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Sample records for hole recognition system

  1. DEVELOPMENT OF HOLE RECOGNITION SYSTEM FROM STEP FILE

    Directory of Open Access Journals (Sweden)

    C. F. Tan

    2017-11-01

    Full Text Available This paper describes the development of Hole Recognition System (HRS for Computer-Aided Process Planning (CAPP using a neutral data format produced by CAD system. The geometrical data of holes is retrieved from STandard for the Exchange of Product model data (STEP. Rule-based algorithm is used during recognising process. Current implementation of feature recognition is limited to simple hole feat ures. Test results are presented to demonstrate the capabilities of the feature recognition algorithm.

  2. Hole Feature on Conical Face Recognition for Turning Part Model

    Science.gov (United States)

    Zubair, A. F.; Abu Mansor, M. S.

    2018-03-01

    Computer Aided Process Planning (CAPP) is the bridge between CAD and CAM and pre-processing of the CAD data in the CAPP system is essential. For CNC turning part, conical faces of part model is inevitable to be recognised beside cylindrical and planar faces. As the sinus cosines of the cone radius structure differ according to different models, face identification in automatic feature recognition of the part model need special intention. This paper intends to focus hole on feature on conical faces that can be detected by CAD solid modeller ACIS via. SAT file. Detection algorithm of face topology were generated and compared. The study shows different faces setup for similar conical part models with different hole type features. Three types of holes were compared and different between merge faces and unmerge faces were studied.

  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. Cognitive object recognition system (CORS)

    Science.gov (United States)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  5. An audiovisual emotion recognition system

    Science.gov (United States)

    Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

    2007-12-01

    Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

  6. 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.

  7. 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.

  8. 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...

  9. System of breast cancer recognition

    International Nuclear Information System (INIS)

    Rozhkova, N.I.

    1984-01-01

    The paper is concerned with the resUlts of the multimodality system of breast cancer recognition using methods, of clinical X-ray and cytological examinations. Altogether 1671 women were examined; breast cancer was detected in 165. Stage 1 was detected in 63 patients, Stage 2 in 34, Stage 3 in 34, and Stage 4 in 8. In 7% of the cases, tumors were inpalpable and could be detected by X-ray only. In 9.9% of the cases, the multicentric nature of tumor growth was established. In 71% tumors had a mixed histological structure. The system of breast cancer recognition provided for accurate diagnosis in 98% of the cases making it possible to avoid surgical intervention in 38%. Good diagnostic results are possible under conditions of a special mammology unit where a roentgenologist working in a close contact with surgeonns working in a close contact with surgeos and morphologists, performs the first stages of diagnosis beginning from clinical examination up to special methods that require X-ray control (paracentesis, ductography, pneumocystography, preoperative marking of the breast and marking of the remote sectors of the breast)

  10. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

    OpenAIRE

    S.PON SANGEETHA; DR.M.KARNAN

    2014-01-01

    The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

  11. System for automatic crate recognition

    Directory of Open Access Journals (Sweden)

    Radovan Kukla

    2012-01-01

    Full Text Available This contribution describes usage of computer vision and artificial intelligence methods for application. The method solves abuse of reverse vending machine. This topic has been solved as innovation voucher for the South Moravian Region. It was developed by Mendel university in Brno (Department of informatics – Faculty of Business and Economics and Department of Agricultural, Food and Environmental Engineering – Faculty of Agronomy together with the Czech subsidiary of Tomra. The project is focused on a possibility of integration industrial cameras and computers to process recognition of crates in the verse vending machine. The aim was the effective security system that will be able to save hundreds-thousands financial loss. As suitable development and runtime platform there was chosen product ControlWeb and VisionLab developed by Moravian Instruments Inc.

  12. 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.

  13. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    2013-12-01

    Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

  14. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Science.gov (United States)

    Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

    2013-01-01

    Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

  15. MASSIVE BLACK HOLES IN STELLAR SYSTEMS: 'QUIESCENT' ACCRETION AND LUMINOSITY

    International Nuclear Information System (INIS)

    Volonteri, M.; Campbell, D.; Mateo, M.; Dotti, M.

    2011-01-01

    Only a small fraction of local galaxies harbor an accreting black hole, classified as an active galactic nucleus. However, many stellar systems are plausibly expected to host black holes, from globular clusters to nuclear star clusters, to massive galaxies. The mere presence of stars in the vicinity of a black hole provides a source of fuel via mass loss of evolved stars. In this paper, we assess the expected luminosities of black holes embedded in stellar systems of different sizes and properties, spanning a large range of masses. We model the distribution of stars and derive the amount of gas available to a central black hole through a geometrical model. We estimate the luminosity of the black holes under simple, but physically grounded, assumptions on the accretion flow. Finally, we discuss the detectability of 'quiescent' black holes in the local universe.

  16. 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

  17. Black holes in binary stellar systems and galactic nuclei

    Science.gov (United States)

    Cherepashchuk, A. M.

    2014-04-01

    In the last 40 years, following pioneering papers by Ya B Zeldovich and E E Salpeter, in which a powerful energy release from nonspherical accretion of matter onto a black hole (BH) was predicted, many observational studies of black holes in the Universe have been carried out. To date, the masses of several dozen stellar-mass black holes (M_BH = (4{-}20) M_\\odot) in X-ray binary systems and of several hundred supermassive black holes (M_BH = (10^{6}{-}10^{10}) M_\\odot) in galactic nuclei have been measured. The estimated radii of these massive and compact objects do not exceed several gravitational radii. For about ten stellar-mass black holes and several dozen supermassive black holes, the values of the dimensionless angular momentum a_* have been estimated, which, in agreement with theoretical predictions, do not exceed the limiting value a_* = 0.998. A new field of astrophysics, so-called black hole demography, which studies the birth and growth of black holes and their evolutionary connection to other objects in the Universe, namely stars, galaxies, etc., is rapidly developing. In addition to supermassive black holes, massive stellar clusters are observed in galactic nuclei, and their evolution is distinct from that of supermassive black holes. The evolutionary relations between supermassive black holes in galactic centers and spheroidal stellar components (bulges) of galaxies, as well as dark-matter galactic haloes are brought out. The launch into Earth's orbit of the space radio interferometer RadioAstron opened up the real possibility of finally proving that numerous discovered massive and highly compact objects with properties very similar to those of black holes make up real black holes in the sense of Albert Einstein's General Relativity. Similar proofs of the existence of black holes in the Universe can be obtained by intercontinental radio interferometry at short wavelengths \\lambda \\lesssim 1 mm (the international program, Event Horizon Telescope).

  18. 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

  19. 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

  20. 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 stabili...... stabilizability. It is shown that it is possible to use the calculus to consider more general feedback systems in a variational setup.......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...

  1. Cross domains Arabic named entity recognition system

    Science.gov (United States)

    Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

    2016-07-01

    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.

  2. Topics in black-hole physics: geometric constraints on noncollapsing, gravitating systems, and tidal distortions of a Schwarzschild black hole

    International Nuclear Information System (INIS)

    Redmount, I.H.

    1984-01-01

    This dissertation consists of two studies on the general-relativistic theory of black holes. The first work concerns the fundamental issue of black-hole formation: in it geometric constraints are sought on gravitating matter systems, in the special case of axial symmetry, which determine whether or not those systems undergo gravitational collapse to form black holes. The second project deals with mechanical behavior of a black hole: specifically, the tidal deformation of a static black hole is studied by the gravitational fields of external bodies

  3. Black holes in binary stellar systems and galactic nuclei

    International Nuclear Information System (INIS)

    Cherepashchuk, A M

    2014-01-01

    In the last 40 years, following pioneering papers by Ya B Zeldovich and E E Salpeter, in which a powerful energy release from nonspherical accretion of matter onto a black hole (BH) was predicted, many observational studies of black holes in the Universe have been carried out. To date, the masses of several dozen stellar-mass black holes (M BH =(4−20)M ⊙ ) in X-ray binary systems and of several hundred supermassive black holes (M BH =(10 6 −10 10 )M ⊙ ) in galactic nuclei have been measured. The estimated radii of these massive and compact objects do not exceed several gravitational radii. For about ten stellar-mass black holes and several dozen supermassive black holes, the values of the dimensionless angular momentum a ∗ have been estimated, which, in agreement with theoretical predictions, do not exceed the limiting value a ∗ =0.998. A new field of astrophysics, so-called black hole demography, which studies the birth and growth of black holes and their evolutionary connection to other objects in the Universe, namely stars, galaxies, etc., is rapidly developing. In addition to supermassive black holes, massive stellar clusters are observed in galactic nuclei, and their evolution is distinct from that of supermassive black holes. The evolutionary relations between supermassive black holes in galactic centers and spheroidal stellar components (bulges) of galaxies, as well as dark-matter galactic haloes are brought out. The launch into Earth's orbit of the space radio interferometer RadioAstron opened up the real possibility of finally proving that numerous discovered massive and highly compact objects with properties very similar to those of black holes make up real black holes in the sense of Albert Einstein's General Relativity. Similar proofs of the existence of black holes in the Universe can be obtained by intercontinental radio interferometry at short wavelengths λ≲1 mm (the international program, Event Horizon Telescope). (100

  4. 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.

  5. 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.

  6. 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.

  7. DOE HIGH-POWER SLIM-HOLE DRILLING SYSTEM

    Energy Technology Data Exchange (ETDEWEB)

    Dr. William C. Maurer; John H. Cohen; J. Chris Hetmaniak; Curtis Leitko

    1999-09-01

    This project used a systems approach to improve slim-hole drilling performance. A high power mud motor, having a double-length power section, and hybrid PDC/TSP drill bit were developed to deliver maximum horsepower to the rock while providing a long life down hole. This high-power slim-hole drilling system drills much faster than conventional slim-hole motor and bit combinations and holds significant potential to reduce slim-hole drilling costs. The oil and gas industries have been faced with downward price pressures since the 1980s. These pressures are not expected to be relieved in the near future. To maintain profitability, companies have had to find ways to reduce the costs of producing oil and gas. Drilling is one of the more costly operations in the production process. One method to reduce costs of drilling is to use smaller more mobile equipment. Slim holes have been drilled in the past using this principle. These wells can save money not only from the use of smaller drilling equipment, but also from reduced tubular costs. Stepping down even one casing size results in significant savings. However, slim holes have not found wide spread use for three reasons. First, until recently, the price of oil has been high so there were no forces to move the industry in this direction. Second, small roller bits and motors were not very reliable and they drilled slowly, removing much of the economic benefit. The third and final reason was the misconception that large holes were needed everywhere to deliver the desired production. Several factors have changed that will encourage the use of slim holes. The industry now favors any method of reducing the costs of producing oil and gas. In addition, the industry now understands that large holes are not always needed. Gas, in particular, can have high production rates in smaller holes. New materials now make it possible to manufacture improved bits and motors that drill for long periods at high rates. All that remains is to

  8. Rotation-invariant neural pattern recognition system with application to coin recognition.

    Science.gov (United States)

    Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

    1992-01-01

    In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

  9. Device-Free Indoor Activity Recognition System

    Directory of Open Access Journals (Sweden)

    Mohammed Abdulaziz Aide Al-qaness

    2016-11-01

    Full Text Available In this paper, we explore the properties of the Channel State Information (CSI of WiFi signals and present a device-free indoor activity recognition system. Our proposed system uses only one ubiquitous router access point and a laptop as a detection point, while the user is free and neither needs to wear sensors nor carry devices. The proposed system recognizes six daily activities, such as walk, crawl, fall, stand, sit, and lie. We have built the prototype with an effective feature extraction method and a fast classification algorithm. The proposed system has been evaluated in a real and complex environment in both line-of-sight (LOS and none-line-of-sight (NLOS scenarios, and the results validate the performance of the proposed system.

  10. Noncontaminating technique for making holes in existing process systems

    Science.gov (United States)

    Hecker, T. P.; Czapor, H. P.; Giordano, S. M.

    1972-01-01

    Technique is developed for making cleanly-contoured holes in assembled process systems without introducing chips or other contaminants into system. Technique uses portable equipment and does not require dismantling of system. Method was tested on Inconel, stainless steel, ASTMA-53, and Hastelloy X in all positions.

  11. 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.

  12. Edge detection techniques for iris recognition system

    International Nuclear Information System (INIS)

    Tania, U T; Motakabber, S M A; Ibrahimy, M I

    2013-01-01

    Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate

  13. 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.

  14. 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.

  15. Cross domains Arabic named entity recognition system

    KAUST Repository

    Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

    2016-01-01

    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.

  16. 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.

  17. Strong gravity effects in accreting black-hole systems

    International Nuclear Information System (INIS)

    Niedzwiecki, A.

    2006-01-01

    I briefly review current status of studying effects of strong gravity in X-ray astronomy. Matter accreting onto a black hole probes the relativistic region of space-time and the high-energy radiation it produces should contain signatures of strong gravity effects. Current X-ray observations provide the evidence that the observed emission originates, in some cases, at a distance of a few gravitational radii from a black hole. Moreover, certain observations invoke interpretations favouring rapid rotation of the black hole. Some observational properties of black hole systems are supposed to result from the lack of a material surface in these objects. I consider further effects, specific for the black hole environment, which can be studied in X-ray data. Bulk motion Comptonization, which would directly reveal converging flow of matter plunging into a black hole, is unlikely to be important in formation of X-ray spectra. Similarly, Penrose processes are unlikely to give observational effects, although this issue has not been thoroughly studied so far for all plausible radiative mechanisms. (author)

  18. Phase separation in fermionic systems with particle–hole asymmetry

    International Nuclear Information System (INIS)

    Montorsi, Arianna

    2008-01-01

    We determine the ground-state phase diagram of a Hubbard Hamiltonian with correlated hopping, which is asymmetric under particle–hole transform. By lowering the repulsive Coulomb interaction U at appropriate filling and interaction parameters, the ground state separates into hole and electron conducting phases: two different wavevectors characterize the system and charge–charge correlations become incommensurate. By further decreasing U another transition occurs at which the hole conducting region becomes insulating, and conventional phase separation takes place. Finally, for negative U the whole system eventually becomes a paired insulator. It is speculated that such behavior could be at the origin of the incommensurate superconducting phase recently discovered in the 1D Hirsch model. The exact phase boundaries are calculated in one dimension. (letter)

  19. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

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

    2016-01-01

    Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... 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...

  20. Taking the Pulse of a Black Hole System

    Science.gov (United States)

    2011-01-01

    Using two NASA X-ray satellites, astronomers have discovered what drives the "heartbeats" seen in the light from an unusual black hole system. These results give new insight into the ways that black holes can regulate their intake and severely curtail their growth. This study examined GRS 1915+105 (GRS 1915 for short), a binary system in the Milky Way galaxy containing a black hole about 14 times more massive than the Sun that is feeding off material from a companion star. As this material falls towards the black hole, it forms a swirling disk that emits X-rays. The black hole in GRS 1915 has been estimated to rotate at the maximum possible rate, allowing material in the inner disk to orbit very close to the black hole, at a radius only 20% larger than the event horizon, where the material travels at 50% the speed of light. Using the Chandra X-ray Observatory and the Rossi X-ray Timing Explorer (RXTE), researchers monitored this black hole system over a period of eight hours. As they watched, GRS 1915 gave off a short, bright pulse of X-ray light approximately every 50 seconds, varying in brightness by a factor of about three. This type of rhythmic cycle closely resembles an electrocardiogram of a human heart -- though at a slower pace. "Trying to understand the physics of this 'heartbeat state' is a little like trying to understand how a person's heart beats by watching changes in the blood flow through their veins," said Joey Neilsen, a graduate student at Harvard University, who presented these results from his dissertation at the American Astronomical Society (AAS) meeting in Seattle, Wash. It was previously known that GRS 1915 can develop such heartbeats when its mass consumption rate is very high. After monitoring it with the special combination of Chandra and RXTE, Neilsen and his collaborators realized that they could use the pulses to figure out what controls how much material the black hole consumes. "With each beat, the black hole pumps an enormous

  1. Probe-Hole Field Emission Microscope System Controlled by Computer

    Science.gov (United States)

    Gong, Yunming; Zeng, Haishan

    1991-09-01

    A probe-hole field emission microscope system, controlled by an Apple II computer, has been developed and operated successfully for measuring the work function of a single crystal plane. The work functions on the clean W(100) and W(111) planes are measured to be 4.67 eV and 4.45 eV, respectively.

  2. Canister positioning. Influence of fracture system on deposition hole stability

    International Nuclear Information System (INIS)

    Hoekmark, Harald

    2003-11-01

    The study concerns the mechanical behaviour of rock surrounding tunnels and deposition holes in a nuclear waste repository. The mechanical effects of tunnel excavation and deposition hole excavation are investigated by use of a tunnel scale numerical model representing a part of a KBS-3 type repository. The excavation geometry, the initial pre-mining state of stress, and the geometrical features of the fracture system are defined according to conditions that prevail in the TBM tunnel rock mass in Aespoe HRL. Comparisons are made between results obtained without consideration of fractures and results obtained with inclusion of the fracture system. The focus is on the region around the intersection of a tunnel and a deposition hole. A general conclusion is that a fracture system of the type found in the TBM rock mass does not have a decisive influence on the stability of the deposition holes. To estimate the expected extent of spalling, information about other conditions, e.g. the orientation of the initial stresses and the strength properties of the intact rock, is more important than detailed information about the fracture system

  3. Research on Face Recognition Based on Embedded System

    Directory of Open Access Journals (Sweden)

    Hong Zhao

    2013-01-01

    Full Text Available Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.

  4. Performance Assessment of Dynaspeak Speech Recognition System on Inflight Databases

    National Research Council Canada - National Science Library

    Barry, Timothy

    2004-01-01

    .... To aid in the assessment of various commercially available speech recognition systems, several aircraft speech databases have been developed at the Air Force Research Laboratory's Human Effectiveness Directorate...

  5. 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…

  6. Black holes and neutron stars: evolution of binary systems

    International Nuclear Information System (INIS)

    Kraft, R.P.

    1975-01-01

    Evidence for the existence of neutron stars and black holes in binary systems has been reviewed, and the following summarizes the current situation: (1) No statistically significant case has been made for the proposition that black holes and/or neutron stars contribute to the population of unseen companions of ordinary spectroscopic binaries; (2) Plausible evolutionary scenarios can be advanced that place compact X-ray sources into context as descendants of several common types of mass-exchange binaries. The collapse object may be a black hole, a neutron star, or a white dwarf, depending mostly on the mass of the original primary; (3) The rotating neutron star model for the pulsating X-ray sources Her X-1 and Cen X-3 is the simplest interpretation of these objects, but the idea that the pulsations result from the non-radial oscillations of a white dwarf cannot be altogether dismissed. The latter is particularly attractive in the case of Her X-1 because the total mass of the system is small; (4) The black hole picture for Cyg X-1 represents the simplest model that can presently be put forward to explain the observations. This does not insure its correctness, however. The picture depends on a long chain of inferences, some of which are by no means unassailable. (Auth.)

  7. 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.

  8. Automated recognition system for power quality disturbances

    Science.gov (United States)

    Abdelgalil, Tarek

    The application of deregulation policies in electric power systems has resulted in the necessity to quantify the quality of electric power. This fact highlights the need for a new monitoring strategy which is capable of tracking, detecting, classifying power quality disturbances, and then identifying the source of the disturbance. The objective of this work is to design an efficient and reliable power quality monitoring strategy that uses the advances in signal processing and pattern recognition to overcome the deficiencies that exist in power quality monitoring devices. The purposed monitoring strategy has two stages. The first stage is to detect, track, and classify any power quality violation by the use of on-line measurements. In the second stage, the source of the classified power quality disturbance must be identified. In the first stage, an adaptive linear combiner is used to detect power quality disturbances. Then, the Teager Energy Operator and Hilbert Transform are utilized for power quality event tracking. After the Fourier, Wavelet, and Walsh Transforms are employed for the feature extraction, two approaches are then exploited to classify the different power quality disturbances. The first approach depends on comparing the disturbance to be classified with a stored set of signatures for different power quality disturbances. The comparison is developed by using Hidden Markov Models and Dynamic Time Warping. The second approach depends on employing an inductive inference to generate the classification rules directly from the data. In the second stage of the new monitoring strategy, only the problem of identifying the location of the switched capacitor which initiates the transients is investigated. The Total Least Square-Estimation of Signal Parameters via Rotational Invariance Technique is adopted to estimate the amplitudes and frequencies of the various modes contained in the voltage signal measured at the facility entrance. After extracting the

  9. 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.

  10. Fingerprint recognition system by use of graph matching

    Science.gov (United States)

    Shen, Wei; Shen, Jun; Zheng, Huicheng

    2001-09-01

    Fingerprint recognition is an important subject in biometrics to identify or verify persons by physiological characteristics, and has found wide applications in different domains. In the present paper, we present a finger recognition system that combines singular points and structures. The principal steps of processing in our system are: preprocessing and ridge segmentation, singular point extraction and selection, graph representation, and finger recognition by graphs matching. Our fingerprint recognition system is implemented and tested for many fingerprint images and the experimental result are satisfactory. Different techniques are used in our system, such as fast calculation of orientation field, local fuzzy dynamical thresholding, algebraic analysis of connections and fingerprints representation and matching by graphs. Wed find that for fingerprint database that is not very large, the recognition rate is very high even without using a prior coarse category classification. This system works well for both one-to-few and one-to-many problems.

  11. 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.

  12. 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.

  13. Image quality assessment for video stream recognition systems

    Science.gov (United States)

    Chernov, Timofey S.; Razumnuy, Nikita P.; Kozharinov, Alexander S.; Nikolaev, Dmitry P.; Arlazarov, Vladimir V.

    2018-04-01

    Recognition and machine vision systems have long been widely used in many disciplines to automate various processes of life and industry. Input images of optical recognition systems can be subjected to a large number of different distortions, especially in uncontrolled or natural shooting conditions, which leads to unpredictable results of recognition systems, making it impossible to assess their reliability. For this reason, it is necessary to perform quality control of the input data of recognition systems, which is facilitated by modern progress in the field of image quality evaluation. In this paper, we investigate the approach to designing optical recognition systems with built-in input image quality estimation modules and feedback, for which the necessary definitions are introduced and a model for describing such systems is constructed. The efficiency of this approach is illustrated by the example of solving the problem of selecting the best frames for recognition in a video stream for a system with limited resources. Experimental results are presented for the system for identity documents recognition, showing a significant increase in the accuracy and speed of the system under simulated conditions of automatic camera focusing, leading to blurring of frames.

  14. 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.

  15. 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.

  16. 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.

  17. 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)

  18. 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

  19. Magnetometry of low-dimensional electron and hole systems

    Energy Technology Data Exchange (ETDEWEB)

    Usher, A [School of Physics, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Elliott, M [School of Physics and Astronomy, Cardiff University, Queens Buildings, Cardiff CF24 3AA (United Kingdom)], E-mail: a.usher@exeter.ac.uk, E-mail: elliottm@cf.ac.uk

    2009-03-11

    The high-magnetic-field, low-temperature magnetic properties of low-dimensional electron and hole systems reveal a wealth of fundamental information. Quantum oscillations of the thermodynamic equilibrium magnetization yield the total density of states, a central quantity in understanding the quantum Hall effect in 2D systems. The magnetization arising from non-equilibrium circulating currents reveals details, not accessible with traditional measurements, of the vanishingly small longitudinal resistance in the quantum Hall regime. We review how the technique of magnetometry has been applied to these systems, the most important discoveries that have been made, and their theoretical significance. (topical review)

  20. 8th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej

    2013-01-01

    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 86 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: Biometrics Data Stream Classification and Big Data Analytics  Features, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications Pattern recognition and image processing in robotics  Speech and word recognition 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.

