The transmission lines are modeled by cable element accounting for the nonlinearity of the cable. For the suspension type, three towers and two span lines with spring model (Model 1 and three towers and four span lines’ model (Model 2 are established, respectively. For the tension type, three towers and two span lines’ model (Model 3 and three towers and four span lines’ model (Model 4 are created, respectively. The frequencies of the transmission towers and transmission lines of the suspension type and tension type are calculated, respectively. The responses of the suspension type and tension type are investigated using nonlinear time history analysis method, respectively. The results show that the responses of the transmission tower and transmission line of the two models of the suspension type are slightly different. However, the responses of transmission tower and transmission line of the two models of the tension type are significantly different. Therefore, in order to obtain accurate results, a reasonable model should be considered. The results could provide a reference for the seismic analysis of the transmission tower-line system.

  8. CoinFLP: a system for efficient mosaic screening and for visualizing clonal boundaries in Drosophila.

    Science.gov (United States)

    Bosch, Justin A; Tran, Ngoc Han; Hariharan, Iswar K

    2015-02-01

    Screens in mosaic Drosophila tissues that use chemical mutagenesis have identified many regulators of growth and patterning. Many of the mutant phenotypes observed were contingent upon the presence of both wild-type and mutant cells in the same tissue. More recently, large collections of RNAi lines or cDNAs expressed under Gal4/UAS control have been used to alter gene expression uniformly in specific tissues. However, these newer approaches are not easily combined with the efficient generation of genetic mosaics. The CoinFLP system described here enables mosaic screens in the context of gene knockdown or overexpression by automatically generating a reliable ratio of mutant to wild-type tissue in a developmentally controlled manner. CoinFLP-Gal4 generates mosaic tissues composed of clones of which only a subset expresses Gal4. CoinFLP-LexGAD/Gal4 generates tissues composed of clones that express either Gal4 or LexGAD, thus allowing the study of interactions between different types of genetically manipulated cells. By combining CoinFLP-LexGAD/Gal4 with the split-GFP system GRASP, boundaries between genetically distinct cell populations can be visualized at high resolution. © 2015. Published by The Company of Biologists Ltd.

  9. Applying different quality and safety models in healthcare improvement work: Boundary objects and system thinking

    International Nuclear Information System (INIS)

    Wiig, Siri; Robert, Glenn; Anderson, Janet E.; Pietikainen, Elina; Reiman, Teemu; Macchi, Luigi; Aase, Karina

    2014-01-01

    A number of theoretical models can be applied to help guide quality improvement and patient safety interventions in hospitals. However there are often significant differences between such models and, therefore, their potential contribution when applied in diverse contexts. The aim of this paper is to explore how two such models have been applied by hospitals to improve quality and safety. We describe and compare the models: (1) The Organizing for Quality (OQ) model, and (2) the Design for Integrated Safety Culture (DISC) model. We analyze the theoretical foundations of the models, and show, by using a retrospective comparative case study approach from two European hospitals, how these models have been applied to improve quality and safety. The analysis shows that differences appear in the theoretical foundations, practical approaches and applications of the models. Nevertheless, the case studies indicate that the choice between the OQ and DISC models is of less importance for guiding the practice of quality and safety improvement work, as they are both systemic and share some important characteristics. The main contribution of the models lay in their role as boundary objects directing attention towards organizational and systems thinking, culture, and collaboration

  10. View-Invariant Gait Recognition Through Genetic Template Segmentation

    Science.gov (United States)

    Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

    2017-08-01

    Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.

  11. Development of a retrospective process for analyzing results of a HMM based posture recognition system in a functionalized nursing bed

    Directory of Open Access Journals (Sweden)

    Demmer Julia

    2017-09-01

    Full Text Available In the area of care in general but especially in the care of elderly, there is a great interest in deriving patient parameters preparation free. For this purpose, a load cell functionalized nursing bed has been developed at Niederrhein University of Applied Science. The system allows analysis and recognition of the persons’ positions and actions in the bed. The Hidden Markov Toolkit (HTK based posture recognition system was initially presented at the BMT 2015 by our research group. The initial system shows good results but to draw conclusions about the patient's condition, a minimum possible error rate should be achieved. For this purpose, a two-step retrospective analysis of the initial results was developed as an extension to improve the accuracy of the system.

  12. Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

    Energy Technology Data Exchange (ETDEWEB)

    Searles, D.B.

    1993-03-01

    The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

  13. Real-time optical multiple object recognition and tracking system and method

    Science.gov (United States)

    Chao, Tien-Hsin (Inventor); Liu, Hua-Kuang (Inventor)

    1990-01-01

    System for optically recognizing and tracking a plurality of objects within a field of vision. Laser (46) produces a coherent beam (48). Beam splitter (24) splits the beam into object (26) and reference (28) beams. Beam expanders (50) and collimators (52) transform the beams (26, 28) into coherent collimated light beams (26', 28'). A two-dimensional SLM (54), disposed in the object beam (26'), modulates the object beam with optical information as a function of signals from a first camera (16) which develops X and Y signals reflecting the contents of its field of vision. A hololens (38), positioned in the object beam (26') subsequent to the modulator (54), focuses the object beam at a plurality of focal points (42). A planar transparency-forming film (32), disposed with the focal points on an exposable surface, forms a multiple position interference filter (62) upon exposure of the surface and development processing of the film (32). A reflector (53) directing the reference beam (28') onto the film (32), exposes the surface, with images focused by the hololens (38), to form interference patterns on the surface. There is apparatus (16', 64) for sensing and indicating light passage through respective ones of the positions of the filter (62), whereby recognition of objects corresponding to respective ones of the positions of the filter (62) is affected. For tracking, apparatus (64) focuses light passing through the filter (62) onto a matrix of CCD's in a second camera (16') to form a two-dimensional display of the recognized objects.