  1. A Spoken English Recognition Expert System.

    Science.gov (United States)

    1983-09-01

    34Speech Recognition by Computer," Scientific American. New York: Scientific American, April 1981: 64-76. 16. Marcus, Mitchell P. A Theo of Syntactic...prob)...) Pcssible words for voice decoder to choose from are: gents dishes issues itches ewes folks foes comunications units eunichs error * farce

  2. Active Multimodal Sensor System for Target Recognition and Tracking.

    Science.gov (United States)

    Qu, Yufu; Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

    2017-06-28

    High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system.

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

    Indian Academy of Sciences (India)

    The issues faced by the handwritten character recognition systems are the similarity. ∗ ... tical/structural features have also been successfully used in character ..... The coordinates (xc, yc) of centroid are calculated by equations (4) and (5). xc =.

  4. Optimization Methods in Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    L. Povoda

    2016-09-01

    Full Text Available Emotions play big role in our everyday communication and contain important information. This work describes a novel method of automatic emotion recognition from textual data. The method is based on well-known data mining techniques, novel approach based on parallel run of SVM (Support Vector Machine classifiers, text preprocessing and 3 optimization methods: sequential elimination of attributes, parameter optimization based on token groups, and method of extending train data sets during practical testing and production release final tuning. We outperformed current state of the art methods and the results were validated on bigger data sets (3346 manually labelled samples which is less prone to overfitting when compared to related works. The accuracy achieved in this work is 86.89% for recognition of 5 emotional classes. The experiments were performed in the real world helpdesk environment, was processing Czech language but the proposed methodology is general and can be applied to many different languages.

  5. Automatic system for localization and recognition of vehicle plate numbers

    OpenAIRE

    Vázquez, N.; Nakano, M.; Pérez-Meana, H.

    2003-01-01

    This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

  6. 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 mus...

  7. Entropy of Iterated Function Systems and Their Relations with Black Holes and Bohr-Like Black Holes Entropies

    Directory of Open Access Journals (Sweden)

    Christian Corda

    2018-01-01

    Full Text Available In this paper we consider the metric entropies of the maps of an iterated function system deduced from a black hole which are known the Bekenstein–Hawking entropies and its subleading corrections. More precisely, we consider the recent model of a Bohr-like black hole that has been recently analysed in some papers in the literature, obtaining the intriguing result that the metric entropies of a black hole are created by the metric entropies of the functions, created by the black hole principal quantum numbers, i.e., by the black hole quantum levels. We present a new type of topological entropy for general iterated function systems based on a new kind of the inverse of covers. Then the notion of metric entropy for an Iterated Function System ( I F S is considered, and we prove that these definitions for topological entropy of IFS’s are equivalent. It is shown that this kind of topological entropy keeps some properties which are hold by the classic definition of topological entropy for a continuous map. We also consider average entropy as another type of topological entropy for an I F S which is based on the topological entropies of its elements and it is also an invariant object under topological conjugacy. The relation between Axiom A and the average entropy is investigated.

  8. Statistical physics of black holes as quantum-mechanical systems

    OpenAIRE

    Giddings, Steven B.

    2013-01-01

    Some basic features of black-hole statistical mechanics are investigated, assuming that black holes respect the principles of quantum mechanics. Care is needed in defining an entropy S_bh corresponding to the number of microstates of a black hole, given that the black hole interacts with its surroundings. An open question is then the relationship between this entropy and the Bekenstein-Hawking entropy S_BH. For a wide class of models with interactions needed to ensure unitary quantum evolutio...

  9. 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.

  10. The NA50 segmented target and vertex recognition system

    International Nuclear Information System (INIS)

    Bellaiche, F.; Cheynis, B.; Contardo, D.; Drapier, O.; Grossiord, J.Y.; Guichard, A.; Haroutunian, R.; Jacquin, M.; Ohlsson-Malek, F.; Pizzi, J.R.

    1997-01-01

    The NA50 segmented target and vertex recognition system is described. The segmented target consists of 7 sub-targets of 1-2 mm thickness. The vertex recognition system used to determine the sub-target where an interaction has occured is based upon quartz elements which produce Cerenkov light when traversed by charged particles from the interaction. The geometrical arrangement of the quartz elements has been optimized for vertex recognition in 208 Pb-Pb collisions at 158 GeV/nucleon. A simple algorithm provides a vertex recognition efficiency of better than 85% for dimuon trigger events collected with a 1 mm sub-target set-up. A method for recognizing interactions of projectile fragments (nuclei and/or groups of nucleons) is presented. The segmented target allows a large target thickness which together with a high beam intensity (∼10 7 ions/s) enables high statistics measurements. (orig.)

  11. 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.

  12. Black hole astrophysics

    International Nuclear Information System (INIS)

    Blandford, R.D.; Thorne, K.S.

    1979-01-01

    Following an introductory section, the subject is discussed under the headings: on the character of research in black hole astrophysics; isolated holes produced by collapse of normal stars; black holes in binary systems; black holes in globular clusters; black holes in quasars and active galactic nuclei; primordial black holes; concluding remarks on the present state of research in black hole astrophysics. (U.K.)

  13. Adamantane in Drug Delivery Systems and Surface Recognition

    OpenAIRE

    Adela Štimac; Marina Šekutor; Kata Mlinarić-Majerski; Leo Frkanec; Ruža Frkanec

    2017-01-01

    The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based struc...

  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. 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.

  16. 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.

  17. An artificial odor recognition system is developed for discriminating odors

    Directory of Open Access Journals (Sweden)

    Wisnu Jatmiko

    2002-12-01

    Full Text Available This artificial system consisted of 16 quartz resonator crystals as the sensor array, a frequency modulator and a frequency counter for each sensor that are connected directly to a microcomputer. We have already shown that the artificial odor recognition system with 4 sensors is high enough to discriminate simple odor correctly, however, when it was used to discriminate compound odors, the recognition capability of this system is dropped significantly to be about 40%. Results of experiments show that the developed artificial system with 16 sensors could discriminate compound aroma based on 6 gradient of alcohol concentrations with high recognition rate of 89.9% for non batch processing system, and 82.4% for batch processing of the classes of odors.

  18. Connected digit speech recognition system for Malayalam language

    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 ...

  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. 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,...

  1. 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.

  2. Hypercompact Stellar Systems Around Recoiling Supermassive Black Holes

    Science.gov (United States)

    Merritt, David; Schnittman, Jeremy D.; Komossa, S.

    2009-07-01

    A supermassive black hole ejected from the center of a galaxy by gravitational-wave recoil carries a retinue of bound stars—a "hypercompact stellar system" (HCSS). The numbers and properties of HCSSs contain information about the merger histories of galaxies, the late evolution of binary black holes, and the distribution of gravitational-wave kicks. We relate the structural properties (size, mass, density profile) of HCSSs to the properties of their host galaxies and to the size of the kick in two regimes: collisional (M BH lsim 107 M sun), i.e., short nuclear relaxation times, and collisionless (M BH gsim 107 M sun), i.e., long nuclear relaxation times. HCSSs are expected to be similar in size and luminosity to globular clusters, but in extreme cases (large galaxies, kicks just above escape velocity) their stellar mass can approach that of ultracompact dwarf galaxies. However, they differ from all other classes of compact stellar system in having very high internal velocities. We show that the kick velocity is encoded in the velocity dispersion of the bound stars. Given a large enough sample of HCSSs, the distribution of gravitational-wave kicks can therefore be empirically determined. We combine a hierarchical merger algorithm with stellar population models to compute the rate of production of HCSSs over time and the probability of observing HCSSs in the local universe as a function of their apparent magnitude, color, size, and velocity dispersion, under two different assumptions about the star formation history prior to the kick. We predict that ~102 HCSSs should be detectable within 2 Mpc of the center of the Virgo cluster, and that many of these should be bright enough that their kick velocities (i.e., velocity dispersions) could be measured with reasonable exposure times. We discuss other strategies for detecting HCSSs and speculate on some exotic manifestations.

  3. 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.

  4. Adamantane in Drug Delivery Systems and Surface Recognition.

    Science.gov (United States)

    Štimac, Adela; Šekutor, Marina; Mlinarić-Majerski, Kata; Frkanec, Leo; Frkanec, Ruža

    2017-02-16

    The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

  5. Adamantane in Drug Delivery Systems and Surface Recognition

    Directory of Open Access Journals (Sweden)

    Adela Štimac

    2017-02-01

    Full Text Available The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

  6. 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....

  7. 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.  .

  8. Black Holes

    OpenAIRE

    Townsend, P. K.

    1997-01-01

    This paper is concerned with several not-quantum aspects of black holes, with emphasis on theoretical and mathematical issues related to numerical modeling of black hole space-times. Part of the material has a review character, but some new results or proposals are also presented. We review the experimental evidence for existence of black holes. We propose a definition of black hole region for any theory governed by a symmetric hyperbolic system of equations. Our definition reproduces the usu...

  9. 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.

  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. 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.

  12. 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

  13. Design and implementation of face recognition system based on Windows

    Science.gov (United States)

    Zhang, Min; Liu, Ting; Li, Ailan

    2015-07-01

    In view of the basic Windows login password input way lacking of safety and convenient operation, we will introduce the biometrics technology, face recognition, into the computer to login system. Not only can it encrypt the computer system, also according to the level to identify administrators at all levels. With the enhancement of the system security, user input can neither be a cumbersome nor worry about being stolen password confidential.

  14. 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

  15. MITLL 2015 Language Recognition Evaluation System Description

    Science.gov (United States)

    2016-01-27

    912 8.18 qsl-rus Russian 2021 37.80 ara-ary Maghrebi 919 46.91 spa-car Carib. Spa. 194 30.59 ara-arz Egyptian 440 97.27 spa-eur Eur. Spa. 366 8.55...qsl-pol Polish 695 32.14 ara-arb MSA 912 8.18 qsl-rus Russian 2021 37.80 ara-ary Maghrebi 919 46.91 spa-car Carib. Spa. 194 30.59 ara-arz Egyptian ...BOTTLENECK I-VECTOR SYSTEM (BNF1) The Deep Neural Network architecture that we used for this system was composed of seven hidden layers. The sixth

  16. No firewalls or information problem for black holes entangled with large systems

    Science.gov (United States)

    Stoltenberg, Henry; Albrecht, Andreas

    2015-01-01

    We discuss how under certain conditions the black hole information puzzle and the (related) arguments that firewalls are a typical feature of black holes can break down. We first review the arguments of Almheiri, Marolf, Polchinski and Sully favoring firewalls, focusing on entanglements in a simple toy model for a black hole and the Hawking radiation. By introducing a large and inaccessible system entangled with the black hole (representing perhaps a de Sitter stretched horizon or inaccessible part of a landscape), we show complementarity can be restored and firewalls can be avoided throughout the black hole's evolution. Under these conditions black holes do not have an "information problem." We point out flaws in some of our earlier arguments that such entanglement might be generically present in some cosmological scenarios and call out certain ways our picture may still be realized.

  17. 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.

  18. Constraints in distortion-invariant target recognition system simulation

    Science.gov (United States)

    Iftekharuddin, Khan M.; Razzaque, Md A.

    2000-11-01

    Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

  19. Using a data fusion-based activity recognition framework to determine surveillance system requirements

    CSIR Research Space (South Africa)

    Le Roux, WH

    2007-07-01

    Full Text Available A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat...

  20. A Classification Framework for Large-Scale Face Recognition Systems

    OpenAIRE

    Zhou, Ziheng; Deravi, Farzin

    2009-01-01

    This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

  1. PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

    OpenAIRE

    ANEES ABU SNEINEH; WAEL A. SALAH

    2017-01-01

    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 sys...

  2. 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.

  3. 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

  4. 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.

  5. Dragging of inertial frames in the composed black-hole-ring system

    International Nuclear Information System (INIS)

    Hod, Shahar

    2015-01-01

    A well-established phenomenon in general relativity is the dragging of inertial frames by a spinning object. In particular, due to the dragging of inertial frames by a ring orbiting a central black hole, the angular velocity Ω H BH-ring of the black-hole horizon in the composed black-hole-ring system is no longer related to the black-hole angular momentum J H by the simple Kerr-like (vacuum) relation Ω H Kerr (J H ) = J H /2M 2 R H (here M and R H are the mass and horizon-radius of the black hole, respectively). Will has performed a perturbative treatment of the composed black-hole-ring system in the regime of slowly rotating black holes and found the explicit relation Ω H BH-ring (J H = 0, J R , R) = 2J R /R 3 for the angular velocity of a central black hole with zero angular momentum, where J R and R are respectively the angular momentum of the orbiting ring and its proper circumferential radius. Analyzing a sequence of black-hole-ring configurations with adiabatically varying (decreasing) circumferential radii, we show that the expression found by Will for Ω H BH-ring (J H = 0, J R , R) implies a smooth transition of the central black-hole angular velocity from its asymptotic near-horizon value Ω H BH-ring (J H = 0, J R , R → R H + ) → 2J R /R H 3 (that is, just before the assimilation of the ring by the central black hole), to its final Kerr (vacuum) value Ω H Kerr (J H new )= J H new /2M new2 R H new [that is, after the adiabatic assimilation of the ring by the central black hole. Here J H new = J R , M new , and R H new are the new parameters of the resulting Kerr (vacuum) black hole after it assimilated the orbiting ring]. We use this important observation in order to generalize the result of Will to the regime of black-hole-ring configurations in which the central black holes possess non-zero angular momenta. In particular, it is shown that the continuity argument (namely, the characteristic smooth evolution of the black-hole angular velocity

  6. Dragging of inertial frames in the composed black-hole-ring system

    Energy Technology Data Exchange (ETDEWEB)

    Hod, Shahar [The Ruppin Academic Center, Emeq Hefer (Israel); The Hadassah Institute, Jerusalem (Israel)

    2015-11-15

    A well-established phenomenon in general relativity is the dragging of inertial frames by a spinning object. In particular, due to the dragging of inertial frames by a ring orbiting a central black hole, the angular velocity Ω{sub H}{sup BH-ring} of the black-hole horizon in the composed black-hole-ring system is no longer related to the black-hole angular momentum J{sub H} by the simple Kerr-like (vacuum) relation Ω{sub H}{sup Kerr}(J{sub H}) = J{sub H}/2M{sup 2}R{sub H} (here M and R{sub H} are the mass and horizon-radius of the black hole, respectively). Will has performed a perturbative treatment of the composed black-hole-ring system in the regime of slowly rotating black holes and found the explicit relation Ω{sub H}{sup BH-ring}(J{sub H} = 0, J{sub R}, R) = 2J{sub R}/R{sup 3} for the angular velocity of a central black hole with zero angular momentum, where J{sub R} and R are respectively the angular momentum of the orbiting ring and its proper circumferential radius. Analyzing a sequence of black-hole-ring configurations with adiabatically varying (decreasing) circumferential radii, we show that the expression found by Will for Ω{sub H}{sup BH-ring}(J{sub H} = 0, J{sub R}, R) implies a smooth transition of the central black-hole angular velocity from its asymptotic near-horizon value Ω{sub H}{sup BH-ring}(J{sub H} = 0, J{sub R}, R → R{sub H}{sup +}) → 2J{sub R}/R{sub H}{sup 3} (that is, just before the assimilation of the ring by the central black hole), to its final Kerr (vacuum) value Ω{sub H}{sup Kerr}(J{sub H}{sup new})= J{sub H}{sup new}/2M{sup new2}R{sub H}{sup new} [that is, after the adiabatic assimilation of the ring by the central black hole. Here J{sub H}{sup new} = J{sub R}, M{sup new}, and R{sub H}{sup new} are the new parameters of the resulting Kerr (vacuum) black hole after it assimilated the orbiting ring]. We use this important observation in order to generalize the result of Will to the regime of black-hole-ring configurations

  7. 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.

  8. An Edge-Based Macao License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Chi-Man Pun

    2011-04-01

    Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

  9. Merger transitions in brane-black-hole systems: Criticality, scaling, and self-similarity

    International Nuclear Information System (INIS)

    Frolov, Valeri P.

    2006-01-01

    We propose a toy model for studying merger transitions in a curved spacetime with an arbitrary number of dimensions. This model includes a bulk N-dimensional static spherically symmetric black hole and a test D-dimensional brane (D≤N-1) interacting with the black hole. The brane is asymptotically flat and allows a O(D-1) group of symmetry. Such a brane-black-hole (BBH) system has two different phases. The first one is formed by solutions describing a brane crossing the horizon of the bulk black hole. In this case the internal induced geometry of the brane describes a D-dimensional black hole. The other phase consists of solutions for branes which do not intersect the horizon, and the induced geometry does not have a horizon. We study a critical solution at the threshold of the brane-black-hole formation, and the solutions which are close to it. In particular, we demonstrate that there exists a striking similarity of the merger transition, during which the phase of the BBH system is changed, both with the Choptuik critical collapse and with the merger transitions in the higher dimensional caged black-hole-black-string system

  10. 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)

  11. 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.

    1976-01-01

    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

  12. 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

  13. Straddle packer system design and operation for vertical characterization of open bore holes

    International Nuclear Information System (INIS)

    Olsen, J.K.

    1994-01-01

    Bore holes open to large intervals provide groundwater samples and test results which represent an unknown integration of properties throughout the depth of the hole. The State of Idaho's INEL Oversight Program is utilizing a custom straddle-packer system to develop a vertical characterization of water chemistry and hydrology in selected open bore holes at the Idaho National Engineering Laboratory. This report describes the design and operation for bore hole zone isolation, water sampling, and hydrologic testing. To reduce potential influences on in situ water chemistry, the system utilizes chemically inert components to the extent possible. Straddle packer systems are effective in producing representative water samples from isolated formations. Hydrologic testing is limited by the ability to produce a measurable stress on the aquifer in individual formations, and head measurement sensitivity. 4 figs

  14. Simulation of hole mobility in two-dimensional systems

    International Nuclear Information System (INIS)

    Donetti, Luca; Gamiz, Francisco; Rodriguez, Noel

    2009-01-01

    We develop a fully self-consistent solver for the six-band k . p Schrödinger and Poisson equations to compute the valence-band structure of Si and Ge devices with arbitrary substrate orientation and uniaxial or biaxial strain. This allows us to compute the potential, charge distribution and subband energy dispersion relation for hole inversion layers in different devices and, using a simplex Monte Carlo simulator, to evaluate the low-field mobility. New procedures have been developed to calculate the scattering rates. The results obtained in the case of a (0 0 1) Si MOSFET device are compared with experimental mobility curves and a very good agreement is found. Then, hole mobility curves for different structures and crystallographic orientations both with strained and unstrained materials are evaluated

  15. The implementation of the integrated design process in the hole-plan system

    Directory of Open Access Journals (Sweden)

    Won-Sun Ruy

    2012-12-01

    Full Text Available All current shipyards are using the customized CAD/CAM programs in order to improve the design quality and increase the design efficiency. Even though the data structures for ship design and construction are almost completed, the implementation related to the ship design processes are still in progress so that it has been the main causes of the bottleneck and delay during the middle of design process. In this study, we thought that the hole-plan system would be a good example which is remained to be improved. The people of outfitting division who don't have direct authority to edit the structural panels, should request the hull design division to install the holes for the outfitting equipment. For acceptance, they should calculate the hole position, determine the hole type, and find the intersected contour of panel. After consideration of the hull people, the requested holes are manually installed on the hull structure. As the above, many processes are needed such as communication and discussion between the divisions, drawings for hole-plan, and the consideration for the structural or production compatibility. However this iterative process takes a lot of working time and requires mental pressure to the related people and cross-division conflict. This paper will handle the hole-plan system in detail to automate the series of process and minimize the human efforts and time-consumption.

  16. 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

  17. 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.

  18. A close-pair binary in a distant triple supermassive black hole system.

    Science.gov (United States)

    Deane, R P; Paragi, Z; Jarvis, M J; Coriat, M; Bernardi, G; Fender, R P; Frey, S; Heywood, I; Klöckner, H-R; Grainge, K; Rumsey, C

    2014-07-03

    Galaxies are believed to evolve through merging, which should lead to some hosting multiple supermassive black holes. There are four known triple black hole systems, with the closest black hole pair being 2.4 kiloparsecs apart (the third component in this system is at 3 kiloparsecs), which is far from the gravitational sphere of influence (about 100 parsecs for a black hole with mass one billion times that of the Sun). Previous searches for compact black hole systems concluded that they were rare, with the tightest binary system having a separation of 7 parsecs (ref. 10). Here we report observations of a triple black hole system at redshift z = 0.39, with the closest pair separated by about 140 parsecs and significantly more distant from Earth than any other known binary of comparable orbital separation. The effect of the tight pair is to introduce a rotationally symmetric helical modulation on the structure of the large-scale radio jets, which provides a useful way to search for other tight pairs without needing extremely high resolution observations. As we found this tight pair after searching only six galaxies, we conclude that tight pairs are more common than hitherto believed, which is an important observational constraint for low-frequency gravitational wave experiments.

  19. 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.

  20. 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.

  1. Increasing the information acquisition volume in iris recognition systems.

    Science.gov (United States)

    Barwick, D Shane

    2008-09-10

    A significant hurdle for the widespread adoption of iris recognition in security applications is that the typically small imaging volume for eye placement results in systems that are not user friendly. Separable cubic phase plates at the lens pupil have been shown to ameliorate this disadvantage by increasing the depth of field. However, these phase masks have limitations on how efficiently they can capture the information-bearing spatial frequencies in iris images. The performance gains in information acquisition that can be achieved by more general, nonseparable phase masks is demonstrated. A detailed design method is presented, and simulations using representative designs allow for performance comparisons.

  2. 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.

  3. 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.

  4. Static spin-3/2 perturbations of two-black hole system

    International Nuclear Information System (INIS)

    Embacher, F.; Aichelburg, P.C.

    1984-01-01

    We construct the most general static regular, non-gauge spin-3/2 perturbations on the Majumdar-Papapetrou background for two black holes. The construction applies a limiting procedure by combining Killing spinors and spacetime perturbations. The supercharge associated with the spin-3/2 field is proportional to the difference of the mass parameters, implying that a system of two equal black holes has zero supercharge. (Author)

  5. Geology of hole drill thermal infra basaltic (Guarani Aquifer System) in Salto Uruguay

    International Nuclear Information System (INIS)

    Goso, C.; Muzio, R.; Marmisolle, J.; De Souza, S.

    2004-01-01

    This paper deals with the lithological description of a thermal infrabasaltic (Guarani Aquifer System) hole drill cutting in Dayman (Kanarek Hotel), Salto department (Uruguay). This hole drill shows 152 meters of Buena Vista Formation (Upper Permian- Lower Triassic), 188 meters of Tacuarembo Formation (Upper Jurassic-Lower Cretaceous) and 940meters of Arapey Formation (Lower Cretaceous). Petrographical studies of six basaltic levels were done [es

  6. Finite difference schemes for second order systems describing black holes

    International Nuclear Information System (INIS)

    Motamed, Mohammad; Kreiss, H-O.; Babiuc, M.; Winicour, J.; Szilagyi, B.

    2006-01-01

    In the harmonic description of general relativity, the principal part of Einstein's equations reduces to 10 curved space wave equations for the components of the space-time metric. We present theorems regarding the stability of several evolution-boundary algorithms for such equations when treated in second order differential form. The theorems apply to a model black hole space-time consisting of a spacelike inner boundary excising the singularity, a timelike outer boundary and a horizon in between. These algorithms are implemented as stable, convergent numerical codes and their performance is compared in a 2-dimensional excision problem

  7. Hawking radiation from astrophysical black holes to analogous systems in lab

    CERN Document Server

    Belgiorno, Francesco D

    2018-01-01

    The aim of this book is to provide the reader with a guide to Hawking radiation through a dual approach to the problem. In the first part of the book, we summarize some basic knowledge about black holes and quantum field theory in curved spacetime. In the second part, we present a survey of methods for deriving and studying Hawking radiation from astrophysical black holes, from the original calculation by S W Hawking to the most recent contributions involving gravitational anomalies and tunneling. In the third part, we introduce analogue gravity models, with particular attention to dielectric black hole systems, to which the studies of the present authors are devoted. The mutual interchange of knowledge between the aforementioned parts is addressed to render a more comprehensive picture of this very fascinating quantum phenomenon associated with black holes.

  8. Real-time image restoration for iris recognition systems.

    Science.gov (United States)

    Kang, Byung Jun; Park, Kang Ryoung

    2007-12-01

    In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.

  9. New neural-networks-based 3D object recognition system

    Science.gov (United States)

    Abolmaesumi, Purang; Jahed, M.

    1997-09-01

    Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

  10. 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.

  11. 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...

  12. Point spread function engineering for iris recognition system design.

    Science.gov (United States)

    Ashok, Amit; Neifeld, Mark A

    2010-04-01

    Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

  13. 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

  14. 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.

  15. Expert methods in control systems of deep oil and gas holes building

    Energy Technology Data Exchange (ETDEWEB)

    Sementsov, G.; Fadeeva, I.; Chigur, I. [State Technical Univ. of Oil and Gas, Ivano-Frankivsk (Ukraine)

    2000-07-01

    Attempts to provide self-control of process of long holing on oil and gas have not given due effect owing to complication of object, it fuzzy and equivocation of the information. In this connection it is offered to use for management of drilling expert systems, which one use fuzzy models and methods of the theory of fuzzy control systems. (orig.)

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Container-code recognition system based on computer vision and deep neural networks

    Science.gov (United States)

    Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

    2018-04-01

    Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

  1. INTEGRATED DRILLING SYSTEM USING MUD ACTUATED DOWN HOLE HAMMER AS PRIMARY ENGINE

    Energy Technology Data Exchange (ETDEWEB)

    John V. Fernandez; David S. Pixton

    2005-12-01

    A history and project summary of the development of an integrated drilling system using a mud-actuated down-hole hammer as its primary engine are given. The summary includes laboratory test results, including atmospheric tests of component parts and simulated borehole tests of the hammer system. Several remaining technical hurdles are enumerated. A brief explanation of commercialization potential is included. The primary conclusion for this work is that a mud actuated hammer can yield substantial improvements to drilling rate in overbalanced, hard rock formations. A secondary conclusion is that the down-hole mud actuated hammer can serve to provide other useful down-hole functions including generation of high pressure mud jets, generation of seismic and sonic signals, and generation of diagnostic information based on hammer velocity profiles.

  2. 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.

  3. 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).

  4. 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...

  5. Intelligent color recognition system using micro-controller

    International Nuclear Information System (INIS)

    Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

    2006-01-01

    Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

  6. 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

  7. Two-dimensional hole systems in indium-based quantum well heterostructures

    Energy Technology Data Exchange (ETDEWEB)

    Loher, Josef

    2016-08-01

    The complex spin-orbit interaction (SOI) of two-dimensional hole gas (2DHG) systems - the relativistic coupling of the hole spin degree of freedom to their movement in an electric field - is of fundamental interest in spin physics due to its key role for spin manipulation in spintronic devices. In this work, we were able to evaluate the tunability of Rashba-SOI-related parameters in the 2DHG system of InAlAs/InGaAs/InAs:Mn quantum well heterostructures experimentally by analyzing the hole density evolution of quantum interference effects at low magnetic fields. We achieved to cover a significant range of hole densities by the joint action of the variation of the manganese modulation doping concentration during molecular beam epitaxy and external field-effect-mediated manipulation of the 2D carrier density in Hall bar devices by a metallic topgate. Within these magnetotransport experiments, a reproducible phenomenon of remarkable robustness emerged in the transverse Hall magnetoresistivity of the indium 2DHG systems which are grown on a special InAlAs step-graded metamorphic buffer layer structure to compensate crystal lattice mismatch. As a consequence of the strain relaxation process, these material systems are characterized by anisotropic properties along different crystallographic directions. We identify a puzzling offset phenomenon in the zero-field Hall magnetoresistance and demonstrate it to be a universal effect in systems with spatially anisotropic transport properties.

  8. Social context predicts recognition systems in ant queens

    DEFF Research Database (Denmark)

    Dreier, Stéphanie Agnès Jeanine; d'Ettorre, Patrizia

    2009-01-01

    Recognition of group-members is a key feature of sociality. Ants use chemical communication to discriminate nestmates from intruders, enhancing kin cooperation and preventing parasitism. The recognition code is embedded in their cuticular chemical profile, which typically varies between colonies....... We predicted that ants might be capable of accurate recognition in unusual situations when few individuals interact repeatedly, as new colonies started by two to three queens. Individual recognition would be favoured by selection when queens establish dominance hierarchies, because repeated fights...... 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...

  9. 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.

  10. A Universal Scaling for the Energetics of Relativistic Jets From Black Hole Systems

    Science.gov (United States)

    Nemmen, R. S.; Georganopoulos, M.; Guiriec, S.; Meyer, E. T.; Gehrels, N.; Sambruna, R. M.

    2013-01-01

    Black holes generate collimated, relativistic jets which have been observed in gamma-ray bursts (GRBs), microquasars, and at the center of some galaxies (active galactic nuclei; AGN). How jet physics scales from stellar black holes in GRBs to the supermassive ones in AGNs is still unknown. Here we show that jets produced by AGNs and GRBs exhibit the same correlation between the kinetic power carried by accelerated particles and the gamma-ray luminosity, with AGNs and GRBs lying at the low and high-luminosity ends, respectively, of the correlation. This result implies that the efficiency of energy dissipation in jets produced in black hole systems is similar over 10 orders of magnitude in jet power, establishing a physical analogy between AGN and GRBs.

  11. 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.

  12. Application of spectral hole burning to the study of in vitro cellular systems

    Energy Technology Data Exchange (ETDEWEB)

    Milanovich, Nebojsa [Iowa State Univ., Ames, IA (United States)

    1999-11-08

    Chapter 1 of this thesis describes the various stages of tumor development and a multitude of diagnostic techniques used to detect cancer. Chapter 2 gives an overview of the aspects of hole burning spectroscopy important for its application to the study of cellular systems. Chapter 3 gives general descriptions of cellular organelles, structures, and physical properties that can serve as possible markers for the differentiation of normal and cancerous cells. Also described in Chapter 3 are the principles of cryobiology important for low temperature spectroscopy of cells, characterization of MCF-10F (normal) and MCF-7 (cancer) cells lines which will serve as model systems, and cellular characteristics of aluminum phthalocyanine tetrasulfonate (APT), which was used as the test probe. Chapters 4 and 5 are previously published papers by the author pertaining to the results obtained from the application of hole burning to the study of cellular systems. Chapter 4 presents the first results obtained by spectral hole burning of cellular systems and Chapter 5 gives results for the differentiation of MCF-10F and MCF-7 cells stained with APT by an external applied electric (Stark) field. A general conclusion is presented in Chapter 6. Appendices A and B provide additional characterization of the cell/probe model systems. Appendix A describes the uptake and subcellular distribution of APT in MCF-10F and MCF-7 cells and Appendix B compares the hole burning characteristics of APT in cells when the cells are in suspension and when they are examined while adhering to a glass coverslip. Appendix C presents preliminary results for a novel probe molecule, referred to as a molecular thumbtack, designed by the authors for use in future hole burning applications to cellular systems.

  13. Implications of access hole size on tank waste retrieval system design and cost

    International Nuclear Information System (INIS)

    Babcock, S.M.; Kwon, D.S.; Burks, B.L.; Stoughton, R.S.; Evans, M.S.

    1994-05-01

    The DOE Environmental Restoration and Waste Management Robotics Technology Development Program has been investigating the application of robotics technology to the retrieval of waste from single-shell storage tanks for several years. The use of a large, ''long-reach'' manipulator to position and orient a variety of tools and other equipment has been recommended. The objective of this study is to determine the appropriate access hole size for the tank waste retrieval system installation. Previous reports on the impact of access hole size on manipulator performance are summarized. In addition, the practical limitation for access hole size based on structural limitations of the waste storage tanks, the state-of-the-art size limitations for the installation of new risers, the radiation safety implications of various access hole sizes, and overall system cost implications are considered. Basic conclusions include: (1) overall cost of remediation will; be dominated by the costs of the balance of plant and time required to perform the task rather than the cost of manipulator hardware or the cost of installing a riser, (2) the most desirable solution from a manipulator controls point of view is to make the manipulator as stiff as possible and have as high as possible a natural frequency, which implies a large access hole diameter, (3) beyond some diameter; simple, uniform cross-section elements become less advantageous from a weight standpoint and alternative structures should be considered, and (4) additional shielding and contamination control measures would be required for larger holes. Parametric studies summarized in this report considered 3,790,000 1 (1,000,000 gal) tanks, while initial applications are likely to be for 2,840,000 1 (750,000 gal) tanks. Therefore, the calculations should be somewhat conservative, recognizing the limitations of the specific conditions considered

  14. 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.

  15. 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

  16. Lidov–Kozai Cycles with Gravitational Radiation: Merging Black Holes in Isolated Triple Systems

    Energy Technology Data Exchange (ETDEWEB)

    Silsbee, Kedron [Department of Astrophysical Sciences, Princeton University, Ivy Lane, Princeton, NJ 08544 (United States); Tremaine, Scott, E-mail: ksilsbee@astro.princeton.edu, E-mail: tremaine@ias.edu [Institute for Advanced Study, 1 Einstein Drive Princeton, NJ 08540 (United States)

    2017-02-10

    We show that a black-hole binary with an external companion can undergo Lidov–Kozai cycles that cause a close pericenter passage, leading to a rapid merger due to gravitational-wave emission. This scenario occurs most often for systems in which the companion has a mass comparable to the reduced mass of the binary and the companion orbit has a semimajor axis within a factor of ∼10 of the binary semimajor axis. Using a simple population-synthesis model and three-body simulations, we estimate the rate of mergers in triple black-hole systems in the field to be about six per Gpc{sup 3} per year in the absence of natal kicks during black-hole formation. This value is within the low end of the 90% credible interval for the total black hole–black hole merger rate inferred from the current LIGO results. There are many uncertainties in these calculations, the largest of which is the unknown distribution of natal kicks. Even modest natal kicks of 40 km s{sup −1} will reduce the merger rate by a factor of 40. A few percent of these systems will have eccentricity greater than 0.999 when they first enter the frequency band detectable by aLIGO (above 10 Hz).

  17. Lidov–Kozai Cycles with Gravitational Radiation: Merging Black Holes in Isolated Triple Systems

    International Nuclear Information System (INIS)

    Silsbee, Kedron; Tremaine, Scott

    2017-01-01

    We show that a black-hole binary with an external companion can undergo Lidov–Kozai cycles that cause a close pericenter passage, leading to a rapid merger due to gravitational-wave emission. This scenario occurs most often for systems in which the companion has a mass comparable to the reduced mass of the binary and the companion orbit has a semimajor axis within a factor of ∼10 of the binary semimajor axis. Using a simple population-synthesis model and three-body simulations, we estimate the rate of mergers in triple black-hole systems in the field to be about six per Gpc 3 per year in the absence of natal kicks during black-hole formation. This value is within the low end of the 90% credible interval for the total black hole–black hole merger rate inferred from the current LIGO results. There are many uncertainties in these calculations, the largest of which is the unknown distribution of natal kicks. Even modest natal kicks of 40 km s −1 will reduce the merger rate by a factor of 40. A few percent of these systems will have eccentricity greater than 0.999 when they first enter the frequency band detectable by aLIGO (above 10 Hz).

  18. Evaluation of Hole Quality in Hardened Steel with High-Speed Drilling Using Different Cooling Systems

    Directory of Open Access Journals (Sweden)

    Lincoln Cardoso Brandão

    2011-01-01

    Full Text Available This work evaluates the hole quality on AISI H13 hardened steel using high-speed drilling. Specimens were machined with new and worn out drills with 8.6 mm diameter and (TiAlN coating. Two levels of cutting speed and three levels of cooling/lubrication systems (flooded, minimum lubrication quantity, and dry were used. The hole quality is evaluated on surface roughness (Ra parameter, diameter error, circularity, and cylindricity error. A statistical analysis of the results shows that the cooling/lubrication system significantly affects the hole quality for all measured variables. This analysis indicates that dry machining produces the worst results. Higher cutting speeds not only prove beneficial to diameter error and circularity errors, but also show no significant difference on surface roughness and cylindricity errors. The effects of the interaction between the cooling/lubrication systems, tool wear, and cutting speed indicate that only cylindricity error is influenced. Thus, the conclusion is that the best hole quality is produced with a higher cutting speed using flooded or minimum lubrication quantity independent of drill wear.

  19. 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.

  20. 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

  1. Search for black holes

    International Nuclear Information System (INIS)

    Cherepashchuk, Anatolii M

    2003-01-01

    Methods and results of searching for stellar mass black holes in binary systems and for supermassive black holes in galactic nuclei of different types are described. As of now (June 2002), a total of 100 black hole candidates are known. All the necessary conditions Einstein's General Relativity imposes on the observational properties of black holes are satisfied for candidate objects available, thus further assuring the existence of black holes in the Universe. Prospects for obtaining sufficient criteria for reliably distinguishing candidate black holes from real black holes are discussed. (reviews of topical problems)

  2. Measuring the spin of black holes in binary systems using gravitational waves.

    Science.gov (United States)

    Vitale, Salvatore; Lynch, Ryan; Veitch, John; Raymond, Vivien; Sturani, Riccardo

    2014-06-27

    Compact binary coalescences are the most promising sources of gravitational waves (GWs) for ground-based detectors. Binary systems containing one or two spinning black holes are particularly interesting due to spin-orbit (and eventual spin-spin) interactions and the opportunity of measuring spins directly through GW observations. In this Letter, we analyze simulated signals emitted by spinning binaries with several values of masses, spins, orientations, and signal-to-noise ratios, as detected by an advanced LIGO-Virgo network. We find that for moderate or high signal-to-noise ratio the spin magnitudes can be estimated with errors of a few percent (5%-30%) for neutron star-black hole (black hole-black hole) systems. Spins' tilt angle can be estimated with errors of 0.04 rad in the best cases, but typical values will be above 0.1 rad. Errors will be larger for signals barely above the threshold for detection. The difference in the azimuth angles of the spins, which may be used to check if spins are locked into resonant configurations, cannot be constrained. We observe that the best performances are obtained when the line of sight is perpendicular to the system's total angular momentum and that a sudden change of behavior occurs when a system is observed from angles such that the plane of the orbit can be seen both from above and below during the time the signal is in band. This study suggests that direct measurement of black hole spin by means of GWs can be as precise as what can be obtained from x-ray binaries.

  3. Multi-Stage System for Automatic Target Recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

    2010-01-01

    A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an

  4. 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.

  5. Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

    Science.gov (United States)

    Muto, Yutaka; Yokoyama, Shigeyuki

    2012-01-01

    'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.

  6. Geothermal pump down-hole energy regeneration system

    Science.gov (United States)

    Matthews, Hugh B.

    1982-01-01

    Geothermal deep well energy extraction apparatus is provided of the general kind in which solute-bearing hot water is pumped to the earth's surface from a subterranean location by utilizing thermal energy extracted from the hot water for operating a turbine motor for driving an electrical power generator at the earth 3 s surface, the solute bearing water being returned into the earth by a reinjection well. Efficiency of operation of the total system is increased by an arrangement of coaxial conduits for greatly reducing the flow of heat from the rising brine into the rising exhaust of the down-well turbine motor.

  7. 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.

  8. AUTOMATIC SPEECH RECOGNITION SYSTEM CONCERNING THE MOROCCAN DIALECTE (Darija and Tamazight)

    OpenAIRE

    A. EL GHAZI; C. DAOUI; N. IDRISSI

    2012-01-01

    In this work we present an automatic speech recognition system for Moroccan dialect mainly: Darija (Arab dialect) and Tamazight. Many approaches have been used to model the Arabic and Tamazightphonetic units. In this paper, we propose to use the hidden Markov model (HMM) for modeling these phoneticunits. Experimental results show that the proposed approach further improves the recognition.

  9. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Recognition of State...

  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. Enhance Criminal Investigation by Proposed Fingerprint Recognition System

    International Nuclear Information System (INIS)

    Hashem, S.H.; Maolod, A.T.; Mohammad, A.A.

    2014-01-01

    Law enforcement officers and forensic specialists spend hours thinking about how fingerprints solve crimes, and trying to find, collect, record and compare these unique identifiers that can connect a specific person to a specific crime. These individuals understand that a basic human feature that most people take for granted, can be one of the most effective tools in crime solving.This research exploits our previous work to be applicable in criminal investigation field. The present study aims to solve the advance crime by strength fingerprint’s criminal investigation to control the alterations happen intentionally to criminals’ fingerprint. That done by suggest strategy introduce an optimal fingerprint image feature’s vector to the person and then considers it to be stored in database for future matching. Selecting optimal fingerprint feature’s vector strategy deal with considering 10 fingerprints for each criminal person (take the fingerprint in different time and different circumstance of criminal such as finger is dirty, wet, trembling, etc.). Proposal begun with apply a proposed enrollment on all 10 fingerprint for each criminal, the enrollment include the following consequence steps; begin with preprocessing step for each of 10 images including enhancement, then two level of feature extraction (first level to extract arches, whorls, and loops, where second level extract minutiae), after that applying proposed Genetic Algorithm to select optimal fingerprint, master fingerprint, which in our point of view present the most universal image which include more detailed features to recognition. Master fingerprint will be feature’s vector which stored in database. Then apply the proposed matching by testing fingerprints with these stored in database.While, measuring of criminal fingerprint investigation performance by calculating False Reject Rate (FRR)and False Accept Rate (FAR) for the traditional system and the proposed in criminal detection field. The

  12. Analysis and 3D inspection system of drill holes in aeronautical surfaces

    Science.gov (United States)

    Rubio, R.; Granero, L.; Sanz, M.; García, J.; Micó, V.

    2017-06-01

    In aerospace industry, the structure of the aircraft is assembled using small parts or a combination of them that are made with different materials, such as for instance aluminium, titanium, composites or even 3D printed parts. The union between these small parts is a critical point for the integrity of the aircraft. The quality of this union will decide the fatigue of adjacent components and therefore the useful life of them. For the union process the most extended method is the rivets, mainly because their low cost and easy manufacturing. For this purpose it is necessary to made drill holes in the aeronautical surface to insert the rivets. In this contribution, we present the preliminary results of a 3D inspection system [1] for drill holes analysis in aeronautical surfaces. The system, based in optical triangulation, was developed by the Group of Optoelectronic Image Processing from the University of Valencia in the framework of the Airbus Defence and Space (AD&S), MINERVA project (Manufacturing industrial - means emerging from validated automation). The capabilities of the system permits to generate a point cloud with 3D information and GD&T (geometrical dimensions and tolerances) characteristics of the drill hole. For the inner surface defects detection, the system can generate an inner image of the drill hole with a scaled axis to obtain the defect position. In addition, we present the analysis performed for the drills in the wing station of the A-400 M. In this analysis the system was tested for diameters in the range of [10 - 15.96] mm, and for Carbon Fibre.

  13. A massive binary black-hole system in OJ 287 and a test of general relativity.

    Science.gov (United States)

    Valtonen, M J; Lehto, H J; Nilsson, K; Heidt, J; Takalo, L O; Sillanpää, A; Villforth, C; Kidger, M; Poyner, G; Pursimo, T; Zola, S; Wu, J-H; Zhou, X; Sadakane, K; Drozdz, M; Koziel, D; Marchev, D; Ogloza, W; Porowski, C; Siwak, M; Stachowski, G; Winiarski, M; Hentunen, V-P; Nissinen, M; Liakos, A; Dogru, S

    2008-04-17

    Tests of Einstein's general theory of relativity have mostly been carried out in weak gravitational fields where the space-time curvature effects are first-order deviations from Newton's theory. Binary pulsars provide a means of probing the strong gravitational field around a neutron star, but strong-field effects may be best tested in systems containing black holes. Here we report such a test in a close binary system of two candidate black holes in the quasar OJ 287. This quasar shows quasi-periodic optical outbursts at 12-year intervals, with two outburst peaks per interval. The latest outburst occurred in September 2007, within a day of the time predicted by the binary black-hole model and general relativity. The observations confirm the binary nature of the system and also provide evidence for the loss of orbital energy in agreement (within 10 per cent) with the emission of gravitational waves from the system. In the absence of gravitational wave emission the outburst would have happened 20 days later.

  14. Non-Existence of Black Hole Solutionsfor a Spherically Symmetric, Static Einstein-Dirac-Maxwell System

    Science.gov (United States)

    Finster, Felix; Smoller, Joel; Yau, Shing-Tung

    We consider for j=1/2, 3/2,... a spherically symmetric, static system of (2j+1) Dirac particles, each having total angular momentum j. The Dirac particles interact via a classical gravitational and electromagnetic field. The Einstein-Dirac-Maxwell equations for this system are derived. It is shown that, under weak regularity conditions on the form of the horizon, the only black hole solutions of the EDM equations are the Reissner-Nordstrom solutions. In other words, the spinors must vanish identically. Applied to the gravitational collapse of a "cloud" of spin-1/2-particles to a black hole, our result indicates that the Dirac particles must eventually disappear inside the event horizon.

  15. Gravitational Waveforms in the Early Inspiral of Binary Black Hole Systems

    Science.gov (United States)

    Barkett, Kevin; Kumar, Prayush; Bhagwat, Swetha; Brown, Duncan; Scheel, Mark; Szilagyi, Bela; Simulating eXtreme Spacetimes Collaboration

    2015-04-01

    The inspiral, merger and ringdown of compact object binaries are important targets for gravitational wave detection by aLIGO. Detection and parameter estimation will require long, accurate waveforms for comparison. There are a number of analytical models for generating gravitational waveforms for these systems, but the only way to ensure their consistency and correctness is by comparing with numerical relativity simulations that cover many inspiral orbits. We've simulated a number of binary black hole systems with mass ratio 7 and a moderate, aligned spin on the larger black hole. We have attached these numerical waveforms to analytical waveform models to generate long hybrid gravitational waveforms that span the entire aLIGO frequency band. We analyze the robustness of these hybrid waveforms and measure the faithfulness of different hybrids with each other to obtain an estimate on how long future numerical simulations need to be in order to ensure that waveforms are accurate enough for use by aLIGO.

  16. 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. .

  17. System of small mammals holes as related to variation of expositional dose in forest litters

    International Nuclear Information System (INIS)

    Bykov, A.V.

    1991-01-01

    It is shown that small mammals play a sufficient role in radionuclide migration in natural biogeocenosis and agrocenosis. The system of underground communications of small mammals increases the rate of radionuclide migration deep in soil and promotes their accumulated around holes. Such migration is characterized by directivity-vertically down. The revealed regularities demostrate biogeocenotic role of voles in processes of directed migration of substances, contaminating soil surface

  18. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Junyi, E-mail: junyi-xia@uiowa.edu; Mart, Christopher [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 (United States); Bayouth, John [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 and Department of Human Oncology, University of Wisconsin - Madison, 600 Highland Avenue, K4/B55, Madison, Wisconsin 53792-0600 (United States)

    2014-01-15

    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

  20. 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 ...

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

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-01-01

    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. PMID:29695113

  2. 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.

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

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-04-24

    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.

  4. 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.

  5. Stability of Sarma phases in density imbalanced electron-hole bilayer systems

    International Nuclear Information System (INIS)

    Subasi, A. L.; Tanatar, B.; Pieri, P.; Senatore, G.