  14. Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems

    Directory of Open Access Journals (Sweden)

    Yongwha Chung

    2013-09-01

    Full Text Available Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD and the Sparse Representation Classifier (SRC as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used and accurately (94% detection and 91% classification accuracy, either as a standalone solution or to complement known methods to obtain a more accurate solution.

  15. A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

    Science.gov (United States)

    Burl, M. C.; Fayyad, U. M.; Smyth, P.; Aubele, J. C.; Crumpler, L. S.

    1993-01-01

    The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary

  16. Numerical methods for stiff systems of two-point boundary value problems

    Science.gov (United States)

    Flaherty, J. E.; Omalley, R. E., Jr.

    1983-01-01

    Numerical procedures are developed for constructing asymptotic solutions of certain nonlinear singularly perturbed vector two-point boundary value problems having boundary layers at one or both endpoints. The asymptotic approximations are generated numerically and can either be used as is or to furnish a general purpose two-point boundary value code with an initial approximation and the nonuniform computational mesh needed for such problems. The procedures are applied to a model problem that has multiple solutions and to problems describing the deformation of thin nonlinear elastic beam that is resting on an elastic foundation.

  17. The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

    Science.gov (United States)

    Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

    2017-10-01

    This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

  18. Electrostatic interactions in finite systems treated with periodic boundary conditions: application to linear-scaling density functional theory.

    Science.gov (United States)

    Hine, Nicholas D M; Dziedzic, Jacek; Haynes, Peter D; Skylaris, Chris-Kriton

    2011-11-28

    We present a comparison of methods for treating the electrostatic interactions of finite, isolated systems within periodic boundary conditions (PBCs), within density functional theory (DFT), with particular emphasis on linear-scaling (LS) DFT. Often, PBCs are not physically realistic but are an unavoidable consequence of the choice of basis set and the efficacy of using Fourier transforms to compute the Hartree potential. In such cases the effects of PBCs on the calculations need to be avoided, so that the results obtained represent the open rather than the periodic boundary. The very large systems encountered in LS-DFT make the demands of the supercell approximation for isolated systems more difficult to manage, and we show cases where the open boundary (infinite cell) result cannot be obtained from extrapolation of calculations from periodic cells of increasing size. We discuss, implement, and test three very different approaches for overcoming or circumventing the effects of PBCs: truncation of the Coulomb interaction combined with padding of the simulation cell, approaches based on the minimum image convention, and the explicit use of open boundary conditions (OBCs). We have implemented these approaches in the ONETEP LS-DFT program and applied them to a range of systems, including a polar nanorod and a protein. We compare their accuracy, complexity, and rate of convergence with simulation cell size. We demonstrate that corrective approaches within PBCs can achieve the OBC result more efficiently and accurately than pure OBC approaches.

  19. Chasing boundaries and cascade effects in a coupled barrier - marshes - lagoon system

    Science.gov (United States)

    Lorenzo Trueba, J.; Mariotti, G.

    2015-12-01

    Low-lying coasts are often characterized by barriers islands, shore-parallel stretches of sand separated from the mainland by marshes and lagoons. We built an exploratory numerical model to examine the morphological feedbacks within an idealized barrier - marshes -lagoon system and predict its evolution under projected rates of sea level rise and sediment supply to the backbarrier environment. Our starting point is a recently developed morphodynamic model, which couples shoreface evolution and overwash processes in a dynamic framework. As such, the model is able to capture dynamics not reproduced by morphokinematic models, which advect geometries without specific concern to processes. These dynamics include periodic barrier retreat due to time lags in the shoreface response to barrier overwash, height drowning due to insufficient overwash fluxes as sea level rises, and width drowning, which occurs when the shoreface response rate is insufficient to maintain the barrier geometry during overwash-driven landward migration. We extended the model by coupling the barrier model with a model for the evolution of the marsh platform and the boundary between the marsh and the adjacent lagoon. The coupled model explicitly describes marsh edge processes and accounts for the modification of the wave regime associated with lagoon width (fetch). Model results demonstrate that changes in factors that are not typically associated with the dynamics of coastal barriers, such as the lagoon width and the rate of export/import of sediments from and to the lagoon, can lead to previously unidentified complex responses of the coupled system. In particular, a wider lagoon in the backbarrier, and/or a reduction in the supply of muddy sediments to the backbarrier, can increase barrier retreat rates and even trigger barrier drowning. Overall, our findings highlight the importance of incorporating backbarrier dynamics in models that aim at predicting the response of barrier systems.

  20. Nonlinear Gulf Stream Interaction with the Deep Western Boundary Current System: Observations and a Numerical Simulation

    Science.gov (United States)

    Dietrich, David E.; Mehra, Avichal; Haney, Robert L.; Bowman, Malcolm J.; Tseng, Yu-Heng

    2003-01-01

    Gulf Stream (GS) separation near its observed Cape Hatteras (CH) separation location, and its ensuing path and dynamics, is a challenging ocean modeling problem. If a model GS separates much farther north than CH, then northward GS meanders, which pinch off warm core eddies (rings), are not possible or are strongly constrained by the Grand Banks shelfbreak. Cold core rings pinch off the southward GS meanders. The rings are often re-absorbed by the GS. The important warm core rings enhance heat exchange and, especially, affect the northern GS branch after GS bifurcation near the New England Seamount Chain. This northern branch gains heat by contact with the southern branch water upstream of bifurcation, and warms the Arctic Ocean and northern seas, thus playing a major role in ice dynamics, thermohaline circulation and possible global climate warming. These rings transport heat northward between the separated GS and shelf slope/Deep Western Boundary Current system (DWBC). This region has nearly level time mean isopycnals. The eddy heat transport convergence/divergence enhances the shelfbreak and GS front intensities and thus also increases watermass transformation. The fronts are maintained by warm advection by the Florida Current and cool advection by the DWBC. Thus, the GS interaction with the DWBC through the intermediate eddy field is climatologically important.