    2010-01-01

    We study excitonic condensation in an electron-hole bilayer system with unequal layer densities at zero temperature. Using mean-field theory we solve the Bardeen-Cooper-Schrieffer (BCS) gap equations numerically and investigate the effects of intralayer interactions. The electron-hole system evolves from BCS in the weak coupling limit to Bose-Einstein condensation (BEC) in the strong coupling limit. We analyze the stability of the Sarma phase with k,-k pairing by calculating the superfluid mass density and also by checking the compressibility matrix. We find that with bare Coulomb interactions the superfluid density is always positive in the Sarma phase, due to a peculiar momentum structure of the gap function originating from the singular behavior of the Coulomb potential at zero momentum and the presence of a sharp Fermi surface. Introducing a simple model for screening, we find that the superfluid density becomes negative in some regions of the phase diagram, corresponding to an instability toward a Fulde-Ferrel-Larkin-Ovchinnikov-type superfluid phase. Thus, intralayer interaction and screening together can lead to a rich phase diagram in the BCS-BEC crossover regime in electron-hole bilayer systems.

  6. Optical-electronic shape recognition system based on synergetic associative memory

    Science.gov (United States)

    Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong

    2001-04-01

    This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.

  7. H I OBSERVATIONS OF THE SUPERMASSIVE BINARY BLACK HOLE SYSTEM IN 0402+379

    International Nuclear Information System (INIS)

    Rodriguez, C.; Taylor, G. B.; Pihlstroem, Y. M.; Zavala, R. T.; Peck, A. B.

    2009-01-01

    We have recently discovered a supermassive binary black hole system with a projected separation between the two black holes of 7.3 pc in the radio galaxy 0402+379 (Rodriguez et al. 2006). This is the most compact supermassive binary black hole pair yet imaged by more than two orders of magnitude. We present Global VLBI observations at 1.3464 GHz of this radio galaxy, taken to improve the quality of the H I data. Two absorption lines are found toward the southern jet of the source, one redshifted by 370 ± 10 km s -1 and the other blueshifted by 700 ± 10 km s -1 with respect to the systemic velocity of the source, which, along with the results obtained for the opacity distribution over the source, suggests the presence of two mass clumps rotating around the central region of the source. We propose a model consisting of a geometrically thick disk, of which we only see a couple of clumps, that reproduces the velocities measured from the H I absorption profiles. These clumps rotate in circular Keplerian orbits around an axis that crosses one of the supermassive black holes of the binary system in 0402+379. We find an upper limit for the inclination angle of the twin jets of the source to the line of sight of θ = 66 deg., which, according to the proposed model, implies a lower limit on the central mass of ∼7 x 10 8 M sun and a lower limit for the scale height of the thick disk of ∼12 pc.

  8. Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

    Science.gov (United States)

    Poock, G. K.; Martin, B. J.

    1984-02-01

    This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

  9. A Dancing Black Hole

    Science.gov (United States)

    Shoemaker, Deirdre; Smith, Kenneth; Schnetter, Erik; Fiske, David; Laguna, Pablo; Pullin, Jorge

    2002-04-01

    Recently, stationary black holes have been successfully simulated for up to times of approximately 600-1000M, where M is the mass of the black hole. Considering that the expected burst of gravitational radiation from a binary black hole merger would last approximately 200-500M, black hole codes are approaching the point where simulations of mergers may be feasible. We will present two types of simulations of single black holes obtained with a code based on the Baumgarte-Shapiro-Shibata-Nakamura formulation of the Einstein evolution equations. One type of simulations addresses the stability properties of stationary black hole evolutions. The second type of simulations demonstrates the ability of our code to move a black hole through the computational domain. This is accomplished by shifting the stationary black hole solution to a coordinate system in which the location of the black hole is time dependent.

  10. Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2013-01-01

    Full Text Available With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activity, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation towards the performance of human activity recognition.

  11. Gravitational waves from the Papaloizou-Pringle instability in black-hole-torus systems.

    Science.gov (United States)

    Kiuchi, Kenta; Shibata, Masaru; Montero, Pedro J; Font, José A

    2011-06-24

    Black hole (BH)-torus systems are promising candidates for the central engine of γ-ray bursts (GRBs), and also possible outcomes of the collapse of supermassive stars to supermassive black holes (SMBHs). By three-dimensional general relativistic numerical simulations, we show that an m = 1 nonaxisymmetric instability grows for a wide range of self-gravitating tori orbiting BHs. The resulting nonaxisymmetric structure persists for a time scale much longer than the dynamical one, becoming a strong emitter of large amplitude, quasiperiodic gravitational waves. Our results indicate that both, the central engine of GRBs and newly formed SMBHs, can be strong gravitational wave sources observable by forthcoming ground-based and spacecraft detectors.

  12. 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...

  13. 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.

  14. The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition

    Science.gov (United States)

    Menasri, Farès; Louradour, Jérôme; Bianne-Bernard, Anne-Laure; Kermorvant, Christopher

    2012-01-01

    This paper describes the system for the recognition of French handwriting submitted by A2iA to the competition organized at ICDAR2011 using the Rimes database. This system is composed of several recognizers based on three different recognition technologies, combined using a novel combination method. A framework multi-word recognition based on weighted finite state transducers is presented, using an explicit word segmentation, a combination of isolated word recognizers and a language model. The system was tested both for isolated word recognition and for multi-word line recognition and submitted to the RIMES-ICDAR2011 competition. This system outperformed all previously proposed systems on these tasks.

  15. Numerical investigations of cooling holes system role in the protection of the walls of a gas turbine combustion chamber

    Energy Technology Data Exchange (ETDEWEB)

    Ben Sik Ali, Ahlem; Kriaa, Wassim; Mhiri, Hatem [Ecole Nationale D' Ingenieurs de Monastir, Unite de Thermique et Thermodynamique des Procedes industriels, Monastir (Tunisia); Bournot, Philippe [IUSTI, UMR CNRS 6595, Marseille (France)

    2012-05-15

    Numerical simulations in a gas turbine Swirl stabilized combustor were conducted to investigate the effectiveness of a cooling system in the protection of combustor walls. The studied combustion chamber has a high degree of geometrical complexity related to the injection system as well as the cooling system based on a big distribution of small holes (about 3,390 holes) bored on the flame tube walls. Two cases were considered respectively the flame tube without and with its cooling system. The calculations were carried out using the industrial CFD code FLUENT 6.2. The various simulations made it possible to highlight the role of cooling holes in the protection of the flame tube walls against the high temperatures of the combustion products. In fact, the comparison between the results of the two studied cases demonstrated that the walls temperature can be reduced by about 800 C by the mean of cooling holes technique. (orig.)

  16. 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...

  17. The Lagrange Points in a Binary Black Hole System: Applications to Electromagnetic Signatures

    Science.gov (United States)

    Schnittman, Jeremy

    2010-01-01

    We study the stability and evolution of the Lagrange points L_4 and L-5 in a black hole (BH) binary system, including gravitational radiation. We find that gas and stars can be shepherded in with the BH system until the final moments before merger, providing the fuel for a bright electromagnetic counterpart to a gravitational wave signal. Other astrophysical signatures include the ejection of hyper-velocity stars, gravitational collapse of globular clusters, and the periodic shift of narrow emission lines in AGN.

  18. BEC-BCS-laser crossover in Coulomb-correlated electron-hole-photon systems

    International Nuclear Information System (INIS)

    Yamaguchi, M; Kamide, K; Ogawa, T; Yamamoto, Y

    2012-01-01

    Many-body features caused by Coulomb correlations are of great importance for understanding phenomena pertaining to polariton systems in semiconductor microcavities, i.e. electron-hole-photon systems. Remarkable many-body effects are shown to exist in both thermal-equilibrium phases and non-equilibrium lasing states. We then show a unified framework for connecting the thermal-equilibrium and the non-equilibrium steady states based on a non-equilibrium Green's function approach. Bose-Einstein condensate (BEC)-Bardeen-Cooper-Schrieffer (BCS)-laser crossovers are investigated by using this approach. (paper)

  19. Investigation of the Role of Hole Doping in Different High Temperature Superconducting Systems Using XANES Technique

    International Nuclear Information System (INIS)

    Hamdan, N.M.; Hasan, A.; Faiz, M.; Salim, M.A.; Hussain, Z.

    2004-01-01

    X-ray Absorption Near edge Structure (XANES) technique was used to study the role of hole doping in F-doped Hg-1223 and the Ce-doped Tl-1223. Oxygen k-edge and Cu L2,3-edge structures were thoroughly investigated. The pre-edge features of O k-edge spectra, as a function of doping, reveal important information about the projected local density of unoccupied states on the O sites in the region close to the absorption edge, which is a measure of O 2p hole concentration in the valance band. Furthermore, the Cu L2,3 absorption edge provides useful information about the valance state of Cu which is also related to the hole state in the CuO 2 planes. In this work, we will discuss these XANES results in these systems and correlate the observed improvements in the superconducting properties to the electronic structure in the CuO2 planes

  20. Very deep hole systems engineering studies. [20,000 ft or less

    Energy Technology Data Exchange (ETDEWEB)

    None

    1983-12-01

    Very Deep Hole (VDH) Waste Isolation is an alternative to or an augmentation of the mined geologic repository (MGR) for high-level radioactive waste. This planning study of the VDH concept identifies the significant problem areas associated with a VDH system, identifies and discusses attributes of the VDH concept, narrows discussions to a reference VDH system, and provides preliminary estimates of costs and schedule, and an engineering program plan for VDH system and equipment development. For the reference VDH selected for this study, the nuclear waste is emplaced and disposed in 20-in. holes that are drilled by modified rotary rigs and at depths of 20,000 feet or less. The waste is to be contained within a repository zone of the host rock having low porosity, low hydraulic gradient, and low permeability, and the repository zone is not penetrated by any aquifer. Thus, the depth of emplacement and characteristics of the host rock provide isolation that would preclude unacceptable migration of radionuclides to the biosphere. The VDH concept is credible and the reference system is technically feasible, logical, practical, and achievable by the year 2000, with slight modification of present technology. In terms of costs, the reference VDH system compares favorably with costs for MGR system disposal in salt, granite, shale, and basalt. 130 references, 39 figures, 17 tables.

  1. Pengoperasian Beban Listrik Fase Tunggal Terkendali Melalui Minimum System Berbasis Mikrokontroler Dan Sensor Voice Recognition (Vr)

    OpenAIRE

    Goeritno, Arief; Ginting, Sandy Ferdiansyah; Yatim, Rakhmad

    2017-01-01

    Minimum system berbasis mikrokontroler dan sensor voice recognition (VR) sebagai pengendali aktuator telah digunakan untuk pengoperasian beban listrik fase tunggal. Minimum system adalah suatu sistem yang tersusun melalui 2 (dua) tahapan, yaitu (a) diagram rangkaian dan bentuk fisis board dan (b) pengawatan terintegrasi terhadap minimum system pada sistem mikrokontroler ATmega16. Keberadaan sistem mikrokontroler pada minimum system perlu program tertanam melalui pemrograman berbasis bahasa ...

  2. Black holes are hot

    International Nuclear Information System (INIS)

    Gibbons, G.

    1976-01-01

    Recent work, which has been investigating the use of the concept of entropy with respect to gravitating systems, black holes and the universe as a whole, is discussed. The resulting theory of black holes assigns a finite temperature to them -about 10 -7 K for ordinary black holes of stellar mass -which is in complete agreement with thermodynamical concepts. It is also shown that black holes must continuously emit particles just like ordinary bodies which have a certain temperature. (U.K.)

  3. 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.

  4. 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

  5. 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....... PTX3 interacts with C1q, ficolin-1 and ficolin-2 as well as mannose-binding lectin, recognition molecules in the classical and lectin complement pathways. The formation of these heterocomplexes results in cooperative pathogen recognition and complement activation. Interactions with C4b binding protein...

  6. 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.

  7. The use of open and machine vision technologies for development of gesture recognition intelligent systems

    Science.gov (United States)

    Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

    2018-05-01

    The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

  8. 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)

  9. 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)

  10. 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.

  11. Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

    Science.gov (United States)

    Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

    1993-03-01

    The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

  12. Multi-Modal Activity Recognition Systems with Minimal Training Data and Unobtrusive Environmental Instrumentations

    OpenAIRE

    Bauer, Gerald

    2014-01-01

    The recognition of day-to-day activities is still a very challenging and important research topic. During recent years, a lot of research has gone into designing and realizing smart environ- ments in different application areas such as health care, maintenance, sports or smart homes. As a result, a large amount of sensor modalities were developed, different types of activity and context recognition services were implemented and the resulting systems were benchmarked using state-of-the-art eva...

  13. Authentication: From Passwords to Biometrics: An implementation of a speaker recognition system on Android

    OpenAIRE

    Heimark, Erlend

    2012-01-01

    We implement a biometric authentication system on the Android platform, which is based on text-dependent speaker recognition. The Android version used in the application is Android 4.0. The application makes use of the Modular Audio Recognition Framework, from which many of the algorithms are adapted in the processes of preprocessing and feature extraction. In addition, we employ the Dynamic Time Warping (DTW) algorithm for the comparison of different voice features. A training procedure is i...

  14. Black hole hair removal

    International Nuclear Information System (INIS)

    Banerjee, Nabamita; Mandal, Ipsita; Sen, Ashoke

    2009-01-01

    Macroscopic entropy of an extremal black hole is expected to be determined completely by its near horizon geometry. Thus two black holes with identical near horizon geometries should have identical macroscopic entropy, and the expected equality between macroscopic and microscopic entropies will then imply that they have identical degeneracies of microstates. An apparent counterexample is provided by the 4D-5D lift relating BMPV black hole to a four dimensional black hole. The two black holes have identical near horizon geometries but different microscopic spectrum. We suggest that this discrepancy can be accounted for by black hole hair - degrees of freedom living outside the horizon and contributing to the degeneracies. We identify these degrees of freedom for both the four and the five dimensional black holes and show that after their contributions are removed from the microscopic degeneracies of the respective systems, the result for the four and five dimensional black holes match exactly.

  15. Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

    2016-12-01

    Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

  16. A Russian Keyword Spotting System Based on Large Vocabulary Continuous Speech Recognition and Linguistic Knowledge

    Directory of Open Access Journals (Sweden)

    Valentin Smirnov

    2016-01-01

    Full Text Available The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use.

  17. 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

  18. 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

    2017-10-01

    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

  19. A Cooking Recipe Recommendation System with Visual Recognition of Food Ingredients

    Directory of Open Access Journals (Sweden)

    Keiji Yanai

    2014-04-01

    Full Text Available In this paper, we propose a cooking recipe recommendation system which runs on a consumer smartphone as an interactive mobile application. The proposed system employs real-time visual object recognition of food ingredients, and recommends cooking recipes related to the recognized food ingredients. Because of visual recognition, by only pointing a built-in camera on a smartphone to food ingredients, a user can get to know a related cooking recipes instantly. The objective of the proposed system is to assist people who cook to decide a cooking recipe at grocery stores or at a kitchen. In the current implementation, the system can recognize 30 kinds of food ingredient in 0.15 seconds, and it has achieved the 83.93% recognition rate within the top six candidates. By the user study, we confirmed the effectiveness of the proposed system.

  20. A Support System for the Electric Appliance Control Using Pose Recognition

    Science.gov (United States)

    Kawano, Takuya; Yamamoto, Kazuhiko; Kato, Kunihito; Hongo, Hitoshi

    In this paper, we propose an electric appliance control support system for aged and bedridden people using pose recognition. We proposed a pose recognition system that distinguishes between seven poses of the user on the bed. First, the face and arm regions of the user are detected by using the skin color. Our system focuses a recognition region surrounding the face region. Next, the higher order local autocorrelation features within the region are extracted. The linear discriminant analysis creates the coefficient matrix that can optimally distinguish among training data from the seven poses. Our algorithm can recognize the seven poses even if the subject wears different clothes and slightly shifts or slants on the bed. From the experimental results, our system achieved an accuracy rate of over 99 %. Then, we show that it possibles to construct one of a user-friendly system.

  1. Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

    Science.gov (United States)

    Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

    2014-01-01

    The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. 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.

  3. 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.

  4. 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.

  5. A multi-view face recognition system based on cascade face detector and improved Dlib

    Science.gov (United States)

    Zhou, Hongjun; Chen, Pei; Shen, Wei

    2018-03-01

    In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

  6. Black holes

    International Nuclear Information System (INIS)

    Feast, M.W.

    1981-01-01

    This article deals with two questions, namely whether it is possible for black holes to exist, and if the answer is yes, whether we have found any yet. In deciding whether black holes can exist or not the central role in the shaping of our universe played by the forse of gravity is discussed, and in deciding whether we are likely to find black holes in the universe the author looks at the way stars evolve, as well as white dwarfs and neutron stars. He also discusses the problem how to detect a black hole, possible black holes, a southern black hole, massive black holes, as well as why black holes are studied

  7. 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.

  8. Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

    Science.gov (United States)

    Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

    We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

  9. 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.

  10. A Robust and Device-Free System for the Recognition and Classification of Elderly Activities.

    Science.gov (United States)

    Li, Fangmin; Al-Qaness, Mohammed Abdulaziz Aide; Zhang, Yong; Zhao, Bihai; Luan, Xidao

    2016-12-01

    Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise.

  11. Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits

    International Nuclear Information System (INIS)

    Gu Yu; Li Qiang

    2014-01-01

    We present a new pattern recognition system based on moving average and linear discriminant analysis (LDA), which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  12. Introduction and Overview of the Vicens-Reddy Speech Recognition System.

    Science.gov (United States)

    Kameny, Iris; Ritea, H.

    The Vicens-Reddy System is unique in the sense that it approaches the problem of speech recognition as a whole, rather than treating particular aspects of the problems as in previous attempts. For example, where earlier systems treated only segmentation of speech into phoneme groups, or detected phonemes in a given context, the Vicens-Reddy System…

  13. A NEW STRATEGY FOR IMPROVING FEATURE SETS IN A DISCRETE HMM­BASED HANDWRITING RECOGNITION SYSTEM

    NARCIS (Netherlands)

    Grandidier, F.; Sabourin, R.; Suen, C.Y.; Gilloux, M.

    2004-01-01

    In this paper we introduce a new strategy for improving a discrete HMM­based handwriting recognition system, by integrating several information sources from specialized feature sets. For a given system, the basic idea is to keep the most discriminative features, and to replace the others with new

  14. Geometric Calibration and Image Reconstruction for a Segmented Slant-Hole Stationary Cardiac SPECT System.

    Science.gov (United States)

    Mao, Yanfei; Yu, Zhicong; Zeng, Gengsheng L

    2015-06-01

    A dedicated stationary cardiac single-photon emission computed tomography (SPECT) system with a novel segmented slant-hole collimator has been developed. The goal of this paper is to calibrate this new imaging geometry with a point source. Unlike the commercially available dedicated cardiac SPECT systems, which are specialized and can be used only to image the heart, our proposed cardiac system is based on a conventional SPECT system but with a segmented slant-hole collimator replacing the collimator. For a dual-head SPECT system, 2 segmented collimators, each with 7 sections, are arranged in an L-shaped configuration such that they can produce a complete cardiac SPECT image with only one gantry position. A calibration method was developed to estimate the geometric parameters of each collimator section as well as the detector rotation radius, under the assumption that the point source location is calculated using the central-section data. With a point source located off the rotation axis, geometric parameters for each collimator section can be estimated independently. The parameters estimated individually are further improved by a joint objective function that uses all collimator sections simultaneously and incorporates the collimator symmetry information. Estimation results and images reconstructed from estimated parameters are presented for both simulated and real data acquired from a prototype collimator. The calibration accuracy was validated by computer simulations with an error of about 0.1° for the slant angles and about 1 mm for the rotation radius. Reconstructions of a heart-insert phantom did not show any image artifacts of inaccurate geometric parameters. Compared with the detector's intrinsic resolution, the estimation error is small and can be ignored. Therefore, the accuracy of the calibration is sufficient for cardiac SPECT imaging. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  15. Comparing planar image quality of rotating slat and parallel hole collimation: influence of system modeling

    International Nuclear Information System (INIS)

    Holen, Roel van; Vandenberghe, Stefaan; Staelens, Steven; Lemahieu, Ignace

    2008-01-01

    The main remaining challenge for a gamma camera is to overcome the existing trade-off between collimator spatial resolution and system sensitivity. This problem, strongly limiting the performance of parallel hole collimated gamma cameras, can be overcome by applying new collimator designs such as rotating slat (RS) collimators which have a much higher photon collection efficiency. The drawback of a RS collimated gamma camera is that, even for obtaining planar images, image reconstruction is needed, resulting in noise accumulation. However, nowadays iterative reconstruction techniques with accurate system modeling can provide better image quality. Because the impact of this modeling on image quality differs from one system to another, an objective assessment of the image quality obtained with a RS collimator is needed in comparison to classical projection images obtained using a parallel hole (PH) collimator. In this paper, a comparative study of image quality, achieved with system modeling, is presented. RS data are reconstructed to planar images using maximum likelihood expectation maximization (MLEM) with an accurate Monte Carlo derived system matrix while PH projections are deconvolved using a Monte Carlo derived point-spread function. Contrast-to-noise characteristics are used to show image quality for cold and hot spots of varying size. Influence of the object size and contrast is investigated using the optimal contrast-to-noise ratio (CNR o ). For a typical phantom setup, results show that cold spot imaging is slightly better for a PH collimator. For hot spot imaging, the CNR o of the RS images is found to increase with increasing lesion diameter and lesion contrast while it decreases when background dimensions become larger. Only for very large background dimensions in combination with low contrast lesions, the use of a PH collimator could be beneficial for hot spot imaging. In all other cases, the RS collimator scores better. Finally, the simulation of a

  16. 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%.

  17. Impact of a voice recognition system on report cycle time and radiologist reading time

    Science.gov (United States)

    Melson, David L.; Brophy, Robert; Blaine, G. James; Jost, R. Gilbert; Brink, Gary S.

    1998-07-01

    Because of its exciting potential to improve clinical service, as well as reduce costs, a voice recognition system for radiological dictation was recently installed at our institution. This system will be clinically successful if it dramatically reduces radiology report turnaround time without substantially affecting radiologist dictation and editing time. This report summarizes an observer study currently under way in which radiologist reporting times using the traditional transcription system and the voice recognition system are compared. Four radiologists are observed interpreting portable intensive care unit (ICU) chest examinations at a workstation in the chest reading area. Data are recorded with the radiologists using the transcription system and using the voice recognition system. The measurements distinguish between time spent performing clerical tasks and time spent actually dictating the report. Editing time and the number of corrections made are recorded. Additionally, statistics are gathered to assess the voice recognition system's impact on the report cycle time -- the time from report dictation to availability of an edited and finalized report -- and the length of reports.

  18. 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.

  19. The effect of optical system design for laser micro-hole drilling process

    Science.gov (United States)

    Ding, Chien-Fang; Lan, Yin-Te; Chien, Yu-Lun; Young, Hong-Tsu

    2017-08-01

    Lasers are a promising high accuracy tool to make small holes in composite or hard material. They offer advantages over the conventional machining process, which is time consuming and has scaling limitations. However, the major downfall in laser material processing is the relatively large heat affect zone or number of molten burrs it generates, even when using nanosecond lasers over high-cost ultrafast lasers. In this paper, we constructed a nanosecond laser processing system with a 532 nm wavelength laser source. In order to enhance precision and minimize the effect of heat generation with the laser drilling process, we investigated the geometric shape of optical elements and analyzed the images using the modulation transfer function (MTF) and encircled energy (EE) by using optical software Zemax. We discuss commercial spherical lenses, including plano-convex lenses, bi-convex lenses, plano-concave lenses, bi-concave lenses, best-form lenses, and meniscus lenses. Furthermore, we determined the best lens configuration by image evaluation, and then verified the results experimentally by carrying out the laser drilling process on multilayer flexible copper clad laminate (FCCL). The paper presents the drilling results obtained with different lens configurations and found the best configuration had a small heat affect zone and a clean edge along laser-drilled holes.