  1. Development of an automated speech recognition interface for personal emergency response systems

    Directory of Open Access Journals (Sweden)

    Mihailidis Alex

    2009-07-01

    Full Text Available Abstract Background Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype. Methods The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults. Results and discussion The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability. Conclusion The use of an automated

  2. Variational methods for boundary value problems for systems of elliptic equations

    CERN Document Server

    Lavrent'ev, M A

    2012-01-01

    Famous monograph by a distinguished mathematician presents an innovative approach to classical boundary value problems. The treatment employs the basic scheme first suggested by Hilbert and developed by Tonnelli. 1963 edition.

  3. Modular Adaptive System Based on a Multi-Stage Neural Structure for Recognition of 2D Objects of Discontinuous Production

    Directory of Open Access Journals (Sweden)

    I. Topalova

    2005-03-01

    Full Text Available This is a presentation of a new system for invariant recognition of 2D objects with overlapping classes, that can not be effectively recognized with the traditional methods. The translation, scale and partial rotation invariant contour object description is transformed in a DCT spectrum space. The obtained frequency spectrums are decomposed into frequency bands in order to feed different BPG neural nets (NNs. The NNs are structured in three stages - filtering and full rotation invariance; partial recognition; general classification. The designed multi-stage BPG Neural Structure shows very good accuracy and flexibility when tested with 2D objects used in the discontinuous production. The reached speed and the opportunuty for an easy restructuring and reprogramming of the system makes it suitable for application in different applied systems for real time work.

  4. Autonomic nervous system dynamics for mood and emotional-state recognition significant advances in data acquisition, signal processing and classification

    CERN Document Server

    Valenza, Gaetano

    2014-01-01

    This monograph reports on advances in the measurement and study of autonomic nervous system (ANS) dynamics as a source of reliable and effective markers for mood state recognition and assessment of emotional responses. Its primary impact will be in affective computing and the application of emotion-recognition systems. Applicative studies of biosignals such as: electrocardiograms; electrodermal responses; respiration activity; gaze points; and pupil-size variation are covered in detail, and experimental results explain how to characterize the elicited affective levels and mood states pragmatically and accurately using the information thus extracted from the ANS. Nonlinear signal processing techniques play a crucial role in understanding the ANS physiology underlying superficially noticeable changes and provide important quantifiers of cardiovascular control dynamics. These have prognostic value in both healthy subjects and patients with mood disorders. Moreover, Autonomic Nervous System Dynamics for Mood and ...

  5. [Development of a new position-recognition system for robotic radiosurgery systems using machine vision].

    Science.gov (United States)

    Mohri, Issai; Umezu, Yoshiyuki; Fukunaga, Junnichi; Tane, Hiroyuki; Nagata, Hironori; Hirashima, Hideaki; Nakamura, Katsumasa; Hirata, Hideki

    2014-08-01

    CyberKnife(®) provides continuous guidance through radiography, allowing instantaneous X-ray images to be obtained; it is also equipped with 6D adjustment for patient setup. Its disadvantage is that registration is carried out just before irradiation, making it impossible to perform stereo-radiography during irradiation. In addition, patient movement cannot be detected during irradiation. In this study, we describe a new registration system that we term "Machine Vision," which subjects the patient to no additional radiation exposure for registration purposes, can be set up promptly, and allows real-time registration during irradiation. Our technique offers distinct advantages over CyberKnife by enabling a safer and more precise mode of treatment. "Machine Vision," which we have designed and fabricated, is an automatic registration system that employs three charge coupled device cameras oriented in different directions that allow us to obtain a characteristic depiction of the shape of both sides of the fetal fissure and external ears in a human head phantom. We examined the degree of precision of this registration system and concluded it to be suitable as an alternative method of registration without radiation exposure when displacement is less than 1.0 mm in radiotherapy. It has potential for application to CyberKnife in clinical treatment.

  6. Multimodal eye recognition

    Science.gov (United States)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  7. Motion of particles in solar and galactic systems by using Neumann boundary condition

    Science.gov (United States)

    Shenavar, Hossein

    2016-12-01

    A new equation of motion, which is derived previously by imposing Neumann boundary condition on cosmological perturbation equations (Shenavar in Astrophys. Space Sci., 2016a, doi: 10.1007/s10509-016-2676-5), is investigated. By studying the precession of perihelion, it is shown that the new equation of motion suggests a small, though detectable, correction in orbits of solar system objects. Then a system of particles is surveyed to have a better understanding of galactic structures. Also the general form of the force law is introduced by which the rotation curve and mass discrepancy of axisymmetric disks of stars are derived. In addition, it is suggested that the mass discrepancy as a function of centripetal acceleration becomes significant near a constant acceleration 2c1a0 where c1 is the Neumann constant and a0 = 6.59 ×10^{-10} m/s2 is a fundamental acceleration. Furthermore, it is shown that a critical surface density equal to σ0=a0/G, in which G is the Newton gravitational constant, has a significant role in rotation curve and mass discrepancy plots. Also, the specific form of NFW mass density profile at small radii, ρ∝1/r, is explained too. Finally, the present model will be tested by using a sample of 39 LSB galaxies for which we will show that the rotation curve fittings are generally acceptable. The derived mass to light ratios too are found within the plausible bound except for the galaxy F571-8.

  8. Surface mixing and biological activity in the four Eastern Boundary Upwelling Systems

    Directory of Open Access Journals (Sweden)

    V. Rossi

    2009-08-01

    Full Text Available Eastern Boundary Upwelling Systems (EBUS are characterized by a high productivity of plankton associated with large commercial fisheries, thus playing key biological and socio-economical roles. Since they are populated by several physical oceanic structures such as filaments and eddies, which interact with the biological processes, it is a major challenge to study this sub- and mesoscale activity in connection with the chlorophyll distribution. The aim of this work is to make a comparative study of these four upwelling systems focussing on their surface stirring, using the Finite Size Lyapunov Exponents (FSLEs, and their biological activity, based on satellite data. First, the spatial distribution of horizontal mixing is analysed from time averages and from probability density functions of FSLEs, which allow us to divide each areas in two different subsystems. Then we studied the temporal variability of surface stirring focussing on the annual and seasonal cycle. We also proposed a ranking of the four EBUS based on the averaged mixing intensity. When investigating the links with chlorophyll concentration, the previous subsystems reveal distinct biological signatures. There is a global negative correlation between surface horizontal mixing and chlorophyll standing stocks over the four areas. To try to better understand this inverse relationship, we consider the vertical dimension by looking at the Ekman-transport and vertical velocities. We suggest the possibility of a changing response of the phytoplankton to sub/mesoscale turbulence, from a negative effect in the very productive coastal areas to a positive one in the open ocean. This study provides new insights for the understanding of the variable biological productivity in the ocean, which results from both dynamics of the marine ecosystem and of the 3-D turbulent medium.

  9. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  10. Development of ion diagnostic system based on electrostatic probe in the boundary plasma of the JFT-2M tokamak

    Energy Technology Data Exchange (ETDEWEB)

    Uehara, Kazuya; Kawakami, Tomohide [Japan Atomic Energy Research Inst., Naka, Ibaraki (Japan). Naka Fusion Research Establishment; Amemiya, Hiroshi; Hoethker, K.; Cosler, A.; Bieger, W.

    1995-06-01

    An ion diagnostic system using electrostatic probes for measurements in the JFT-2M tokamak boundary plasma has been developed under the collaboration program between KFA and JAERI. The rotating double probe system, on which the Hoethker double probe and Amemiya asymmetric probe can mounted, are manufactured at KFA workshop while the linear driver to support the rotating double probe, the ion toothbrush probe, the Katsumata probe and the cubic Mach probe are developed at JAERI. This report describes the hardware of this probe system for ion diagnostics in the boundary plasma and preliminary data obtained by means of this system. Furthermore, results on the transport are estimated on the basis of these probe data. (author).

  11. Development of ion diagnostic system based on electrostatic probe in the boundary plasma of the JFT-2M tokamak

    International Nuclear Information System (INIS)

    Uehara, Kazuya; Kawakami, Tomohide; Amemiya, Hiroshi; Hoethker, K.; Cosler, A.; Bieger, W.

    1995-06-01

    An ion diagnostic system using electrostatic probes for measurements in the JFT-2M tokamak boundary plasma has been developed under the collaboration program between KFA and JAERI. The rotating double probe system, on which the Hoethker double probe and Amemiya asymmetric probe can mounted, are manufactured at KFA workshop while the linear driver to support the rotating double probe, the ion toothbrush probe, the Katsumata probe and the cubic Mach probe are developed at JAERI. This report describes the hardware of this probe system for ion diagnostics in the boundary plasma and preliminary data obtained by means of this system. Furthermore, results on the transport are estimated on the basis of these probe data. (author)

  12. A state-of-the-art hotspot recognition system for full chip verification with lithographic simulation

    Science.gov (United States)

    Simmons, Mark C.; Kang, Jae-Hyun; Kim, Youngkeun; Park, Joung Il; Paek, Seung weon; Kim, Kee-sup

    2011-04-01

    In today's semiconductor industry, prior to wafer fabrication, it has become a desirable practice to scan layout designs for lithography-induced defects using advanced process window simulations in conjunction with corresponding manufacturing checks. This methodology has been proven to provide the highest level of accuracy when correlating systematic defects found on the wafer with those identified through simulation. To date, when directly applying this methodology at the full chip level, there has been unfavorable expenses incurred that are associated with simulation which are currently overshadowing its primary benefit of accuracy - namely, long runtimes and the requirement for an abundance of cpus. Considering the aforementioned, the industry has begun to lean towards a more practical application for hotspot identification that revolves around topological pattern recognition in an attempt to sidestep the simulation runtime. This solution can be much less costly when weighing against the negative runtime overhead of simulation. The apparent benefits of pattern matching are, however, counterbalanced with a fundamental concern regarding detection accuracy; topological pattern identification can only detect polygonal configurations, or some derivative of a configuration, which have been previously identified. It is evident that both systems have their strengths and their weaknesses, and that one system's strength is the other's weakness, and vice-versa. A novel hotspot detection methodology that utilizes pattern matching combined with lithographic simulation will be introduced. This system will attempt to minimize the negative aspects of both pattern matching and simulation. The proposed methodology has a high potential to decrease the amount of processing time spent during simulation, to relax the high cpu count requirement, and to maximize pattern matching accuracy by incorporating a multi-staged pattern matching flow prior to performing simulation on a reduced

  13. Design and application of pulse information acquisition and analysis system with dynamic recognition in traditional Chinese medicine.

    Science.gov (United States)

    Zhang, Jian; Niu, Xin; Yang, Xue-zhi; Zhu, Qing-wen; Li, Hai-yan; Wang, Xuan; Zhang, Zhi-guo; Sha, Hong

    2014-09-01

    To design the pulse information which includes the parameter of pulse-position, pulse-number, pulse-shape and pulse-force acquisition and analysis system with function of dynamic recognition, and research the digitalization and visualization of some common cardiovascular mechanism of single pulse. To use some flexible sensors to catch the radial artery pressure pulse wave and utilize the high frequency B mode ultrasound scanning technology to synchronously obtain the information of radial extension and axial movement, by the way of dynamic images, then the gathered information was analyzed and processed together with ECG. Finally, the pulse information acquisition and analysis system was established which has the features of visualization and dynamic recognition, and it was applied to serve for ten healthy adults. The new system overcome the disadvantage of one-dimensional pulse information acquisition and process method which was common used in current research area of pulse diagnosis in traditional Chinese Medicine, initiated a new way of pulse diagnosis which has the new features of dynamic recognition, two-dimensional information acquisition, multiplex signals combination and deep data mining. The newly developed system could translate the pulse signals into digital, visual and measurable motion information of vessel.