  20. Towards low-dimensional hole systems in Be-doped GaAs nanowires

    DEFF Research Database (Denmark)

    Ullah, A. R.; Gluschke, J. G.; Jeppesen, Peter Krogstrup

    2017-01-01

    -gates produced using GaAs nanowires with three different Be-doping densities and various AuBe contact processing recipes. We show that contact annealing only brings small improvements for the moderately doped devices under conditions of lower anneal temperature and short anneal time. We only obtain good......GaAs was central to the development of quantum devices but is rarely used for nanowire-based quantum devices with InAs, InSb and SiGe instead taking the leading role. p-type GaAs nanowires offer a path to studying strongly confined 0D and 1D hole systems with strong spin–orbit effects, motivating...... our development of nanowire transistors featuring Be-doped p-type GaAs nanowires, AuBe alloy contacts and patterned local gate electrodes towards making nanowire-based quantum hole devices. We report on nanowire transistors with traditional substrate back-gates and EBL-defined metal/oxide top...

  1. Black holes

    OpenAIRE

    Brügmann, B.; Ghez, A. M.; Greiner, J.

    2001-01-01

    Recent progress in black hole research is illustrated by three examples. We discuss the observational challenges that were met to show that a supermassive black hole exists at the center of our galaxy. Stellar-size black holes have been studied in x-ray binaries and microquasars. Finally, numerical simulations have become possible for the merger of black hole binaries.

  2. Evaluation of iris recognition system for wavefront-guided laser in situ keratomileusis for myopic astigmatism.

    Science.gov (United States)

    Ghosh, Sudipta; Couper, Terry A; Lamoureux, Ecosse; Jhanji, Vishal; Taylor, Hugh R; Vajpayee, Rasik B

    2008-02-01

    To evaluate the visual and refractive outcomes of wavefront-guided laser in situ keratomileusis (LASIK) using an iris recognition system for the correction of myopic astigmatism. Centre for Eye Research Australia, Melbourne Excimer Laser Research Group, and Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia. A comparative analysis of wavefront-guided LASIK was performed with an iris recognition system (iris recognition group) and without iris recognition (control group). The main parameters were uncorrected visual acuity (UCVA), best spectacle-corrected visual acuity, amount of residual cylinder, manifest spherical equivalent (SE), and the index of success using the Alpins method of astigmatism analysis 1 and 3 months postoperatively. A P value less than 0.05 was considered statistically significant. Preoperatively, the mean SE was -4.32 diopters (D) +/- 1.59 (SD) in the iris recognition group (100 eyes) and -4.55 +/- 1.87 D in the control group (98 eyes) (P = .84). At 3 months, the mean SE was -0.05 +/- 0.21 D and -0.20 +/- 0.40 D, respectively (P = .001), and an SE within +/-0.50 D of emmetropia was achieved in 92.0% and 85.7% of eyes, respectively (P = .07). At 3 months, the UCVA was 20/20 or better in 90.0% and 76.5% of eyes, respectively. A statistically significant difference in the amount of astigmatic correction was seen between the 2 groups (P = .00 and P = .01 at 1 and 3 months, respectively). The index of success was 98.0% in the iris recognition group and 81.6% in the control group (P = .03). Iris recognition software may achieve better visual and refractive outcomes in wavefront-guided LASIK for myopic astigmatism.

  3. 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)

  4. 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.

  5. 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)

  6. Many-particle correlations in quasi-two-dimensional electron-hole systems

    International Nuclear Information System (INIS)

    Nikolaev, Valentin

    2002-01-01

    This thesis reports a theoretical investigation of many-particle correlation effects in semiconductor heterostructures containing quantum wells. Particular attention is paid towards quasi-particle pair correlations. Using the Green's function technique and the ladder approximation as a basis, the generalized mass action law, which describes the redistribution of particles between correlated and uncorrelated states in quasi-two-dimensional systems for different temperatures and total densities, is derived. The expression is valid beyond the low-density limit, which allows us to investigate the transition of the system from a dilute exciton gas to a dense electron-hole plasma. A generalized Levinson theorem, which takes k-space filling into account, is formulated. Screening in quasi-two-dimensional systems is analyzed rigorously. Firstly, the qualitatively new mechanism of static local screening by indirect excitons is studied using the simple Thomas-Fermi approximation. Then, a detailed many-body description suitable for a proper account of dynamic screening by a quasi-2D electron-hole plasma, and consistent with the previously derived mass action law, is provided. The generalized Lindhard approximation and excitonic plasmon-pole approximations are also derived. The theory is applied to single and double quantum wells. A self-consistent procedure is developed for numerical investigation of the ionization degree of an electron-hole plasma at different values of temperature/exciton Rydberg ratios. This procedure accounts for screening, k-space filling (exciton bleaching), and the formation of excitons. An abrupt jump in the value of the ionization degree that happens with an increase of the carrier density or temperature (Mott transition) is found in a certain density-temperature region. It has been found that the critical density of the Mott transition for indirect excitons may be much smaller than that for direct excitons. A suggestion has been made that some of the

  7. 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...

  8. An application of the tensor virial theorem to hole + vortex + bulge systems

    Science.gov (United States)

    Caimmi, R.

    2009-04-01

    The tensor virial theorem for subsystems is formulated for three-component systems and further effort is devoted to a special case where the inner subsystems and the central region of the outer one are homogeneous, the last surrounded by an isothermal homeoid. The virial equations are explicitly written under the additional restrictions: (i) similar and similarly placed inner subsystems, and (ii) spherical outer subsystem. An application is made to hole + vortex + bulge systems, in the limit of flattened inner subsystems, which implies three virial equations in three unknowns. Using the Faber-Jackson relation, R∝σ02, the standard M- σ0 form (M∝σ04) is deduced from qualitative considerations. The projected bulge velocity dispersion to projected vortex velocity ratio, η=(σ)33/{[(v)qq]2+[(σ)qq]2}, as a function of the fractional radius, y=R/R, and the fractional masses, m=M/M and m=M/M, is studied in the range of interest, 0⩽m=M/M⩽5 [Escala, A., 2006. ApJ, 648, L13] and 229⩽m⩽795 [Marconi, A., Hunt, L.H., 2003. ApJ 589, L21], consistent with observations. The related curves appear to be similar to Maxwell velocity distributions, which implies a fixed value of η below the maximum corresponds to two different configurations: a compact bulge on the left of the maximum, and an extended bulge on the right. All curves lie very close one to the other on the left of the maximum, and parallel one to the other on the right. On the other hand, fixed m or m, and y, are found to imply more massive bulges passing from bottom to top along a vertical line on the (Oyη) plane, and vice versa. The model is applied to NGC 4374 and NGC 4486, taking the fractional mass, m, and the fractional radius, y, as unknowns, and the bulge mass is inferred from the knowledge of the hole mass, and compared with results from different methods. In presence of a massive vortex (m=5), the hole mass has to be reduced by a factor 2-3 with respect to the case of a massless vortex, to get

  9. Down-Hole Heat Exchangers: Modelling of a Low-Enthalpy Geothermal System for District Heating

    Directory of Open Access Journals (Sweden)

    M. Carlini

    2012-01-01

    Full Text Available In order to face the growing energy demands, renewable energy sources can provide an alternative to fossil fuels. Thus, low-enthalpy geothermal plants may play a fundamental role in those areas—such as the Province of Viterbo—where shallow groundwater basins occur and conventional geothermal plants cannot be developed. This may lead to being fuelled by locally available sources. The aim of the present paper is to exploit the heat coming from a low-enthalpy geothermal system. The experimental plant consists in a down-hole heat exchanger for civil purposes and can supply thermal needs by district heating. An implementation in MATLAB environment is provided in order to develop a mathematical model. As a consequence, the amount of withdrawable heat can be successfully calculated.

  10. 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...

  11. an enhanced iris recognition and authentication system using ...

    African Journals Online (AJOL)

    Biu et al.

    1Department of Mathematical Sciences, Kaduna State University, Kaduna – Nigeria. (E-mail: ..... localization, the iris is in a circulation fashion then lastly, the image is saved into .... Conference on Computer Engineering Systems. Cleve, K.

  12. Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

    Science.gov (United States)

    Li, Jianwei; Nowak, Piotr; Otto, Sijbren

    2013-06-26

    Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

  13. 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.

  14. 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.

  15. An introduction to application-independent evaluation of speaker recognition systems

    NARCIS (Netherlands)

    Leeuwen, D.A. van; Brümmer, N.

    2007-01-01

    In the evaluation of speaker recognition systems - an important part of speaker classification [1], the trade-off between missed speakers and false alarms has always been an important diagnostic tool. NIST has defined the task of speaker detection with the associated Detection Cost Function (DCF) to

  16. Cherry Picking Robot Vision Recognition System Based on OpenCV

    Directory of Open Access Journals (Sweden)

    Zhang Qi Rong

    2016-01-01

    Full Text Available Through OpenCV function, the cherry in a natural environment image after image preprocessing, color recognition, threshold segmentation, morphological filtering, edge detection, circle Hough transform, you can draw the cherry’s center and circular contour, to carry out the purpose of the machine picking. The system is simple and effective.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

    Science.gov (United States)

    Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

    2018-04-01

    An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

  3. System certification progress in concept recognition in IAEA regulation

    International Nuclear Information System (INIS)

    Luna, R.E.; Pollog, T.

    1995-01-01

    System Certification is a regulatory concept which is intended to expand the scope of radioactive material transport regulations by allowing alternative means for proving compliance with the requisite standards of safety set out in transport regulations. In practice it may allow more stringent requirements in one aspect of the regulations to be substituted for less stringent application in other areas so long as the safety standard provided by regulation is preserved. The concept is widely perceived as the imposition of operational controls in exchange for relaxation of packaging standards, but that is only one possibility in the spectrum of potential actions under a System Certification provision in IAEA or national regulations

  4. 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.

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

    Indian Academy of Sciences (India)

    are on the way for the development of efficient OCR systems for Indian languages, .... Each vowel has a vowel sign (modifier) and each consonant has a basic form (prim- itive). ..... as a single class of character in the first stage of classification.

  6. 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...

  7. 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.

  8. Vision-based obstacle recognition system for automated lawn mower robot development

    Science.gov (United States)

    Mohd Zin, Zalhan; Ibrahim, Ratnawati

    2011-06-01

    Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

  9. 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.

  10. 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)

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

    NARCIS (Netherlands)

    Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, 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

  12. The MITLL NIST LRE 2015 Language Recognition System

    Science.gov (United States)

    2016-05-06

    Cluster Target Classes Arabic Egyptian , Iraqi, Levantine, Maghrebi, Modern Standard Chinese Cantonese, Mandarin, Min, Wu English...42.69 Egyptian (ara-arz) 440 97.27 British English (eng-gbr) 47 0.51 Indian English (eng-sas) 418 7.82 American English (eng-usg) 428 100.37...are obtained by training a Deep Neural Network (DNN) using a seven hidden layer architecture . On these systems, all hidden layers have 1024 nodes

  13. Developing a broadband automatic speech recognition system for Afrikaans

    CSIR Research Space (South Africa)

    De Wet, Febe

    2011-08-01

    Full Text Available baseline transcription for the news data. The match between a baseline transcription and its corre- sponding audio can be evaluated automatically using an ASR system in forced alignment mode. Only those bulletins for which a bad match is indicated... Component Index for data [3]. occurrence of Afrikaans words3. Other text corpora that are currently under construction in- clude daily downloads of the scripts of news bulletins that are read on an Afrikaans radio station as well as transcripts of par...

  14. Involvement of the intrinsic/default system in movement-related self recognition.

    Science.gov (United States)

    Salomon, Roy; Malach, Rafael; Lamy, Dominique

    2009-10-21

    The question of how people recognize themselves and separate themselves from the environment and others has long intrigued philosophers and scientists. Recent findings have linked regions of the 'default brain' or 'intrinsic system' to self-related processing. We used a paradigm in which subjects had to rely on subtle sensory-motor synchronization differences to determine whether a viewed movement belonged to them or to another person, while stimuli and task demands associated with the "responded self" and "responded other" conditions were precisely matched. Self recognition was associated with enhanced brain activity in several ROIs of the intrinsic system, whereas no differences emerged within the extrinsic system. This self-related effect was found even in cases where the sensory-motor aspects were precisely matched. Control conditions ruled out task difficulty as the source of the differential self-related effects. The findings shed light on the neural systems underlying bodily self recognition.

  15. 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.

  16. Mesoscopic Structural Observations of Cores from the Chelungpu Fault System, Taiwan Chelungpu-Fault Drilling Project Hole-A, Taiwan

    Directory of Open Access Journals (Sweden)

    Hiroki Sone

    2007-01-01

    Full Text Available Structural characteristics of fault rocks distributed within major fault zones provide basic information in understanding the physical aspects of faulting. Mesoscopic structural observations of the drilledcores from Taiwan Chelungpu-fault Drilling Project Hole-A are reported in this article to describe and reveal the distribution of fault rocks within the Chelungpu Fault System.

  17. 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.

  18. An analog VLSI real time optical character recognition system based on a neural architecture

    International Nuclear Information System (INIS)

    Bo, G.; Caviglia, D.; Valle, M.

    1999-01-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system

  19. An analog VLSI real time optical character recognition system based on a neural architecture

    Energy Technology Data Exchange (ETDEWEB)

    Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering

    1999-03-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.

  20. 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.

  1. Face Prediction Model for an Automatic Age-invariant Face Recognition System

    OpenAIRE

    Yadav, Poonam

    2015-01-01

    07.11.14 KB. Emailed author re copyright. Author says that copyright is retained by author. Ok to add to spiral Automated face recognition and identi cation softwares are becoming part of our daily life; it nds its abode not only with Facebooks auto photo tagging, Apples iPhoto, Googles Picasa, Microsofts Kinect, but also in Homeland Security Departments dedicated biometric face detection systems. Most of these automatic face identification systems fail where the e ects of aging come into...

  2. Prospects for Probing Strong Gravity with a Pulsar-Black Hole System

    Science.gov (United States)

    Wex, N.; Liu, K.; Eatough, R. P.; Kramer, M.; Cordes, J. M.; Lazio, T. J. W.

    2012-01-01

    The discovery of a pulsar (PSR) in orbit around a black hole (BH) is expected to provide a superb new probe of relativistic gravity and BH properties. Apart from a precise mass measurement for the BH, one could expect a clean verification of the dragging of space-time caused by the BH spin. In order to measure the quadrupole moment of the BH for testing the no-hair theorem of general relativity (GR), one has to hope for a sufficiently massive BH. In this respect, a PSR orbiting the super-massive BH in the center of our Galaxy would be the ultimate laboratory for gravity tests with PSRs. But even for gravity theories that predict the same properties for BHs as GR, a PSR-BH system would constitute an excellent test system, due to the high grade of asymmetry in the strong field properties of these two components. Here we highlight some of the potential gravity tests that one could expect from different PSR-BH systems.

  3. 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%).

  4. Facial Emotion Recognition System – A Machine Learning Approach

    Science.gov (United States)

    Ramalingam, V. V.; Pandian, A.; Jayakumar, Lavanya

    2018-04-01

    Frown is a medium for people correlation and it could be exercised in multiple real systems. Single crucial stage for frown realizing is to exactly select hysterical aspects. This journal proposed a frown realization scheme applying transformative Particle Swarm Optimization (PSO) based aspect accumulation. This entity initially employs changed LVP, handles crisscross adjacent picture element contrast, for achieving the selective first frown portrayal. Then the PSO entity inserted with a concept of micro Genetic Algorithm (mGA) called mGA-embedded PSO designed for achieving aspect accumulation. This study, the technique subsumes no disposable memory, a little-populace insignificant flock, a latest acceleration that amends with the approach and a sub dimension-based in-depth local frown aspect examines. Assistance of provincial utilization and comprehensive inspection examine structure of alleviating of an immature concurrence complication of conventional PSO. Numerous identifiers are used to diagnose different frown expositions. Stationed on extensive study within and other-sphere pictures from the continued Cohn Kanade and MMI benchmark directory appropriately. Determination of the application exceeds most advanced level PSO variants, conventional PSO, classical GA and alternate relevant frown realization structures is described with powerful limit. Extending our accession to a motion based FER application for connecting patch-based Gabor aspects with continuous data in multi-frames.

  5. Black Holes

    OpenAIRE

    Horowitz, Gary T.; Teukolsky, Saul A.

    1998-01-01

    Black holes are among the most intriguing objects in modern physics. Their influence ranges from powering quasars and other active galactic nuclei, to providing key insights into quantum gravity. We review the observational evidence for black holes, and briefly discuss some of their properties. We also describe some recent developments involving cosmic censorship and the statistical origin of black hole entropy.

  6. Pattern-recognition system application to EBR-II plant-life extension

    International Nuclear Information System (INIS)

    King, R.W.; Radtke, W.H.; Mott, J.E.

    1988-01-01

    A computer-based pattern-recognition system, the System State Analyzer (SSA), is being used as part of the EBR-II plant-life extension program for detection of degradation and other abnormalities in plant systems. The SSA is used for surveillance of the EBR-II primary system instrumentation, primary sodium pumps, and plant heat balances. Early results of this surveillance indicate that the SSA can detect instrumentation degradation and system performance degradation over varying time intervals, and can provide derived signal values to replace signals from failed critical sensors. These results are being used in planning for extended-life operation of EBR-II

  7. 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

  8. 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)

  9. Improving a HMM-based off-line handwriting recognition system using MME-PSO optimization

    Science.gov (United States)

    Hamdani, Mahdi; El Abed, Haikal; Hamdani, Tarek M.; Märgner, Volker; Alimi, Adel M.

    2011-01-01

    One of the trivial steps in the development of a classifier is the design of its architecture. This paper presents a new algorithm, Multi Models Evolvement (MME) using Particle Swarm Optimization (PSO). This algorithm is a modified version of the basic PSO, which is used to the unsupervised design of Hidden Markov Model (HMM) based architectures. For instance, the proposed algorithm is applied to an Arabic handwriting recognizer based on discrete probability HMMs. After the optimization of their architectures, HMMs are trained with the Baum- Welch algorithm. The validation of the system is based on the IfN/ENIT database. The performance of the developed approach is compared to the participating systems at the 2005 competition organized on Arabic handwriting recognition on the International Conference on Document Analysis and Recognition (ICDAR). The final system is a combination between an optimized HMM with 6 other HMMs obtained by a simple variation of the number of states. An absolute improvement of 6% of word recognition rate with about 81% is presented. This improvement is achieved comparing to the basic system (ARAB-IfN). The proposed recognizer outperforms also most of the known state-of-the-art systems.

  10. 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.

  11. A Vision-Based Counting and Recognition System for Flying Insects in Intelligent Agriculture

    Directory of Open Access Journals (Sweden)

    Yuanhong Zhong

    2018-05-01

    Full Text Available Rapid and accurate counting and recognition of flying insects are of great importance, especially for pest control. Traditional manual identification and counting of flying insects is labor intensive and inefficient. In this study, a vision-based counting and classification system for flying insects is designed and implemented. The system is constructed as follows: firstly, a yellow sticky trap is installed in the surveillance area to trap flying insects and a camera is set up to collect real-time images. Then the detection and coarse counting method based on You Only Look Once (YOLO object detection, the classification method and fine counting based on Support Vector Machines (SVM using global features are designed. Finally, the insect counting and recognition system is implemented on Raspberry PI. Six species of flying insects including bee, fly, mosquito, moth, chafer and fruit fly are selected to assess the effectiveness of the system. Compared with the conventional methods, the test results show promising performance. The average counting accuracy is 92.50% and average classifying accuracy is 90.18% on Raspberry PI. The proposed system is easy-to-use and provides efficient and accurate recognition data, therefore, it can be used for intelligent agriculture applications.

  12. Formation of the black-hole binary M33 X-7 through mass exchange in a tight massive system.

    Science.gov (United States)

    Valsecchi, Francesca; Glebbeek, Evert; Farr, Will M; Fragos, Tassos; Willems, Bart; Orosz, Jerome A; Liu, Jifeng; Kalogera, Vassiliki

    2010-11-04

    The X-ray source M33 X-7 in the nearby galaxy Messier 33 is among the most massive X-ray binary stellar systems known, hosting a rapidly spinning, 15.65M(⊙) black hole orbiting an underluminous, 70M(⊙) main-sequence companion in a slightly eccentric 3.45-day orbit (M(⊙), solar mass). Although post-main-sequence mass transfer explains the masses and tight orbit, it leaves unexplained the observed X-ray luminosity, the star's underluminosity, the black hole's spin and the orbital eccentricity. A common envelope phase, or rotational mixing, could explain the orbit, but the former would lead to a merger and the latter to an overluminous companion. A merger would also ensue if mass transfer to the black hole were invoked for its spin-up. Here we report simulations of evolutionary tracks which reveal that if M33 X-7 started as a primary body of 85M(⊙)-99M(⊙) and a secondary body of 28M(⊙)-32M(⊙), in a 2.8-3.1-d orbit, its observed properties can be consistently explained. In this model, the main-sequence primary transfers part of its envelope to the secondary and loses the rest in a wind; it ends its life as a ∼16M(⊙) helium star with an iron-nickel core that collapses to a black hole (with or without an accompanying supernova). The release of binding energy, and possibly collapse asymmetries, 'kick' the nascent black hole into an eccentric orbit. Wind accretion explains the X-ray luminosity, and the black-hole spin can be natal.

  13. Black hole Berry phase

    NARCIS (Netherlands)

    de Boer, J.; Papadodimas, K.; Verlinde, E.

    2009-01-01

    Supersymmetric black holes are characterized by a large number of degenerate ground states. We argue that these black holes, like other quantum mechanical systems with such a degeneracy, are subject to a phenomenon which is called the geometric or Berry’s phase: under adiabatic variations of the

  14. A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

    Science.gov (United States)

    Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna

    2016-01-01

    The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

  15. A Human Activity Recognition System Using Skeleton Data from RGBD Sensors

    Directory of Open Access Journals (Sweden)

    Enea Cippitelli

    2016-01-01

    Full Text Available The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

  16. FORMATION OF BLACK HOLE LOW-MASS X-RAY BINARIES IN HIERARCHICAL TRIPLE SYSTEMS

    Energy Technology Data Exchange (ETDEWEB)

    Naoz, Smadar; Stephan, Alexander P. [Department of Physics and Astronomy, University of California, Los Angeles, CA 90095 (United States); Fragos, Tassos [Geneva Observatory, University of Geneva, Chemin des Maillettes 51, 1290 Sauverny (Switzerland); Geller, Aaron; Rasio, Frederic A., E-mail: snaoz@astro.ucla.edu [Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA), Northwestern University, Evanston, IL 60201 (United States)

    2016-05-10

    The formation of black hole (BH) low-mass X-ray binaries (LMXB) poses a theoretical challenge, as low-mass companions are not expected to survive the common-envelope scenario with the BH progenitor. Here we propose a formation mechanism that skips the common-envelope scenario and relies on triple-body dynamics. We study the evolution of hierarchical triples following the secular dynamical evolution up to the octupole-level of approximation, including general relativity, tidal effects, and post-main-sequence evolution such as mass loss, changes to stellar radii, and supernovae. During the dynamical evolution of the triple system the “eccentric Kozai-Lidov” mechanism can cause large eccentricity excitations in the LMXB progenitor, resulting in three main BH-LMXB formation channels. Here we define BH-LMXB candidates as systems where the inner BH-companion star crosses its Roche limit. In the “eccentric” channel (∼81% of the LMXBs in our simulations) the donor star crosses its Roche limit during an extreme eccentricity excitation while still on a wide orbit. Second, we find a “giant” LMXB channel (∼11%), where a system undergoes only moderate eccentricity excitations but the donor star fills its Roche-lobe after evolving toward the giant branch. Third, we identify a “classical” channel (∼8%), where tidal forces and magnetic braking shrink and circularize the orbit to short periods, triggering mass-transfer. Finally, for the giant channel we predict an eccentric (∼0.3–0.6) preferably inclined (∼40°, ∼140°) tertiary, typically on a wide enough orbit (∼10{sup 4} au) to potentially become unbound later in the triple evolution. While this initial study considers only one representative system and neglects BH natal kicks, we expect our scenario to apply across a broad region of parameter space for triple-star systems.