  14. Pattern Recognition for Robotic Fish Swimming Gaits Based on Artificial Lateral Line System and Subtractive Clustering Algorithms

    Directory of Open Access Journals (Sweden)

    Hongli Liu

    2014-11-01

    Full Text Available The complicated and changeable underwater environment increases the difficulty of pattern recognition for robotic fish swimming gaits. Aiming at this question, environment sensing and pattern recognition using an artificial lateral system are investigated in this work. Imitating lateral line of real fish in nature, a novel artificial lateral line system for robotic fish is designed in this paper. Based on this novel system, the pressure information around robotic fish can be sensed when robotic fish swims in different gaits, so the feature points can be extracted from the pressure information. And then, based on the feature points, a subtractive clustering algorithm is used to recognize the swimming gaits of robotic fish. So the pattern state of robotic fish can be obtained, which provides a basis for the quick control of robotic fish in water. Finally, a validation experiment is conducted with freely swimming robotic fish. The validity of this novel system is demonstrated. And the feasibility and accuracy of subtractive clustering algorithm used in pattern recognition for robotic fish is verified too.

  15. Very Early Systemic Sclerosis and Pre-systemic Sclerosis: Definition, Recognition, Clinical Relevance and Future Directions.

    Science.gov (United States)

    Bellando-Randone, Silvia; Matucci-Cerinic, Marco

    2017-09-18

    The approach to systemic sclerosis (SSc) has changed over the years with an increasing focus on the very early diagnosis of the disease. The terminology identifying patients in the early phase of SSc has been significantly confusing in the last three decades. The purpose of this article is to analyze how the concept of "very early SSc" has evolved over the years, which is the role of an early diagnosis and how early treat patients. Several attempts have been made over time, to create more sensitive and specific classification criteria to include the largest number of SSc patients, also in the earliest phase. An algorythm for the very early diagnosis of SSc was identified, diagnostic preliminary criteria proposed, and new 2013 ACR/EULAR SSc classification criteria published, including new items and adding emphasis to the vasculopathic manifestations. True biomarkers that could predict the disease evolution are still missing. Treat or not to treat patients in the earliest phases still remain a dilemma. For the moment, the only feasible clinical strategy in very early SSc remains a tight follow up program to detect in "real time" the early internal organ involvement which may allow an aggressive therapeutic agenda.

  16. Reduced order models, inertial manifolds, and global bifurcations: searching instability boundaries in nuclear power systems

    International Nuclear Information System (INIS)

    Suarez-Antola, Roberto; Ministerio de Industria, Energia y Mineria, Montevideo

    2011-01-01

    One of the goals of nuclear power systems design and operation is to restrict the possible states of certain critical subsystems to remain inside a certain bounded set of admissible states and state variations. In the framework of an analytic or numerical modeling process of a BWR power plant, this could imply first to find a suitable approximation to the solution manifold of the differential equations describing the stability behavior, and then a classification of the different solution types concerning their relation with the operational safety of the power plant. Inertial manifold theory gives a foundation for the construction and use of reduced order models (ROM's) of reactor dynamics to discover and characterize meaningful bifurcations that may pass unnoticed during digital simulations done with full scale computer codes of the nuclear power plant. The March-Leuba's BWR ROM is generalized and used to exemplify the analytical approach developed here. A nonlinear integral-differential equation in the logarithmic power is derived. Introducing a KBM Ansatz, a coupled set of two nonlinear ordinary differential equations is obtained. Analytical formulae are derived for the frequency of oscillation and the parameters that determine the stability of the steady states, including sub- and supercritical PAH bifurcations. A Bautin's bifurcation scenario seems possible on the power-flow plane: near the boundary of stability, a region where stable steady states are surrounded by unstable limit cycles surrounded at their turn by stable limit cycles. The analytical results are compared with recent digital simulations and applications of semi-analytical bifurcation theory done with reduced order models of BWR. (author)

  17. Reduced order models, inertial manifolds, and global bifurcations: searching instability boundaries in nuclear power systems

    Energy Technology Data Exchange (ETDEWEB)

    Suarez-Antola, Roberto, E-mail: roberto.suarez@miem.gub.u, E-mail: rsuarez@ucu.edu.u [Universidad Catolica del Uruguay, Montevideo (Uruguay). Fac. de Ingenieria y Tecnologias. Dept. de Matematica; Ministerio de Industria, Energia y Mineria, Montevideo (Uruguay). Direccion General de Secretaria

    2011-07-01

    One of the goals of nuclear power systems design and operation is to restrict the possible states of certain critical subsystems to remain inside a certain bounded set of admissible states and state variations. In the framework of an analytic or numerical modeling process of a BWR power plant, this could imply first to find a suitable approximation to the solution manifold of the differential equations describing the stability behavior, and then a classification of the different solution types concerning their relation with the operational safety of the power plant. Inertial manifold theory gives a foundation for the construction and use of reduced order models (ROM's) of reactor dynamics to discover and characterize meaningful bifurcations that may pass unnoticed during digital simulations done with full scale computer codes of the nuclear power plant. The March-Leuba's BWR ROM is generalized and used to exemplify the analytical approach developed here. A nonlinear integral-differential equation in the logarithmic power is derived. Introducing a KBM Ansatz, a coupled set of two nonlinear ordinary differential equations is obtained. Analytical formulae are derived for the frequency of oscillation and the parameters that determine the stability of the steady states, including sub- and supercritical PAH bifurcations. A Bautin's bifurcation scenario seems possible on the power-flow plane: near the boundary of stability, a region where stable steady states are surrounded by unstable limit cycles surrounded at their turn by stable limit cycles. The analytical results are compared with recent digital simulations and applications of semi-analytical bifurcation theory done with reduced order models of BWR. (author)

  18. Vertical Sampling Scales for Atmospheric Boundary Layer Measurements from Small Unmanned Aircraft Systems (sUAS

    Directory of Open Access Journals (Sweden)

    Benjamin L. Hemingway

    2017-09-01

    Full Text Available The lowest portion of the Earth’s atmosphere, known as the atmospheric boundary layer (ABL, plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to understanding the exchange of energy within this region, but conventional surveillance techniques such as towers, radar, weather balloons, and satellites do not provide adequate spatial and/or temporal coverage for monitoring weather events. Small unmanned aircraft, or aerial, systems (sUAS provide a versatile, dynamic platform for atmospheric sensing that can provide higher spatio-temporal sampling frequencies than available through most satellite sensing methods. They are also able to sense portions of the atmosphere that cannot be measured from ground-based radar, weather stations, or weather balloons and have the potential to fill gaps in atmospheric sampling. However, research on the vertical sampling scales for collecting atmospheric measurements from sUAS and the variabilities of these scales across atmospheric phenomena (e.g., temperature and humidity is needed. The objective of this study is to use variogram analysis, a common geostatistical technique, to determine optimal spatial sampling scales for two atmospheric variables (temperature and relative humidity captured from sUAS. Results show that vertical sampling scales of approximately 3 m for temperature and 1.5–2 m for relative humidity were sufficient to capture the spatial structure of these phenomena under the conditions tested. Future work is needed to model these scales across the entire ABL as well as under variable conditions.

  19. Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems.

    Science.gov (United States)

    Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

    2017-06-01

    This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be

  20. Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

    Science.gov (United States)

    Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

    2017-06-01

    Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

  1. Derivative matrices of a skew ray for spherical boundary surfaces and their applications in system analysis and design.

    Science.gov (United States)

    Lin, Psang Dain

    2014-05-10

    In a previous paper [Appl. Opt.52, 4151 (2013)], we presented the first- and second-order derivatives of a ray for a flat boundary surface to design prisms. In this paper, that scheme is extended to determine the Jacobian and Hessian matrices of a skew ray as it is reflected/refracted at a spherical boundary surface. The validity of the proposed approach as an analysis and design tool is demonstrated using an axis-symmetrical system for illustration purpose. It is found that these two matrices can provide the search direction used by existing gradient-based schemes to minimize the merit function during the optimization stage of the optical system design process. It is also possible to make the optical system designs more automatic, if the image defects can be extracted from the Jacobian and Hessian matrices of a skew ray.

  2. Transpressional segment boundaries in strike-slip fault systems offshore southern California: Implications for fluid expulsion and cold seep habitats

    Science.gov (United States)

    Maloney, Jillian M.; Grupe, Benjamin M.; Pasulka, Alexis L.; Dawson, Katherine S.; Case, David H.; Frieder, Christina A.; Levin, Lisa A.; Driscoll, Neal W.

    2015-05-01

    The importance of tectonics and fluid flow in controlling cold seep habitats has long been appreciated at convergent margins but remains poorly understood in strike-slip systems. Here we present geophysical, geochemical, and biological data from an active methane seep offshore from Del Mar, California, in the inner California borderlands (ICB). The location of this seep appears controlled by localized transpression associated with a step in the San Diego Trough fault zone and provides an opportunity to examine the interplay between fluid expulsion and restraining step overs along strike-slip fault systems. These segment boundaries may have important controls on seep locations in the ICB and other margins characterized by strike-slip faulting (e.g., Greece, Sea of Marmara, and Caribbean). The strike-slip fault systems offshore southern California appear to have a limited distribution of seep sites compared to a wider distribution at convergent plate boundaries, which may influence seep habitat diversity and connectivity.

  3. Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems.

    Science.gov (United States)

    Fedorov, A K; Anufriev, M N; Zhirnov, A A; Stepanov, K V; Nesterov, E T; Namiot, D E; Karasik, V E; Pnev, A B

    2016-03-01

    We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples.

  4. Multi-layer potentials and boundary problems for higher-order elliptic systems in Lipschitz domains

    CERN Document Server

    Mitrea, Irina

    2013-01-01

    Many phenomena in engineering and mathematical physics can be modeled by means of boundary value problems for a certain elliptic differential operator in a given domain. When the differential operator under discussion is of second order a variety of tools are available for dealing with such problems, including boundary integral methods, variational methods, harmonic measure techniques, and methods based on classical harmonic analysis. When the differential operator is of higher-order (as is the case, e.g., with anisotropic plate bending when one deals with a fourth order operator) only a few options could be successfully implemented. In the 1970s Alberto Calderón, one of the founders of the modern theory of Singular Integral Operators, advocated the use of layer potentials for the treatment of higher-order elliptic boundary value problems. The present monograph represents the first systematic treatment based on this approach. This research monograph lays, for the first time, the mathematical foundation aimed...

  5. Technology for Boundaries

    DEFF Research Database (Denmark)

    Bødker, Susanne; Kristensen, Jannie Friis; Nielsen, Christina

    2003-01-01

    This paper presents a study of an organisation, which is undergoing a process transforming organisational and technological boundaries. In particular, we shall look at three kinds of boundaries: the work to maintain and change the boundary between the organisation and its customers; boundaries...... between competencies within the organisation; and boundaries between various physical locations of work, in particular between what is done in the office and what is done on site. Maintaining and changing boundaries are the processes through which a particular community sustains its identity and practice...... on the one hand, and where it is confronted with the identity and practices on the other.The organisation being studied employs a multitude of IT systems that support and maintain these boundaries in a particular manner that are in many ways inappropriate to the current needs of the organisation...

  6. Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment.

    Science.gov (United States)

    Lemaire, Edward D; Tundo, Marco D; Baddour, Natalie

    2015-12-11

    recognition systems in rehabilitation medicine where mobility monitoring may be beneficial in clinical decision-making.