  17. 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)

  18. 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.

  19. 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.

  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. 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.

  2. 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.

  3. Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Shieh

    2014-01-01

    Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

  4. 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.

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

    Science.gov (United States)

    Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

    2017-05-11

    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.

  6. Dynamical spin susceptibility of electron-doped high-Tc cuprates. Comparison with hole-doped systems

    International Nuclear Information System (INIS)

    Suzuki, Atsuo; Mutou, Tetsuya; Tanaka, Syunsuke; Hirashima, Dai S.

    2010-01-01

    The magnetic excitation spectrum of electron-doped copper oxide superconductors is studied by calculating the dynamical spin susceptibility of the two-dimensional Hubbard model in which a d x2-y2 -wave superconducting order parameter is assumed. The spectrum of electron-doped systems is compared with that of hole-doped systems, and the relationship between the frequency at which a peak grows in the spectrum and the superconducting energy gap at a hot spot is investigated. A peak may be observed even when the magnetic resonance condition is not exactly satisfied. We find that, in the electron-doped systems, the resonance condition is less likely to be satisfied than in the hole-doped systems because of the small density of states around the hot spots, and the peak frequency is close to twice the gap magnitude at the hot spots. (author)

  7. A small-animal imaging system capable of multipinhole circular/helical SPECT and parallel-hole SPECT

    International Nuclear Information System (INIS)

    Qian Jianguo; Bradley, Eric L.; Majewski, Stan; Popov, Vladimir; Saha, Margaret S.; Smith, Mark F.; Weisenberger, Andrew G.; Welsh, Robert E.

    2008-01-01

    We have designed and built a small-animal single-photon emission computed tomography (SPECT) imaging system equipped with parallel-hole and multipinhole collimators and capable of circular or helical SPECT. Copper-beryllium parallel-hole collimators suitable for imaging the ∼35 keV photons from the decay of 125 I have been built and installed to achieve useful spatial resolution over a range of object-detector distances and to reduce imaging time on our dual-detector array. To address the resolution limitations in the parallel-hole SPECT and the sensitivity and limited field of view of single-pinhole SPECT, we have incorporated multipinhole circular and helical SPECT in addition to expanding the parallel-hole SPECT capabilities. The pinhole SPECT system is based on a 110 mm diameter circular detector equipped with a pixellated NaI(Tl) scintillator array (1x1x5 mm 3 /pixel). The helical trajectory is accomplished by two stepping motors controlling the rotation of the detector-support gantry and displacement of the animal bed along the axis of rotation of the gantry. Results obtained in SPECT studies of various phantoms show an enlarged field of view, very good resolution and improved sensitivity using multipinhole circular or helical SPECT. Collimators with one, three and five, 1-mm-diameter pinholes have been implemented and compared in these tests. Our objective is to develop a system on which one may readily select a suitable mode of either parallel-hole SPECT or pinhole circular or helical SPECT for a variety of small animal imaging applications

  8. Compact holographic optical neural network system for real-time pattern recognition

    Science.gov (United States)

    Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

    1996-08-01

    One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

  9. 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

  10. 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.

  11. 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

  12. Search for Black-Holes: the nature of the Unseen Companions of the Systems HD 152667 and 72754

    International Nuclear Information System (INIS)

    Freitas Pacheco, J.A. de

    1978-01-01

    The nature of the unseen companions in the single spectroscopic binary systems HD 152667 and HD 72754 is analysed. In the first system, the secondary is likely to be a normal B4 main sequence star while in HD 72754, the secondary, in spite of being the more massive star, is not detected. We cannot at the present, disregard the possibility that this massive object be associated with a collapsed star - a black-hole [pt

  13. All-organic microelectromechanical systems integrating specific molecular recognition--a new generation of chemical sensors.

    Science.gov (United States)

    Ayela, Cédric; Dubourg, Georges; Pellet, Claude; Haupt, Karsten

    2014-09-03

    Cantilever-type all-organic microelectromechanical systems based on molecularly imprinted polymers for specific analyte recognition are used as chemical sensors. They are produced by a simple spray-coating-shadow-masking process. Analyte binding to the cantilever generates a measurable change in its resonance frequency. This allows label-free detection by direct mass sensing of low-molecular-weight analytes at nanomolar concentrations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Practising verbal maritime communication with computer dialogue systems using automatic speech recognition (My Practice session)

    OpenAIRE

    John, Peter; Wellmann, J.; Appell, J.E.

    2016-01-01

    This My Practice session presents a novel online tool for practising verbal communication in a maritime setting. It is based on low-fi ChatBot simulation exercises which employ computer-based dialogue systems. The ChatBot exercises are equipped with an automatic speech recognition engine specifically designed for maritime communication. The speech input and output functionality enables learners to communicate with the computer freely and spontaneously. The exercises replicate real communicati...

  15. Rapid Mergers in a Mixed System of Black Holes and Neutron Stars

    Science.gov (United States)

    Tagawa, Hiromichi; Umemura, Masayuki

    Recently, it has been argued that r-process elements in galaxies primarily originate from the mergers of double neutron stars (NSs) and black hole (BH)-NS. However, there is a momentous problem that the merger timescale is estimated to be much longer than the production timescale of r-process elements inferred from metal poor stars in the Galactic halo. To solve this problem, we propose the rapid merger processes in gas-rich first-generation objects in a high redshift epoch. In such an era, it is expected that the dynamical friction by dense gas effectively promotes the merger of compact objects. To explore the possibility of mergers in a system composed of multiple NSs as well as BHs, we perform post Newtonian N-body simulations, incorporating the gas dynamical friction, the gas accretion, and the gravitational wave emission including the recoil kick. As a result, we find that NS-NS or NS-BH can merge within 10 Myr in first-generation objects. Furthermore, to satisfy the condition of the mass ejection of r-process elements, the gas accretion rate need to be lower than 0.1 Hoyle-Lyttleton accretion rate. These results imply that the mergers in early cosmic epochs may reconcile the conflict on the timescale of NS mergers.

  16. Phase diagram of a symmetric electron–hole bilayer system: a variational Monte Carlo study

    Science.gov (United States)

    Sharma, Rajesh O.; Saini, L. K.; Prasad Bahuguna, Bhagwati

    2018-05-01

    We study the phase diagram of a symmetric electron–hole bilayer system at absolute zero temperature and in zero magnetic field within the quantum Monte Carlo approach. In particular, we conduct variational Monte Carlo simulations for various phases, i.e. the paramagnetic fluid phase, the ferromagnetic fluid phase, the anti-ferromagnetic Wigner crystal phase, the ferromagnetic Wigner crystal phase and the excitonic phase, to estimate the ground-state energy at different values of in-layer density and inter-layer spacing. Slater–Jastrow style trial wave functions, with single-particle orbitals appropriate for different phases, are used to construct the phase diagram in the (r s , d) plane by finding the relative stability of trial wave functions. At very small layer separations, we find that the fluid phases are stable, with the paramagnetic fluid phase being particularly stable at and the ferromagnetic fluid phase being particularly stable at . As the layer spacing increases, we first find that there is a phase transition from the ferromagnetic fluid phase to the ferromagnetic Wigner crystal phase when d reaches 0.4 a.u. at r s   =  20, and before there is a return to the ferromagnetic fluid phase when d approaches 1 a.u. However, for r s   Wigner crystal is stable over the considered range of r s and d. We also find that as r s increases, the critical layer separations for Wigner crystallization increase.

  17. Momentum distributions for two-electron systems: electron correlation and the Coulomb hole

    International Nuclear Information System (INIS)

    Banyard, K.E.; Reed, C.E.

    1978-01-01

    By evaluating the distribution function f(p 12 ), where p 12 ) in momentum space can be investigated. difference[p 1 - p 2 ] the concept of a Coulomb hole Δf(p 12 ) in momentum space can be investigated. Results are presented for the isoelectronic systems H - , He and Li + . The electron correlation within each CI wavefunction was analysed into its radial and angular components so that the structure and composition of Δf(p 12 ) could be assessed. The two-particle momentum radial density distribution and several two-particle expectation quantities are also examined. The present findings indicate, that in momentum space, the radial components of correlation produce effects characteristic of total correlation in position space whereas, by contrast, angular correlation creates an opposite effect. Thus the shape and formation of Δf(p 12 ) proves to be considerably more complex than that found for its counterpart in position space. The results also reveal a noticeable change in the relative importance of the components of correlation as the momentum increases. (author)

  18. 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.

  19. Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

    Science.gov (United States)

    Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

    2018-04-01

    To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

  20. 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.

  1. 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...

  2. Evaluating a voice recognition system: finding the right product for your department.

    Science.gov (United States)

    Freeh, M; Dewey, M; Brigham, L

    2001-06-01

    The Department of Radiology at the University of Utah Health Sciences Center has been in the process of transitioning from the traditional film-based department to a digital imaging department for the past 2 years. The department is now transitioning from the traditional method of dictating reports (dictation by radiologist to transcription to review and signing by radiologist) to a voice recognition system. The transition to digital operations will not be complete until we have the ability to directly interface the dictation process with the image review process. Voice recognition technology has advanced to the level where it can and should be an integral part of the new way of working in radiology and is an integral part of an efficient digital imaging department. The transition to voice recognition requires the task of identifying the product and the company that will best meet a department's needs. This report introduces the methods we used to evaluate the vendors and the products available as we made our purchasing decision. We discuss our evaluation method and provide a checklist that can be used by other departments to assist with their evaluation process. The criteria used in the evaluation process fall into the following major categories: user operations, technical infrastructure, medical dictionary, system interfaces, service support, cost, and company strength. Conclusions drawn from our evaluation process will be detailed, with the intention being to shorten the process for others as they embark on a similar venture. As more and more organizations investigate the many products and services that are now being offered to enhance the operations of a radiology department, it becomes increasingly important that solid methods are used to most effectively evaluate the new products. This report should help others complete the task of evaluating a voice recognition system and may be adaptable to other products as well.

  3. From binary black hole simulation to triple black hole simulation

    International Nuclear Information System (INIS)

    Bai Shan; Cao Zhoujian; Han, Wen-Biao; Lin, Chun-Yu; Yo, Hwei-Jang; Yu, Jui-Ping

    2011-01-01

    Black hole systems are among the most promising sources for a gravitational wave detection project. Now, China is planning to construct a space-based laser interferometric detector as a follow-on mission of LISA in the near future. Aiming to provide some theoretical support to this detection project on the numerical relativity side, we focus on black hole systems simulation in this work. Considering the globular galaxy, multiple black hole systems also likely to exist in our universe and play a role as a source for the gravitational wave detector we are considering. We will give a progress report in this paper on our black hole system simulation. More specifically, we will present triple black hole simulation together with binary black hole simulation. On triple black hole simulations, one novel perturbational method is proposed.

  4. 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.

  5. IoT-Based Image Recognition System for Smart Home-Delivered Meal Services

    Directory of Open Access Journals (Sweden)

    Hsiao-Ting Tseng

    2017-07-01

    Full Text Available Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.

  6. 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.

  7. 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.

  8. 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.

  9. Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

    Science.gov (United States)

    Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

    2014-01-01

    For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

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

    International Nuclear Information System (INIS)

    Zeng Hui; Li Qiang; Gu Yu

    2016-01-01

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

  11. 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.

  12. Single-Walled Carbon Nano tubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

    International Nuclear Information System (INIS)

    Upadhyayula, V.K.K

    2008-01-01

    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 x108 and 2 x108 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.

  13. High-emulation mask recognition with high-resolution hyperspectral video capture system

    Science.gov (United States)

    Feng, Jiao; Fang, Xiaojing; Li, Shoufeng; Wang, Yongjin

    2014-11-01

    We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. Two separate outflows in the dual supermassive black hole system NGC 6240.

    Science.gov (United States)

    Müller-Sánchez, F; Nevin, R; Comerford, J M; Davies, R I; Privon, G C; Treister, E

    2018-04-01

    Theoretical models and numerical simulations have established a framework of galaxy evolution in which galaxies merge and create dual supermassive black holes (with separations of one to ten kiloparsecs), which eventually sink into the centre of the merger remnant, emit gravitational waves and coalesce. The merger also triggers star formation and supermassive black hole growth, and gas outflows regulate the stellar content 1-3 . Although this theoretical picture is supported by recent observations of starburst-driven and supermassive black hole-driven outflows 4-6 , it remains unclear how these outflows interact with the interstellar medium. Furthermore, the relative contributions of star formation and black hole activity to galactic feedback remain unknown 7-9 . Here we report observations of dual outflows in the central region of the prototypical merger NGC 6240. We find a black-hole-driven outflow of [O III] to the northeast and a starburst-driven outflow of Hα to the northwest. The orientations and positions of the outflows allow us to isolate them spatially and study their properties independently. We estimate mass outflow rates of 10 and 75 solar masses per year for the Hα bubble and the [O III] cone, respectively. Their combined mass outflow is comparable to the star formation rate 10 , suggesting that negative feedback on star formation is occurring.

  20. 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.

  1. Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

    Science.gov (United States)

    Lhamon, Michael Earl

    A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

  2. An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

    Science.gov (United States)

    Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

    2018-04-01

    Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

  3. 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.

  4. Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

    Science.gov (United States)

    Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

    2017-01-01

    In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

  5. Energy flux through the horizon in the black hole-domain wall systems

    International Nuclear Information System (INIS)

    Stojkovic, Dejan

    2004-01-01

    We study various configurations in which a domain wall (or cosmic string), described by the Nambu-Goto action, is embedded in a background space-time of a black hole in (3+1) and higher dimensional models. We calculate energy fluxes through the black hole horizon. In the simplest case, when a static domain wall enters the horizon of a static black hole perpendicularly, the energy flux is zero. In more complicated situations, where parameters which describe the domain wall surface are time and position dependent, the flux is non-vanishing is principle. These results are of importance in various conventional cosmological models which accommodate the existence of domain walls and strings and also in brane world scenarios. (author)

  6. A low-cost machine vision system for the recognition and sorting of small parts

    Science.gov (United States)

    Barea, Gustavo; Surgenor, Brian W.; Chauhan, Vedang; Joshi, Keyur D.

    2018-04-01

    An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.

  7. Phase diagram of a symmetric electron-hole bilayer system: a variational Monte Carlo study.

    Science.gov (United States)

    Sharma, Rajesh O; Saini, L K; Bahuguna, Bhagwati Prasad

    2018-05-10

    We study the phase diagram of a symmetric electron-hole bilayer system at absolute zero temperature and in zero magnetic field within the quantum Monte Carlo approach. In particular, we conduct variational Monte Carlo simulations for various phases, i.e. the paramagnetic fluid phase, the ferromagnetic fluid phase, the anti-ferromagnetic Wigner crystal phase, the ferromagnetic Wigner crystal phase and the excitonic phase, to estimate the ground-state energy at different values of in-layer density and inter-layer spacing. Slater-Jastrow style trial wave functions, with single-particle orbitals appropriate for different phases, are used to construct the phase diagram in the (r s , d) plane by finding the relative stability of trial wave functions. At very small layer separations, we find that the fluid phases are stable, with the paramagnetic fluid phase being particularly stable at [Formula: see text] and the ferromagnetic fluid phase being particularly stable at [Formula: see text]. As the layer spacing increases, we first find that there is a phase transition from the ferromagnetic fluid phase to the ferromagnetic Wigner crystal phase when d reaches 0.4 a.u. at r s   =  20, and before there is a return to the ferromagnetic fluid phase when d approaches 1 a.u. However, for r s   Wigner crystal is stable over the considered range of r s and d. We also find that as r s increases, the critical layer separations for Wigner crystallization increase.

  8. Gamma emission tomosynthesis based on an automated slant hole collimation system

    Science.gov (United States)

    Pellegrini, R.; Pani, R.; Cinti, M. N.; Longo, M.; Lo Meo, S.; Viviano, M.

    2015-03-01

    The imaging capabilities of radioisotope molecular imaging systems are limited by their ring geometry and by the object-to-detector distance, which impairs spatial resolution, efficiency and image quality. These detection capabilities could be enhanced by performing acquisitions with dedicated gamma cameras placed in close proximity to the object that has to be examined. The main aim of this work is to develop a compact camera suitable for detecting small and low-contrast lesions, with a higher detection efficiency than conventional SPECT, through a gamma emission tomosynthesis method. In this contribution a prototype of a new automated slant hole collimator, coupled to a small Field of View (FoV) gamma camera, is presented. The proposed device is able to acquire planar projection images at different angles without rotating around the patient body; these projection images are then three-dimensional reconstructed. Therefore, in order to perform the volumetric reconstruction of the studied object, the traditional Back Projection (BP) reconstruction is compared with the Shift And Add (SAA) method. In order to verify the effectiveness of the technique and to test the image reconstruction algorithms, a Monte Carlo simulation, based on the GEANT4 code, was implemented. The method was also validated by a set of experimental measurements. The discussed device is designed to work in patient proximity for detecting lesions placed at a distances ranged from 0 to 8 cm, thus allowing few millimeters planar resolutions and sagittal resolution of about 2 cm. The new collimation method implies high-resolution capabilities demonstrated by reconstructing the projection images through the BP and the SAA methods. The latter is simpler than BP and produces comparable spatial resolutions with respect to the traditional tomographic method, while preserving the image counts.

  9. 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.

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

    Science.gov (United States)

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    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.

  11. A neural network based artificial vision system for licence plate recognition.

    Science.gov (United States)

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

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

    Directory of Open Access Journals (Sweden)

    Hongqiang Li

    2016-10-01

    Full Text Available 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.

  13. 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

  14. Communication: Density functional theory model for multi-reference systems based on the exact-exchange hole normalization.

    Science.gov (United States)

    Laqua, Henryk; Kussmann, Jörg; Ochsenfeld, Christian

    2018-03-28

    The correct description of multi-reference electronic ground states within Kohn-Sham density functional theory (DFT) requires an ensemble-state representation, employing fractionally occupied orbitals. However, the use of fractional orbital occupation leads to non-normalized exact-exchange holes, resulting in large fractional-spin errors for conventional approximative density functionals. In this communication, we present a simple approach to directly include the exact-exchange-hole normalization into DFT. Compared to conventional functionals, our model strongly improves the description for multi-reference systems, while preserving the accuracy in the single-reference case. We analyze the performance of our proposed method at the example of spin-averaged atoms and spin-restricted bond dissociation energy surfaces.

  15. Communication: Density functional theory model for multi-reference systems based on the exact-exchange hole normalization

    Science.gov (United States)

    Laqua, Henryk; Kussmann, Jörg; Ochsenfeld, Christian

    2018-03-01

    The correct description of multi-reference electronic ground states within Kohn-Sham density functional theory (DFT) requires an ensemble-state representation, employing fractionally occupied orbitals. However, the use of fractional orbital occupation leads to non-normalized exact-exchange holes, resulting in large fractional-spin errors for conventional approximative density functionals. In this communication, we present a simple approach to directly include the exact-exchange-hole normalization into DFT. Compared to conventional functionals, our model strongly improves the description for multi-reference systems, while preserving the accuracy in the single-reference case. We analyze the performance of our proposed method at the example of spin-averaged atoms and spin-restricted bond dissociation energy surfaces.

  16. Computerized literature reference system: use of an optical scanner and optical character recognition software.

    Science.gov (United States)

    Lossef, S V; Schwartz, L H

    1990-09-01

    A computerized reference system for radiology journal articles was developed by using an IBM-compatible personal computer with a hand-held optical scanner and optical character recognition software. This allows direct entry of scanned text from printed material into word processing or data-base files. Additionally, line diagrams and photographs of radiographs can be incorporated into these files. A text search and retrieval software program enables rapid searching for keywords in scanned documents. The hand scanner and software programs are commercially available, relatively inexpensive, and easily used. This permits construction of a personalized radiology literature file of readily accessible text and images requiring minimal typing or keystroke entry.

  17. 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

  18. 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.

  19. Universality in the relaxation dynamics of the composed black-hole-charged-massive-scalar-field system: The role of quantum Schwinger discharge

    Directory of Open Access Journals (Sweden)

    Shahar Hod

    2015-07-01

    Full Text Available The quasinormal resonance spectrum {ωn(μ,q,M,Q}n=0n=∞ of charged massive scalar fields in the charged Reissner–Nordström black-hole spacetime is studied analytically in the large-coupling regime qQ≫Mμ (here {μ,q} are respectively the mass and charge coupling constant of the field, and {M,Q} are respectively the mass and electric charge of the black hole. This physical system provides a striking illustration for the validity of the universal relaxation bound τ×T≥ħ/π in black-hole physics (here τ≡1/ℑω0 is the characteristic relaxation time of the composed black-hole-scalar-field system, and T is the Bekenstein–Hawking temperature of the black hole. In particular, it is shown that the relaxation dynamics of charged massive scalar fields in the charged Reissner–Nordström black-hole spacetime may saturate this quantum time-times-temperature inequality. Interestingly, we prove that potential violations of the bound by light scalar fields are excluded by the Schwinger-type pair-production mechanism (a vacuum polarization effect, a quantum phenomenon which restricts the physical parameters of the composed black-hole-charged-field system to the regime qQ≪M2μ2/ħ.

  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. Applied learning-based color tone mapping for face recognition in video surveillance system

    Science.gov (United States)

    Yew, Chuu Tian; Suandi, Shahrel Azmin

    2012-04-01

    In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

  2. A Presence-Based Context-Aware Chronic Stress Recognition System

    Directory of Open Access Journals (Sweden)

    Andrej Kos

    2012-11-01

    Full Text Available Stressors encountered in daily life may play an important role in personal well-being. Chronic stress can have a serious long-term impact on our physical as well as our psychological health, due to ongoing increased levels of the chemicals released in the ‘fight or flight’ response. The currently available stress assessment methods are usually not suitable for daily chronic stress measurement. The paper presents a context-aware chronic stress recognition system that addresses this problem. The proposed system obtains contextual data from various mobile sensors and other external sources in order to calculate the impact of ongoing stress. By identifying and visualizing ongoing stress situations of an individual user, he/she is able to modify his/her behavior in order to successfully avoid them. Clinical evaluation of the proposed methodology has been made in parallel by using electrodermal activity sensor. To the best of our knowledge, the system presented herein is the first one that enables recognition of chronic stress situations on the basis of user context.

  3. 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.

  4. 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.

  5. Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

    Science.gov (United States)

    Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

    2017-03-01

    Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

  6. Statistical mechanics of black holes

    International Nuclear Information System (INIS)

    Harms, B.; Leblanc, Y.