  7. Reduced order models, inertial manifolds, and global bifurcations: searching instability boundaries in nuclear power systems

    International Nuclear Information System (INIS)

    Suarez Antola, R.

    2011-01-01

    One of the goals of nuclear power systems design and operation is to restrict the possible states of certain critical subsystems, during steady operation and during transients, to remain inside a certain bounded set of admissible states and state variations. Also, during transients, certain restrictions must be imposed on the time scale of evolution of the critical subsystem's state. A classification of the different solution types concerning their relation with the operational safety of the power plant is done by distributing the different solution types in relation with the exclusion region of the power-flow map. In the framework of an analytic or numerical modeling process of a boiling water reactor (BWR) power plant, this could imply first to find an suitable approximation to the solution manifold of the differential equations describing the stability behavior of this nonlinear system, and then a classification of the different solution types concerning their relation with the operational safety of the power plant, by distributing the different solution types in relation with the exclusion region of the power-flow map. Inertial manifold theory gives a foundation for the construction and use of reduced order models (ROM's) of reactor dynamics to discover and characterize meaningful bifurcations that may pass unnoticed during digital simulations done with full scale computer codes of the nuclear power plant. The March-Leuba's BWR ROM is used to exemplify the analytical approach developed here. The equation for excess void reactivity of this ROM is generalized. A nonlinear integral-differential equation in the logarithmic power is derived, including the generalized thermal-hydraulics feedback on the reactivity. Introducing a Krilov- Bogoliubov-Mitropolsky (KBM) ansatz with both amplitude and phase being slowly varying functions of time relative to the center period of oscillation, a coupled set of nonlinear ordinary differential equations for amplitude and phase

  8. Entropy criteria applied to pattern selection in systems with free boundaries

    Science.gov (United States)

    Kirkaldy, J. S.

    1985-10-01

    The steady state differential or integral equations which describe patterned dissipative structures, typically to be identified with first order phase transformation morphologies like isothermal pearlites, are invariably degenerate in one or more order parameters (the lamellar spacing in the pearlite case). It is often observed that a different pattern is attained at the steady state for each initial condition (the hysteresis or metastable case). Alternatively, boundary perturbations and internal fluctuations during transition up to, or at the steady state, destroy the path coherence. In this case a statistical ensemble of imperfect patterns often emerges which represents a fluctuating but recognizably patterned and unique average steady state. It is cases like cellular, lamellar pearlite, involving an assembly of individual cell patterns which are regularly perturbed by local fluctuation and growth processes, which concern us here. Such weakly fluctuating nonlinear steady state ensembles can be arranged in a thought experiment so as to evolve as subsystems linking two very large mass-energy reservoirs in isolation. Operating on this discontinuous thermodynamic ideal, Onsager’s principle of maximum path probability for isolated systems, which we interpret as a minimal time correlation function connecting subsystem and baths, identifies the stable steady state at a parametric minimum or maximum (or both) in the dissipation rate. This nonlinear principle is independent of the Principle of Minimum Dissipation which is applicable in the linear regime of irreversible thermodynamics. The statistical argument is equivalent to the weak requirement that the isolated system entropy as a function of time be differentiable to the second order despite the macroscopic pattern fluctuations which occur in the subsystem. This differentiability condition is taken for granted in classical stability theory based on the 2nd Law. The optimal principle as applied to isothermal and

  9. An urban systems framework to assess the trans-boundary food-energy-water nexus: implementation in Delhi, India

    Science.gov (United States)

    Ramaswami, Anu; Boyer, Dana; Singh Nagpure, Ajay; Fang, Andrew; Bogra, Shelly; Bakshi, Bhavik; Cohen, Elliot; Rao-Ghorpade, Ashish

    2017-02-01

    This paper develops a generalizable systems framework to analyze the food-energy-water (FEW) nexus from an urban systems perspective, connecting in- and trans-boundary interactions, quantifying multiple environmental impacts of community-wide FEW provisioning to cities, and visualizing FEW supply-chain risks posed to cities by the environment. Delhi’s community-wide food demand includes household consumption by socio-economic-strata, visitors- and industrial food-use. This demand depends 90%, 76%, and 86% on trans-boundary supply of FEW, respectively. Supply chain data reveal unique features of trans-boundary FEW production regions (e.g. irrigation-electricity needs and GHG intensities of power-plants), yielding supply chain-informed coupled energy-water-GHG footprints of FEW provisioning to Delhi. Agri-food supply contributes to both GHG (19%) and water-footprints (72%-82%) of Delhi’s FEW provisioning, with milk, rice and wheat dominating these footprints. Analysis of FEW interactions within Delhi found >75% in-boundary water-use for food is for urban agriculture and >76% in-boundary energy-use for food is from cooking fuels. Food waste-to-energy and energy-intensity of commercial and industrial food preparation are key data gaps. Visualizing supply chains shows >75% of water embodied in Delhi’s FEW supply is extracted from locations over-drafting ground water. These baseline data enable evaluation of future urban FEW scenarios, comparing impacts of demand shifts, production shifts, and emerging technologies and policies, within and outside of cities.