    1992-01-01

    We analyze the statistical mechanics of a gas of neutral and charged black holes. The microcanonical ensemble is the only possible approach to this system, and the equilibrium configuration is the one for which most of the energy is carried by a single black hole. Schwarzschild black holes are found to obey the statistical bootstrap condition. In all cases, the microcanonical temperature is identical to the Hawking temperature of the most massive black hole in the gas. U(1) charges in general break the bootstrap property. The problems of black-hole decay and of quantum coherence are also addressed

  7. DISCOVERY OF X-RAY EMISSION FROM THE FIRST Be/BLACK HOLE SYSTEM

    Energy Technology Data Exchange (ETDEWEB)

    Munar-Adrover, P.; Paredes, J. M.; Ribó, M. [Departament d' Astronomia i Meteorologia, Institut de Ciències del Cosmos, Universitat de Barcelona, IEEC-UB, Martí i Franquès 1, E-08028 Barcelona (Spain); Iwasawa, K. [ICREA, Institut de Ciències del Cosmos, Universitat de Barcelona, IEEC-UB, Martí i Franquès 1, E-08028 Barcelona (Spain); Zabalza, V. [Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH (United Kingdom); Casares, J. [Instituto de Astrofísica de Canarias, E-38200 La Laguna, Tenerife (Spain)

    2014-05-10

    MWC 656 (=HD 215227) was recently discovered to be the first binary system composed of a Be star and a black hole (BH). We observed it with XMM-Newton, and detected a faint X-ray source compatible with the position of the optical star, thus proving it to be the first Be/BH X-ray binary. The spectrum analysis requires a model fit with two components, a blackbody plus a power law, with k{sub B}T=0.07{sub −0.03}{sup +0.04} keV and a photon index Γ = 1.0 ± 0.8, respectively. The non-thermal component dominates above ≅0.8 keV. The obtained total flux is F(0.3-5.5 keV)=(4.6{sub −1.1}{sup +1.3})×10{sup −14} erg cm{sup –2} s{sup –1}. At a distance of 2.6 ± 0.6 kpc the total flux translates into a luminosity L {sub X} = (3.7 ± 1.7) × 10{sup 31} erg s{sup –1}. Considering the estimated range of BH masses to be 3.8-6.9 M {sub ☉}, this luminosity represents (6.7 ± 4.4) × 10{sup –8} L {sub Edd}, which is typical of stellar-mass BHs in quiescence. We discuss the origin of the two spectral components: the thermal component is associated with the hot wind of the Be star, whereas the power-law component is associated with emission from the vicinity of the BH. We also find that the position of MWC 656 in the radio versus X-ray luminosity diagram may be consistent with the radio/X-ray correlation observed in BH low-mass X-ray binaries. This suggests that this correlation might also be valid for BH high-mass X-ray binaries (HMXBs) with X-ray luminosities down to ∼10{sup –8} L {sub Edd}. MWC 656 will allow the accretion processes and the accretion/ejection coupling at very low luminosities for BH HMXBs to be studied.

  8. 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...

  9. Magnonic black holes

    OpenAIRE

    Roldán-Molina, A.; Nunez, A.S.; Duine, R. A.

    2017-01-01

    We show that the interaction between spin-polarized current and magnetization dynamics can be used to implement black-hole and white-hole horizons for magnons - the quanta of oscillations in the magnetization direction in magnets. We consider three different systems: easy-plane ferromagnetic metals, isotropic antiferromagnetic metals, and easy-plane magnetic insulators. Based on available experimental data, we estimate that the Hawking temperature can be as large as 1 K. We comment on the imp...

  10. An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

    Science.gov (United States)

    Maddox, Brian G.; Swadley, Casey L.

    2002-01-01

    Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

  11. 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.

  12. Quantum diffusion in two-dimensional random systems with particle–hole symmetry

    International Nuclear Information System (INIS)

    Ziegler, K

    2012-01-01

    We study the scattering dynamics of an n-component spinor wavefunction in a random environment on a two-dimensional lattice. If the particle–hole symmetry of the Hamiltonian is spontaneously broken the dynamics of the quantum particles becomes diffusive on large scales. The latter is described by a non-interacting Grassmann field, indicating a special kind of asymptotic freedom on large scales in d = 2. (paper)

  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. Unmodeled search for black hole binary systems in the NINJA project

    International Nuclear Information System (INIS)

    Cadonati, Laura; Fischetti, Sebastian; Mohapatra, Satyanarayan R P; Chatterji, Shourov; Guidi, Gianluca; Sturani, Riccardo; Vicere, Andrea

    2009-01-01

    The gravitational-wave signature from binary black hole coalescences is an important target for ground-based interferometric detectors such as LIGO and Virgo. The Numerical INJection Analysis (NINJA) project brought together the numerical relativity and gravitational wave data analysis communities, with the goal to optimize the detectability of these events. In its first instantiation, the NINJA project produced a simulated data set with numerical waveforms from binary black hole coalescences of various morphologies (spin, mass ratio, initial conditions), superimposed to Gaussian colored noise at the design sensitivity for initial LIGO and Virgo. We analyzed the NINJA simulated data set with the Q-pipeline algorithm, designed for the all-sky detection of gravitational-wave bursts with minimal assumptions on the shape of the waveform. The algorithm filters the data with a bank of sine-Gaussians, sinusoids with Gaussian envelope, to identify significant excess power in the time-frequency domain. We compared the performance of this burst search algorithm with lalapps r ing, which match-filters data with a bank of ring-down templates to specifically target the final stage of a coalescence of black holes. A comparison of the output of the two algorithms on NINJA data in a single detector analysis yielded qualitatively consistent results; however, due to the low simulation statistics in the first NINJA project, it is premature to draw quantitative conclusions at this stage, and further studies with higher statistics and real detector noise will be needed.

  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. Recognition and management of idiopathic systemic capillary leak syndrome: an evidence-based review.

    Science.gov (United States)

    Baloch, Noor Ul-Ain; Bikak, Marvi; Rehman, Abdul; Rahman, Omar

    2018-05-01

    Idiopathic systemic capillary leak syndrome (SCLS) is a unique disorder characterized by episodes of massive systemic leak of intravascular fluid leading to volume depletion and shock. A typical attack of SCLS consists of prodromal, leak and post-leak phases. Complications, such as compartment syndrome and pulmonary edema, usually develop during the leak and post-leak phases respectively. Judicious intravenous hydration and early use of vasopressors is the cornerstone of management in such cases. Areas covered: The purpose of the present review is to provide an up-to-date, evidence-based review of our understanding of SCLS and its management in the light of currently available evidence. Idiopathic SCLS was first described in 1960 and, since then, more than 250 cases have been reported. A large number of cases have been reported over the past one decade, most likely due to improved recognition. In the acute care setting, most patients with SCLS are managed as per the Surviving Sepsis guidelines and receive aggressive volume resuscitation - which is not the optimal management strategy for such patients. There is a need to raise awareness amongst physicians and clinicians in order to improve recognition of this disorder and ensure its appropriate management.

  18. A Vehicle Steering Recognition System Based on Low-Cost Smartphone Sensors

    Directory of Open Access Journals (Sweden)

    Xinhua Liu

    2017-03-01

    Full Text Available Recognizing how a vehicle is steered and then alerting drivers in real time is of utmost importance to the vehicle and driver’s safety, since fatal accidents are often caused by dangerous vehicle maneuvers, such as rapid turns, fast lane-changes, etc. Existing solutions using video or in-vehicle sensors have been employed to identify dangerous vehicle maneuvers, but these methods are subject to the effects of the environmental elements or the hardware is very costly. In the mobile computing era, smartphones have become key tools to develop innovative mobile context-aware systems. In this paper, we present a recognition system for dangerous vehicle steering based on the low-cost sensors found in a smartphone: i.e., the gyroscope and the accelerometer. To identify vehicle steering maneuvers, we focus on the vehicle’s angular velocity, which is characterized by gyroscope data from a smartphone mounted in the vehicle. Three steering maneuvers including turns, lane-changes and U-turns are defined, and a vehicle angular velocity matching algorithm based on Fast Dynamic Time Warping (FastDTW is adopted to recognize the vehicle steering. The results of extensive experiments show that the average accuracy rate of the presented recognition reaches 95%, which implies that the proposed smartphone-based method is suitable for recognizing dangerous vehicle steering maneuvers.

  19. Material recognition with the Medipix photon counting colour X-ray system

    Energy Technology Data Exchange (ETDEWEB)

    Norlin, B. E-mail: borje.norlin@mh.se; Manuilskiy, A.; Nilsson, H.-E.; Froejdh, C

    2004-09-21

    An energy sensitive imaging system like Medipix1 has proved to be promising in distinguishing different materials in an X-ray image of an object. We propose a general method utilising X-ray energy information for material recognition. For objects where the thickness of the materials is unknown, a convenient material parameter to identify is K={alpha}{sub 1}/{alpha}{sub 2}, which is the ratio of the logarithms of the measured transmissions ln(t{sub 1})/ln(t{sub 2}). If a database of the parameter K for different materials and energies is created, this method can be used for material recognition independent of the thickness of the materials. Series of images of an object consisting of aluminium and silicon were taken with different energy thresholds. The X-ray absorption for silicon and aluminium is very similar for the range 40-60 keV and only differs for lower energies. The results show that it is possible to distinguish between aluminium and silicon on images achieved by Medipix1 using a standard dental source. By decreasing the spatial resolution a better contrast between the materials was achieved. The resolution of contrasts shown by the histograms was close to the limit of the system due to the statistical noise of the signal.

  20. Fluorescent sensor systems based on nanostructured polymeric membranes for selective recognition of Aflatoxin B1.

    Science.gov (United States)

    Sergeyeva, Tetyana; Yarynka, Daria; Piletska, Elena; Lynnik, Rostyslav; Zaporozhets, Olga; Brovko, Oleksandr; Piletsky, Sergey; El'skaya, Anna

    2017-12-01

    Nanostructured polymeric membranes for selective recognition of aflatoxin B1 were synthesized in situ and used as highly sensitive recognition elements in the developed fluorescent sensor. Artificial binding sites capable of selective recognition of aflatoxin B1 were formed in the structure of the polymeric membranes using the method of molecular imprinting. A composition of molecularly imprinted polymer (MIP) membranes was optimized using the method of computational modeling. The MIP membranes were synthesized using the non-toxic close structural analogue of aflatoxin B1, ethyl-2-oxocyclopentanecarboxylate as a dummy template. The MIP membranes with the optimized composition demonstrated extremely high selectivity towards aflatoxin B1 (AFB1). Negligible binding of close structural analogues of AFB1 - aflatoxins B2 (AFB2), aflatoxin G2 (AFG2), and ochratoxin A (OTA) was demonstrated. Binding of AFB1 by the MIP membranes was investigated as a function of both type and concentration of the functional monomer in the initial monomer composition used for the membranes' synthesis, as well as sample composition. The conditions of the solid-phase extraction of the mycotoxin using the MIP membrane as a stationary phase (pH, ionic strength, buffer concentration, volume of the solution, ratio between water and organic solvent, filtration rate) were optimized. The fluorescent sensor system based on the optimized MIP membranes provided a possibility of AFB1 detection within the range 14-500ngmL -1 demonstrating detection limit (3Ϭ) of 14ngmL -1 . The developed technique was successfully applied for the analysis of model solutions and waste waters from bread-making plants. Copyright © 2017 Elsevier B.V. All rights reserved.

  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 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. Template protection and its implementation in 3D face recognition systems

    Science.gov (United States)

    Zhou, Xuebing

    2007-04-01

    As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

  3. 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.

  4. An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Abdu Gumaei

    2018-01-01

    Full Text Available Multispectral palmprint recognition system (MPRS is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE and regularized extreme learning machine (RELM is proposed in this paper. The proposed approach is intended to make the recognition faster by reducing the number of palmprint features without degrading the accuracy of classifier. To achieve this objective, first, the region of interest (ROI from palmprint images is extracted by David Zhang’s method. Second, an efficient normalized Gist (NGist descriptor is used for palmprint feature extraction. Then, the dimensionality of extracted features is reduced using optimized AE. Finally, the reduced features are fed to the RELM for classification. A comprehensive set of experiments are conducted on the benchmark MS-PolyU dataset. The results were significantly high compared to the state-of-the-art approaches, and the robustness and efficiency of the proposed approach are revealed.

  5. Application of Business Process Management to drive the deployment of a speech recognition system in a healthcare organization.

    Science.gov (United States)

    González Sánchez, María José; Framiñán Torres, José Manuel; Parra Calderón, Carlos Luis; Del Río Ortega, Juan Antonio; Vigil Martín, Eduardo; Nieto Cervera, Jaime

    2008-01-01

    We present a methodology based on Business Process Management to guide the development of a speech recognition system in a hospital in Spain. The methodology eases the deployment of the system by 1) involving the clinical staff in the process, 2) providing the IT professionals with a description of the process and its requirements, 3) assessing advantages and disadvantages of the speech recognition system, as well as its impact in the organisation, and 4) help reorganising the healthcare process before implementing the new technology in order to identify how it can better contribute to the overall objective of the organisation.

  6. Brane holes

    International Nuclear Information System (INIS)

    Frolov, Valeri P.; Mukohyama, Shinji

    2011-01-01

    The aim of this paper is to demonstrate that in models with large extra dimensions under special conditions one can extract information from the interior of 4D black holes. For this purpose we study an induced geometry on a test brane in the background of a higher-dimensional static black string or a black brane. We show that, at the intersection surface of the test brane and the bulk black string or brane, the induced metric has an event horizon, so that the test brane contains a black hole. We call it a brane hole. When the test brane moves with a constant velocity V with respect to the bulk black object, it also has a brane hole, but its gravitational radius r e is greater than the size of the bulk black string or brane r 0 by the factor (1-V 2 ) -1 . We show that bulk ''photon'' emitted in the region between r 0 and r e can meet the test brane again at a point outside r e . From the point of view of observers on the test brane, the events of emission and capture of the bulk photon are connected by a spacelike curve in the induced geometry. This shows an example in which extra dimensions can be used to extract information from the interior of a lower-dimensional black object. Instead of the bulk black string or brane, one can also consider a bulk geometry without a horizon. We show that nevertheless the induced geometry on the moving test brane can include a brane hole. In such a case the extra dimensions can be used to extract information from the complete region of the brane-hole interior. We discuss thermodynamic properties of brane holes and interesting questions which arise when such an extra-dimensional channel for the information mining exists.

  7. The neuro-immunological interface in an evolutionary perspective: the dynamic relationship between effector and recognition systems.

    Science.gov (United States)

    Ottaviani, E; Valensin, S; Franceschi, C

    1998-04-16

    The evolutionary perspective indicates that an immune-neuroendocrine effector system integrating innate immunity, stress and inflammation is present in invertebrates. This defense network, centered on the macrophage and exerting primitive and highly promiscuous recognition units, is very effective, ancestral and appears to have been conserved throughout evolution from invertebrates to higher vertebrates. It would seem that there was a "big bang" in the recognition system of lower vertebrates, and T and B cell repertoires, MHC and antibodies suddenly appeared. We argue that this phenomenon is the counterpart of the increasing complexity of the internal circuitry and recognition units in the effector system. The immediate consequences were a progressive enlargement of the pathogen repertoire and new problems regarding self/not-self discrimination. Probably not by chance, a new organ appeared, capable of purging cells able of excessive self recognition. This organ, the thymus, appears to be the result of a well known evolutionary strategy of re-using pre-existing material (neuroendocrine cells and mediators constituting the thymic microenvironment). This bricolage at an organ level is similar to the effect we have already described at the level of molecules and functions of the defense network, and has a general counterpart at genetic level. Thus, in vertebrates, the conserved immune-neuroendocrine effector system remains of fundamental importance in defense against pathogens, while its efficiency has increased through synergy with the new, clonotipical recognition repertoire.

  8. Orbit classification in an equal-mass non-spinning binary black hole pseudo-Newtonian system

    Science.gov (United States)

    Zotos, Euaggelos E.; Dubeibe, F. L.; González, Guillermo A.

    2018-04-01

    The dynamics of a test particle in a non-spinning binary black hole system of equal masses is numerically investigated. The binary system is modeled in the context of the pseudo-Newtonian circular restricted three-body problem, such that the primaries are separated by a fixed distance and move in a circular orbit around each other. In particular, the Paczyński-Wiita potential is used for describing the gravitational field of the two non-Newtonian primaries. The orbital properties of the test particle are determined through the classification of the initial conditions of the orbits, using several values of the Jacobi constant, in the Hill's regions of possible motion. The initial conditions are classified into three main categories: (i) bounded, (ii) escaping and (iii) displaying close encounters. Using the smaller alignment index (SALI) chaos indicator, we further classify bounded orbits into regular, sticky or chaotic. To gain a complete view of the dynamics of the system, we define grids of initial conditions on different types of two-dimensional planes. The orbital structure of the configuration plane, along with the corresponding distributions of the escape and collision/close encounter times, allow us to observe the transition from the classical Newtonian to the pseudo-Newtonian regime. Our numerical results reveal a strong dependence of the properties of the considered basins with the Jacobi constant as well as with the Schwarzschild radius of the black holes.

  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. 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.

  11. Toward a multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition

    International Nuclear Information System (INIS)

    King, D; Lyons, W B; Flanagan, C; Lewis, E

    2005-01-01

    An optical fibre sensor capable of detecting various concentrations of ethanol in water supplies is reported. The sensor is based on a U-bend sensor configuration and is incorporated into a 170-metre length of silica cladding silica core optical fibre. The sensor is interrogated using Optical Time Domain Reflectometry (OTDR) and it is proposed to apply artificial neural network (ANN) pattern recognition techniques to the resulting OTDR signals to accurately classify the sensor test conditions. It is also proposed that additional U-bend configuration sensors will be added to the fibre measurement length, in order to implement a multipoint optical fibre sensor system

  12. 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…

  13. Towards evidence-based, quality-controlled health promotion: the Dutch recognition system for health promotion interventions.

    NARCIS (Netherlands)

    Brug, J.; Dale, D. van; Lanting, L.; Kremers, S.; Veenhof, C.; Leurs, M.; Yperen, T. van; Kok, G.

    2010-01-01

    Registration or recognition systems for best-practice health promotion interventions may contribute to better quality assurance and control in health promotion practice. In the Netherlands, such a system has been developed and is being implemented aiming to provide policy makers and professionals

  14. Computer system for structure recognition of polyatomic molecules by i. r. , n. m. r. , u. v. and m. s. methods

    Energy Technology Data Exchange (ETDEWEB)

    Gribov, L A; Elyashberg, M E; Serov, V V [USSR Academy of Sciences, Moscow (USSR). V.I. Vernadsky Institute of Geochemistry and Analytical Chemistry

    1977-12-15

    A system of algorithms and programs for the recognition of the structures of polyatomic molecules by means of i.r., n.m.r., u.v. and mass spectra is described. Examples of structures identified are cited. The results are promising and suggest that the system could be used for the identification of complex organic compounds.

  15. CL-L1 and CL-K1 and other complement associated pattern recognition molecules in systemic lupus erythematosus

    DEFF Research Database (Denmark)

    Troldborg, Anne; Thiel, Steffen; Jensen, Lisbeth

    2015-01-01

    The objective of this study was to explore the involvement of collectin liver 1 (CL-L1) and collectin kidney 1 (CL-K1) and other pattern recognition molecules (PRMs) of the lectin pathway of the complement system in a cross-sectional cohort of systemic lupus erythematosus (SLE) patients...

  16. New methods to benchmark simulations of accreting black holes systems against observations

    Science.gov (United States)

    Markoff, Sera; Chatterjee, Koushik; Liska, Matthew; Tchekhovskoy, Alexander; Hesp, Casper; Ceccobello, Chiara; Russell, Thomas

    2017-08-01

    The field of black hole accretion has been significantly advanced by the use of complex ideal general relativistic magnetohydrodynamics (GRMHD) codes, now capable of simulating scales from the event horizon out to ~10^5 gravitational radii at high resolution. The challenge remains how to test these simulations against data, because the self-consistent treatment of radiation is still in its early days, and is complicated by dependence on non-ideal/microphysical processes not yet included in the codes. On the other extreme, a variety of phenomenological models (disk, corona, jet, wind) can well-describe spectra or variability signatures in a particular waveband, although often not both. To bring these two methodologies together, we need robust observational “benchmarks” that can be identified and studied in simulations. I will focus on one example of such a benchmark, from recent observational campaigns on black holes across the mass scale: the jet break. I will describe new work attempting to understand what drives this feature by searching for regions that share similar trends in terms of dependence on accretion power or magnetisation. Such methods can allow early tests of simulation assumptions and help pinpoint which regions will dominate the light production, well before full radiative processes are incorporated, and will help guide the interpretation of, e.g. Event Horizon Telescope data.

  17. Black Hole Area Quantization rule from Black Hole Mass Fluctuations

    OpenAIRE

    Schiffer, Marcelo

    2016-01-01

    We calculate the black hole mass distribution function that follows from the random emission of quanta by Hawking radiation and with this function we calculate the black hole mass fluctuation. From a complete different perspective we regard the black hole as quantum mechanical system with a quantized event horizon area and transition probabilities among the various energy levels and then calculate the mass dispersion. It turns out that there is a perfect agreement between the statistical and ...

  18. 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.

  19. 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.

  20. Extraction Of Audio Features For Emotion Recognition System Based On Music

    Directory of Open Access Journals (Sweden)

    Kee Moe Han

    2015-08-01

    Full Text Available Music is the combination of melody linguistic information and the vocalists emotion. Since music is a work of art analyzing emotion in music by computer is a difficult task. Many approaches have been developed to detect the emotions included in music but the results are not satisfactory because emotion is very complex. In this paper the evaluations of audio features from the music files are presented. The extracted features are used to classify the different emotion classes of the vocalists. Musical features extraction is done by using Music Information Retrieval MIR tool box in this paper. The database of 100 music clips are used to classify the emotions perceived in music clips. Music may contain many emotions according to the vocalists mood such as happy sad nervous bored peace etc. In this paper the audio features related to the emotions of the vocalists are extracted to use in emotion recognition system based on music.

  1. 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

    2015-04-08

    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.

  2. Combining Users’ Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

    Directory of Open Access Journals (Sweden)

    Gorka Azkune

    2015-04-01

    Full Text Available 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.

  3. 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%.

  4. 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

  5. White holes and eternal black holes

    International Nuclear Information System (INIS)

    Hsu, Stephen D H

    2012-01-01

    We investigate isolated white holes surrounded by vacuum, which correspond to the time reversal of eternal black holes that do not evaporate. We show that isolated white holes produce quasi-thermal Hawking radiation. The time reversal of this radiation, incident on a black hole precursor, constitutes a special preparation that will cause the black hole to become eternal. (paper)

  6. A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

    Directory of Open Access Journals (Sweden)

    Ahmad Jalal

    2014-07-01

    Full Text Available Recent advancements in depth video sensors technologies have made human activity recognition (HAR realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

  7. A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments.

    Science.gov (United States)

    Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

    2014-07-02

    Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

  8. 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.

  9. Statistical black-hole thermodynamics

    International Nuclear Information System (INIS)

    Bekenstein, J.D.

    1975-01-01

    Traditional methods from statistical thermodynamics, with appropriate modifications, are used to study several problems in black-hole thermodynamics. Jaynes's maximum-uncertainty method for computing probabilities is used to show that the earlier-formulated generalized second law is respected in statistically averaged form in the process of spontaneous radiation by a Kerr black hole discovered by Hawking, and also in the case of a Schwarzschild hole immersed in a bath of black-body radiation, however cold. The generalized second law is used to motivate a maximum-entropy principle for determining the equilibrium probability distribution for a system containing a black hole. As an application we derive the distribution for the radiation in equilibrium with a Kerr hole (it is found to agree with what would be expected from Hawking's results) and the form of the associated distribution among Kerr black-hole solution states of definite mass. The same results are shown to follow from a statistical interpretation of the concept of black-hole entropy as the natural logarithm of the number of possible interior configurations that are compatible with the given exterior black-hole state. We also formulate a Jaynes-type maximum-uncertainty principle for black holes, and apply it to obtain the probability distribution among Kerr solution states for an isolated radiating Kerr hole

  10. Interaction-driven versus disorder-driven transport in ultra-dilute GaAs two-dimensional hole systems

    Science.gov (United States)

    Huang, Jian; Pfeiffer, L. N.; West, K. W.