  10. Towards social touch intelligence: developing a robust system for automatic touch recognition

    NARCIS (Netherlands)

    Jung, Merel Madeleine

    2014-01-01

    Touch behavior is of great importance during social interaction. Automatic recognition of social touch is necessary to transfer the touch modality from interpersonal interaction to other areas such as Human-Robot Interaction (HRI). This paper describes a PhD research program on the automatic

  11. Description and Recognition of the Concept of Social Capital in Higher Education System

    Science.gov (United States)

    Tonkaboni, Forouzan; Yousefy, Alireza; Keshtiaray, Narges

    2013-01-01

    The current research is intended to describe and recognize the concept of social capital in higher education based on theoretical method in a descriptive-analytical approach. Description and Recognition of the data, gathered from theoretical and experimental studies, indicated that social capital is one of the most important indices for…

  12. Automatic speech recognition used for evaluation of text-to-speech systems

    Czech Academy of Sciences Publication Activity Database

    Vích, Robert; Nouza, J.; Vondra, Martin

    -, č. 5042 (2008), s. 136-148 ISSN 0302-9743 R&D Projects: GA AV ČR 1ET301710509; GA AV ČR 1QS108040569 Institutional research plan: CEZ:AV0Z20670512 Keywords : speech recognition * speech processing Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

  13. Pattern recognition principles

    Science.gov (United States)

    Tou, J. T.; Gonzalez, R. C.

    1974-01-01

    The present work gives an account of basic principles and available techniques for the analysis and design of pattern processing and recognition systems. Areas covered include decision functions, pattern classification by distance functions, pattern classification by likelihood functions, the perceptron and the potential function approaches to trainable pattern classifiers, statistical approach to trainable classifiers, pattern preprocessing and feature selection, and syntactic pattern recognition.

  14. Paradigms in object recognition

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.

    1999-09-01

    A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)

  15. On preconditioning techniques for dense linear systems arising from singular boundary integral equations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Ke [Univ. of Liverpool (United Kingdom)

    1996-12-31

    We study various preconditioning techniques for the iterative solution of boundary integral equations, and aim to provide a theory for a class of sparse preconditioners. Two related ideas are explored here: singularity separation and inverse approximation. Our preliminary conclusion is that singularity separation based preconditioners perform better than approximate inverse based while it is desirable to have both features.

  16. Aerosols in the convective boundary layer: Shortwave radiation effects on the coupled land-atmosphere system

    NARCIS (Netherlands)

    Wilde Barbaro, E.; Vilà-Guerau de Arellano, J.; Ouwersloot, H.G.; Schroter, J.S.; Donovan, D.P.; Krol, M.C.

    2014-01-01

    By combining observations and numerical simulations, we investigated the responses of the surface energy budget and the convective boundary layer (CBL) dynamics to the presence of aerosols. A detailed data set containing (thermo)dynamic observations at CESAR (Cabauw Experimental Site for Atmospheric

  17. Correlation equations for classical continuous systems: finite-volume solutions for tempered boundary conditions

    International Nuclear Information System (INIS)

    Zagrebnov, V.A.

    1980-01-01

    Using resolvents for Kirkwood-Zalburg, Kirkwood-Ruelle and Meier-Montroll operators, solutions of the finite-volume correlation equations for tempered boundary conditions are obtained explicity. The uniqueness theorem is proved. A connection of the correlation equations with the Dobrushin-Landford-Ruelle equations for the Gibbs probability measure is discussed

  18. Exchanges across land-water-scape boundaries in urban systems: strategies for reducing nitrate pollution.

    Science.gov (United States)

    Cadenasso, M L; Pickett, S T A; Groffman, P M; Band, L E; Brush, G S; Galvin, M F; Grove, J M; Hagar, G; Marshall, V; McGrath, B P; O'Neil-Dunne, J P M; Stack, W P; Troy, A R

    2008-01-01

    Conservation in urban areas typically focuses on biodiversity and large green spaces. However, opportunities exist throughout urban areas to enhance ecological functions. An important function of urban landscapes is retaining nitrogen thereby reducing nitrate pollution to streams and coastal waters. Control of nonpoint nitrate pollution in urban areas was originally based on the documented importance of riparian zones in agricultural and forested ecosystems. The watershed and boundary frameworks have been used to guide stream research and a riparian conservation strategy to reduce nitrate pollution in urban streams. But is stream restoration and riparian-zone conservation enough? Data from the Baltimore Ecosystem Study and other urban stream research indicate that urban riparian zones do not necessarily prevent nitrate from entering, nor remove nitrate from, streams. Based on this insight, policy makers in Baltimore extended the conservation strategy throughout larger watersheds, attempting to restore functions that no longer took place in riparian boundaries. Two urban revitalization projects are presented as examples aimed at reducing nitrate pollution to stormwater, streams, and the Chesapeake Bay. An adaptive cycle of ecological urban design synthesizes the insights from the watershed and boundary frameworks, from new data, and from the conservation concerns of agencies and local communities. This urban example of conservation based on ameliorating nitrate water pollution extends the initial watershed-boundary approach along three dimensions: 1) from riparian to urban land-water-scapes; 2) from discrete engineering solutions to ecological design approaches; and 3) from structural solutions to inclusion of individual, household, and institutional behavior.

  19. Existence of global solutions to free boundary value problems for bipolar Navier-Stokes-Possion systems

    Directory of Open Access Journals (Sweden)

    Jian Liu

    2013-09-01

    Full Text Available In this article, we consider the free boundary value problem for one-dimensional compressible bipolar Navier-Stokes-Possion (BNSP equations with density-dependent viscosities. For general initial data with finite energy and the density connecting with vacuum continuously, we prove the global existence of the weak solution. This extends the previous results for compressible NS [27] to NSP.

  20. Boltzmann’s Six-Moment One-Dimensional Nonlinear System Equations with the Maxwell-Auzhan Boundary Conditions

    Directory of Open Access Journals (Sweden)

    A. Sakabekov

    2016-01-01

    Full Text Available We prove existence and uniqueness of the solution of the problem with initial and Maxwell-Auzhan boundary conditions for nonstationary nonlinear one-dimensional Boltzmann’s six-moment system equations in space of functions continuous in time and summable in square by a spatial variable. In order to obtain a priori estimation of the initial and boundary value problem for nonstationary nonlinear one-dimensional Boltzmann’s six-moment system equations we get the integral equality and then use the spherical representation of vector. Then we obtain the initial value problem for Riccati equation. We have managed to obtain a particular solution of this equation in an explicit form.