    2012-02-01

    It is well-known that the insulating behavior in the two-dimensional metal-to-insulator transition demonstrates a finite temperature conduction via hopping. Recently, however, some very strongly interacting higher purity two-dimensional electron systems at temperatures T->0 demonstrate certain nonactivated insulating behaviors that are absent in more disordered systems. Through measuring in dark the T-dependence of the conductivity of ultra-high quality 2D holes with charge densities down to 7x10^8 cm-2, an approximate power-law behavior is identified. Moreover, for the lowest charge densities, the exponent exhibits a linearly decreasing density-dependence which suggests an interaction-driven nature. Such an electron state is fragile to even a slight increase of disorder which causes a crossover from nonactivated to activated conduction. The non-activated conduction may well be an universal interaction-driven signature of an electron state of strongly correlated (semiquantum) liquid.

  11. Nonactivated transport of ultradilute two-dimensional hole systems in GaAs field-effect transistors: Interaction versus disorder

    Science.gov (United States)

    Huang, Jian; Pfeiffer, L. N.; West, K. W.

    2012-01-01

    Very strongly interacting high-purity two-dimensional (2D) electron systems at temperatures T→0 demonstrate certain nonactivated insulating behaviors that are absent in more disordered systems. By measuring in dark the T dependence of the conductivity of ultrahigh-quality 2D holes with charge densities down to 7×108 cm-2, an approximate power-law behavior is identified. Moreover, the exponent exhibits a linearly decreasing density dependence which suggests an interaction-driven nature. Such an electron state is fragile to even a slight increase of disorder, which causes a crossover from nonactivated to activated conduction. The nonactivated conduction may well be a universal interaction-driven signature of an electron state of strongly correlated (semiquantum) liquid.

  12. 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.

  13. 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.

  14. 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.

  15. 24/7 security system: 60-FPS color EMCCD camera with integral human recognition

    Science.gov (United States)

    Vogelsong, T. L.; Boult, T. E.; Gardner, D. W.; Woodworth, R.; Johnson, R. C.; Heflin, B.

    2007-04-01

    An advanced surveillance/security system is being developed for unattended 24/7 image acquisition and automated detection, discrimination, and tracking of humans and vehicles. The low-light video camera incorporates an electron multiplying CCD sensor with a programmable on-chip gain of up to 1000:1, providing effective noise levels of less than 1 electron. The EMCCD camera operates in full color mode under sunlit and moonlit conditions, and monochrome under quarter-moonlight to overcast starlight illumination. Sixty frame per second operation and progressive scanning minimizes motion artifacts. The acquired image sequences are processed with FPGA-compatible real-time algorithms, to detect/localize/track targets and reject non-targets due to clutter under a broad range of illumination conditions and viewing angles. The object detectors that are used are trained from actual image data. Detectors have been developed and demonstrated for faces, upright humans, crawling humans, large animals, cars and trucks. Detection and tracking of targets too small for template-based detection is achieved. For face and vehicle targets the results of the detection are passed to secondary processing to extract recognition templates, which are then compared with a database for identification. When combined with pan-tilt-zoom (PTZ) optics, the resulting system provides a reliable wide-area 24/7 surveillance system that avoids the high life-cycle cost of infrared cameras and image intensifiers.

  16. Toward fast feature adaptation and localization for real-time face recognition systems

    NARCIS (Netherlands)

    Zuo, F.; With, de P.H.N.; Ebrahimi, T.; Sikora, T.

    2003-01-01

    In a home environment, video surveillance employing face detection and recognition is attractive for new applications. Facial feature (e.g. eyes and mouth) localization in the face is an essential task for face recognition because it constitutes an indispensable step for face geometry normalization.

  17. 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

    recognition: two deep architectures are presented and examined, which aim at suppressing channel effects and recovering speaker-discriminative information on back-ends trained on a small dataset. Experiments are carried out on the MOBIO SRE'13 database, which is a challenging and publicly available dataset...... 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....

  18. The influence of age, hearing, and working memory on the speech comprehension benefit derived from an automatic speech recognition system

    NARCIS (Netherlands)

    Zekveld, A.A.; Kramer, S.E.; Kessens, J.M.; Vlaming, M.S.M.G.; Houtgast, T.

    2009-01-01

    Objective: The aim of the current study was to examine whether partly incorrect subtitles that are automatically generated by an Automatic Speech Recognition (ASR) system, improve speech comprehension by listeners with hearing impairment. In an earlier study (Zekveld et al. 2008), we showed that

  19. A modified artificial immune system based pattern recognition approach -- an application to clinic diagnostics

    Science.gov (United States)

    Zhao, Weixiang; Davis, Cristina E.

    2011-01-01

    Objective This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. Methods and materials Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function – partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network). Results The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for

  20. High precision, rapid laser hole drilling

    Science.gov (United States)

    Chang, Jim J.; Friedman, Herbert W.; Comaskey, Brian J.

    2013-04-02

    A laser system produces a first laser beam for rapidly removing the bulk of material in an area to form a ragged hole. The laser system produces a second laser beam for accurately cleaning up the ragged hole so that the final hole has dimensions of high precision.

  1. Technology of double casing tubes & a binary cycle system for hole cleaning for CBM multi-branch horizontal wells

    Directory of Open Access Journals (Sweden)

    Yong Yang

    2017-03-01

    Full Text Available At present, the aeration-assisted cutting-carrying technology is faced with complexities in the drilling of CBM multi-branch horizontal wells. For example, the aerating pressure is hardly maintained, and the borehole instability may happen. In view of these prominent problems, the technology of double casing tubes & a binary cycle system suitable for CBM multi-branch horizontal wells was developed according to the Venturi principle by means of parasitic tube insufflation which is used for well control simulation system. Then, a multiphase flow finite element model was established for the fluid-cutting particle system in this drilling condition. This technology was tested in field. Double-casing tubes cementing is adopted in this technology and a jet generator is installed at the bottom of the inner casing. In the process of drilling, the drilling fluid injected through double intermediate casing annulus is converted by the jet generator into a high-efficiency steering water jet, which, together with the water jet generated by the bit nozzle, increases the fluid returning rate in the inner annulus space. It is indicated from simulation results that the cutting-carrying effect is the best when the included angle between the nozzle of the jet generator and the vertical direction is 30°. Besides, the influential laws of cutting size, primary cycle volume, accessory cycle volume and drilling velocity on hole cleaning are figured out. It is concluded that this technology increases the flow rate of drilling fluid in annulus space, the returning rate of drilling fluid significantly and the cutting-carrying capacity. It is currently one of the effective hole cleaning technologies for CBM multi-branch horizontal wells where fresh water is taken as the drilling fluid.

  2. Type I interferon production during herpes simplex virus infection is controlled by cell-type-specific viral recognition through Toll-like receptor 9, the mitochondrial antiviral signaling protein pathway, and novel recognition systems

    DEFF Research Database (Denmark)

    Rasmussen, Simon Brandtoft; Sørensen, Louise Nørgaard; Malmgaard, Lene

    2007-01-01

    Recognition of viruses by germ line-encoded pattern recognition receptors of the innate immune system is essential for rapid production of type I interferon (IFN) and early antiviral defense. We investigated the mechanisms of viral recognition governing production of type I IFN during herpes...... simplex virus (HSV) infection. We show that early production of IFN in vivo is mediated through Toll-like receptor 9 (TLR9) and plasmacytoid dendritic cells, whereas the subsequent alpha/beta IFN (IFN-alpha/beta) response is derived from several cell types and induced independently of TLR9...

  3. 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

  4. 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.

  5. Dissecting molecular interactions involved in recognition of target disulfides by the barley thioredoxin system

    DEFF Research Database (Denmark)

    Björnberg, Olof; Maeda, Kenji; Svensson, Birte

    2012-01-01

    Thioredoxin reduces disulfide bonds, thus regulating activities of target proteins in various biological systems, e.g., inactivation of inhibitors of starch hydrolases and proteases in germinating plant seeds. In the three-dimensional structure of a complex with barley α-amylase/subtilisin inhibi......Thioredoxin reduces disulfide bonds, thus regulating activities of target proteins in various biological systems, e.g., inactivation of inhibitors of starch hydrolases and proteases in germinating plant seeds. In the three-dimensional structure of a complex with barley α...... thioredoxin reductase. HvTrxh2 M88G and M88A adjacent to the invariant cis-proline lost efficiency in both BASI disulfide reduction and recycling by thioredoxin reductase. These effects were further pronounced in M88P lacking a backbone NH group. Remarkably, HvTrxh2 E86R in the same loop displayed overall...... retained catalytic properties, with the exception of a 3-fold increased activity toward BASI. From the 104VGA106 loop, a backbone hydrogen bond donated by A106 appears to be important for target disulfide recognition as A106P lost 90% activity toward BASI but was efficiently recycled by thioredoxin...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. N=2 SUGRA BPS multi-center black holes and freudenthal triple systems

    Directory of Open Access Journals (Sweden)

    Torrente-Lujan E.

    2015-01-01

    Full Text Available We present a detailed description of N = 2 stationary BPS multicenter black hole solutions for quadratic prepotentials with an arbitrary number of centers and scalar fields making a systematic use of the algebraic properties of the matrix of second derivatives of the prepotential, S, which in this case is a scalar-independent matrix. The anti-involution matrix S can be understood as a Freudenthal duality x̃ = Sx. We show that this duality can be generalized to “Freudenthal transformations” x→λexp(θSx=ax+bx˜$x \\to \\lambda \\exp \\left( {\\theta S} \\rightx = ax + b\\tilde x$ under which the horizon area, ADM mass and intercenter distances scale up leaving constant the scalars at the fixed points. In the special case λ = 1, “S-rotations”, the transformations leave invariant the solution. The standard Freudenthal duality can be written as x˜=exp (π2S x$\\tilde x = {\\rm{exp }}\\left( {{\\pi \\over 2}S} \\right{\\rm{ }}x$. We argue that these generalized transformations leave invariant not only the quadratic preotential theories but also the general stringy extremal quartic form Δ4, Δ4(x = Δ4(cos θx + sin θx̃ and therefore its entropy at lowest order.

  11. Hole superconductivity

    International Nuclear Information System (INIS)

    Hirsch, J.E.; Marsiglio, F.

    1989-01-01

    The authors review recent work on a mechanism proposed to explain high T c superconductivity in oxides as well as superconductivity of conventional materials. It is based on pairing of hole carriers through their direct Coulomb interaction, and gives rise to superconductivity because of the momentum dependence of the repulsive interaction in the solid state environment. In the regime of parameters appropriate for high T c oxides this mechanism leads to characteristic signatures that should be experimentally verifiable. In the regime of conventional superconductors most of these signatures become unobservable, but the characteristic dependence of T c on band filling survives. New features discussed her include the demonstration that superconductivity can result from repulsive interactions even if the gap function does not change sign and the inclusion of a self-energy correction to the hole propagator that reduces the range of band filling where T c is not zero

  12. Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors

    Directory of Open Access Journals (Sweden)

    Tuyen Danh Pham

    2015-07-01

    Full Text Available Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

  13. Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

    Science.gov (United States)

    Pham, Tuyen Danh; Park, Young Ho; Nguyen, Dat Tien; Kwon, Seung Yong; Park, Kang Ryoung

    2015-07-13

    Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

  14. Characterizing Black Hole Mergers

    Science.gov (United States)

    Baker, John; Boggs, William Darian; Kelly, Bernard

    2010-01-01

    Binary black hole mergers are a promising source of gravitational waves for interferometric gravitational wave detectors. Recent advances in numerical relativity have revealed the predictions of General Relativity for the strong burst of radiation generated in the final moments of binary coalescence. We explore features in the merger radiation which characterize the final moments of merger and ringdown. Interpreting the waveforms in terms of an rotating implicit radiation source allows a unified phenomenological description of the system from inspiral through ringdown. Common features in the waveforms allow quantitative description of the merger signal which may provide insights for observations large-mass black hole binaries.

  15. Dancing with Black Holes

    Science.gov (United States)

    Aarseth, S. J.

    2008-05-01

    We describe efforts over the last six years to implement regularization methods suitable for studying one or more interacting black holes by direct N-body simulations. Three different methods have been adapted to large-N systems: (i) Time-Transformed Leapfrog, (ii) Wheel-Spoke, and (iii) Algorithmic Regularization. These methods have been tried out with some success on GRAPE-type computers. Special emphasis has also been devoted to including post-Newtonian terms, with application to moderately massive black holes in stellar clusters. Some examples of simulations leading to coalescence by gravitational radiation will be presented to illustrate the practical usefulness of such methods.

  16. Magnonic Black Holes.

    Science.gov (United States)

    Roldán-Molina, A; Nunez, Alvaro S; Duine, R A

    2017-02-10

    We show that the interaction between the spin-polarized current and the magnetization dynamics can be used to implement black-hole and white-hole horizons for magnons-the quanta of oscillations in the magnetization direction in magnets. We consider three different systems: easy-plane ferromagnetic metals, isotropic antiferromagnetic metals, and easy-plane magnetic insulators. Based on available experimental data, we estimate that the Hawking temperature can be as large as 1 K. We comment on the implications of magnonic horizons for spin-wave scattering and transport experiments, and for magnon entanglement.

  17. Black-hole astrophysics

    Energy Technology Data Exchange (ETDEWEB)

    Bender, P. [Univ. of Colorado, Boulder, CO (United States); Bloom, E. [Stanford Linear Accelerator Center, Menlo Park, CA (United States); Cominsky, L. [Sonoma State Univ., Rohnert Park, CA (United States). Dept. of Physics and Astronomy] [and others

    1995-07-01

    Black-hole astrophysics is not just the investigation of yet another, even if extremely remarkable type of celestial body, but a test of the correctness of the understanding of the very properties of space and time in very strong gravitational fields. Physicists` excitement at this new prospect for testing theories of fundamental processes is matched by that of astronomers at the possibility to discover and study a new and dramatically different kind of astronomical object. Here the authors review the currently known ways that black holes can be identified by their effects on their neighborhood--since, of course, the hole itself does not yield any direct evidence of its existence or information about its properties. The two most important empirical considerations are determination of masses, or lower limits thereof, of unseen companions in binary star systems, and measurement of luminosity fluctuations on very short time scales.

  18. Black-hole driven winds

    International Nuclear Information System (INIS)

    Punsly, B.M.

    1988-01-01

    This dissertation is a study of the physical mechanism that allows a large scale magnetic field to torque a rapidly rotating, supermassive black hole. This is an interesting problem as it has been conjectured that rapidly rotating black holes are the central engines that power the observed extragalactic double radio sources. Axisymmetric solutions of the curved space-time version of Maxwell's equations in the vacuum do not torque black holes. Plasma must be introduced for the hole to mechanically couple to the field. The dynamical aspect of rotating black holes that couples the magnetic field to the hole is the following. A rotating black hole forces the external geometry of space-time to rotate (the dragging of inertial frames). Inside of the stationary limit surface, the ergosphere, all physical particle trajectories must appear to rotate in the same direction as the black hole as viewed by the stationary observers at asymptotic infinity. In the text, it is demonstrated how plasma that is created on field lines that thread both the ergosphere and the equatorial plane will be pulled by gravity toward the equator. By the aforementioned properties of the ergosphere, the disk must rotate. Consequently, the disk acts like a unipolar generator. It drives a global current system that supports the toroidal magnetic field in an outgoing, magnetically dominated wind. This wind carries energy (mainly in the form of Poynting flux) and angular momentum towards infinity. The spin down of the black hole is the ultimate source of this energy and angular momentum flux

  19. Large Vocabulary Recognition of Wall Street Journal Sentences at Dragon Systems

    National Research Council Canada - National Science Library

    Baker, James; Baker, Janet; Bamberg, Paul; Bishop, Kathleen; Gillick, Larry; Helman, Vera; Huang, Zezhen; Ito, Yoshiko; Lowe, Stephen; Peskin, Barbara; Roth, Robert; Scattone, Francesco

    1992-01-01

    In this paper we present some of the algorithm improvements that have been made to Dragon's continuous speech recognition and training programs, improvements that have more than halved our error rate...

  20. Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor

    OpenAIRE

    CHIKH, Mohamed Amine; SAIDI, Meryem; SETTOUTI, Nesma

    2012-01-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disea...

  1. Developing a Natural User Interface and Facial Recognition System With OpenCV and the Microsoft Kinect

    Science.gov (United States)

    Gutensohn, Michael

    2018-01-01

    The task for this project was to design, develop, test, and deploy a facial recognition system for the Kennedy Space Center Augmented/Virtual Reality Lab. This system will serve as a means of user authentication as part of the NUI of the lab. The overarching goal is to create a seamless user interface that will allow the user to initiate and interact with AR and VR experiences without ever needing to use a mouse or keyboard at any step in the process.

  2. 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.

  3. A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier

    Directory of Open Access Journals (Sweden)

    Haryati Jaafar

    2015-01-01

    Full Text Available Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN, was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%.

  4. Financial and workflow analysis of radiology reporting processes in the planning phase of implementation of a speech recognition system

    Science.gov (United States)

    Whang, Tom; Ratib, Osman M.; Umamoto, Kathleen; Grant, Edward G.; McCoy, Michael J.

    2002-05-01

    The goal of this study is to determine the financial value and workflow improvements achievable by replacing traditional transcription services with a speech recognition system in a large, university hospital setting. Workflow metrics were measured at two hospitals, one of which exclusively uses a transcription service (UCLA Medical Center), and the other which exclusively uses speech recognition (West Los Angeles VA Hospital). Workflow metrics include time spent per report (the sum of time spent interpreting, dictating, reviewing, and editing), transcription turnaround, and total report turnaround. Compared to traditional transcription, speech recognition resulted in radiologists spending 13-32% more time per report, but it also resulted in reduction of report turnaround time by 22-62% and reduction of marginal cost per report by 94%. The model developed here helps justify the introduction of a speech recognition system by showing that the benefits of reduced operating costs and decreased turnaround time outweigh the cost of increased time spent per report. Whether the ultimate goal is to achieve a financial objective or to improve operational efficiency, it is important to conduct a thorough analysis of workflow before implementation.

  5. Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

    Science.gov (United States)

    Alkilani, Amjad; Shirkhodaie, Amir

    2013-05-01

    Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

  6. Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system.

    Science.gov (United States)

    Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari Hormozi, Shahram; Wah, Teh Ying; Aghabozorgi, Saeed; Pourhoseingholi, Mohamad Amin; Olariu, Teodora

    2015-04-01

    Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis. Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows. With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients. There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for

  7. Black holes and everyday physics

    International Nuclear Information System (INIS)

    Bekenstein, J.D.

    1982-01-01

    Black holes have piqued much curiosity. But thus far they have been important only in ''remote'' subjects like astrophysics and quantum gravity. It is shown that the situation can be improved. By a judicious application of black hole physics, one can obtain new results in ''everyday physics''. For example, black holes yield a quantum universal upper bound on the entropy-to-energy ratio for ordinary thermodynamical systems which was unknown earlier. It can be checked, albeit with much labor, by ordinary statistical methods. Black holes set a limitation on the number of species of elementary particles-quarks, leptons, neutrinos - which may exist. And black holes lead to a fundamental limitation on the rate at which information can be transferred for given message energy by any communication system. (author)

  8. The search for black holes

    International Nuclear Information System (INIS)

    Torn, K.

    1976-01-01

    Conceivable experimental investigations to prove the existence of black holes are discussed. Double system with a black hole turning around a star-satellite are in the spotlight. X-radiation emmited by such systems and resulting from accretion of the stellar gas by a black hole, and the gas heating when falling on the black hole might prove the model suggested. A source of strong X-radiation observed in the Cygnus star cluster and referred to as Cygnus X-1 may be thus identified as a black hole. Direct registration of short X-ray pulses with msec intervals might prove the suggestion. The lack of appropriate astrophysic facilities is pointed out to be the major difficulty on the way of experimental verifications

  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 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

  11. 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.

  12. 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 ...

  13. 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

    2008-11-01

    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.

  14. Notes on Phase Transition of Nonsingular Black Hole

    International Nuclear Information System (INIS)

    Ma Meng-Sen; Zhao Ren

    2015-01-01

    On the belief that a black hole is a thermodynamic system, we study the phase transition of nonsingular black holes. If the black hole entropy takes the form of the Bekenstein—Hawking area law, the black hole mass M is no longer the internal energy of the black hole thermodynamic system. Using the thermodynamic quantities, we calculate the heat capacity, thermodynamic curvature and free energy. It is shown that there will be a larger black hole/smaller black hole phase transition for the nonsingular black hole. At the critical point, the second-order phase transition appears. (paper)

  15. Optical Pattern Recognition

    Science.gov (United States)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

    Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

  16. Black hole final state conspiracies

    International Nuclear Information System (INIS)

    McInnes, Brett

    2009-01-01

    The principle that unitarity must be preserved in all processes, no matter how exotic, has led to deep insights into boundary conditions in cosmology and black hole theory. In the case of black hole evaporation, Horowitz and Maldacena were led to propose that unitarity preservation can be understood in terms of a restriction imposed on the wave function at the singularity. Gottesman and Preskill showed that this natural idea only works if one postulates the presence of 'conspiracies' between systems just inside the event horizon and states at much later times, near the singularity. We argue that some AdS black holes have unusual internal thermodynamics, and that this may permit the required 'conspiracies' if real black holes are described by some kind of sum over all AdS black holes having the same entropy

  17. 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

  18. Black holes escaping from domain walls

    International Nuclear Information System (INIS)

    Flachi, Antonino; Sasaki, Misao; Pujolas, Oriol; Tanaka, Takahiro

    2006-01-01

    Previous studies concerning the interaction of branes and black holes suggested that a small black hole intersecting a brane may escape via a mechanism of reconnection. Here we consider this problem by studying the interaction of a small black hole and a domain wall composed of a scalar field and simulate the evolution of this system when the black hole acquires an initial recoil velocity. We test and confirm previous results, however, unlike the cases previously studied, in the more general set-up considered here, we are able to follow the evolution of the system also during the separation, and completely illustrate how the escape of the black hole takes place

  19. Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-08-01

    Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

  20. Automated Field-of-View, Illumination, and Recognition Algorithm Design of a Vision System for Pick-and-Place Considering Colour Information in Illumination and Images.

    Science.gov (United States)

    Chen, Yibing; Ogata, Taiki; Ueyama, Tsuyoshi; Takada, Toshiyuki; Ota, Jun

    2018-05-22

    Machine vision is playing an increasingly important role in industrial applications, and the automated design of image recognition systems has been a subject of intense research. This study has proposed a system for automatically designing the field-of-view (FOV) of a camera, the illumination strength and the parameters in a recognition algorithm. We formulated the design problem as an optimisation problem and used an experiment based on a hierarchical algorithm to solve it. The evaluation experiments using translucent plastics objects showed that the use of the proposed system resulted in an effective solution with a wide FOV, recognition of all objects and 0.32 mm and 0.4° maximal positional and angular errors when all the RGB (red, green and blue) for illumination and R channel image for recognition were used. Though all the RGB illumination and grey scale images also provided recognition of all the objects, only a narrow FOV was selected. Moreover, full recognition was not achieved by using only G illumination and a grey-scale image. The results showed that the proposed method can automatically design the FOV, illumination and parameters in the recognition algorithm and that tuning all the RGB illumination is desirable even when single-channel or grey-scale images are used for recognition.

  1. Vadose zone studies at an industrial contaminated site: the vadose zone monitoring system and cross-hole geophysics

    Science.gov (United States)

    Fernandez de Vera, Natalia; Beaujean, Jean; Jamin, Pierre; Nguyen, Frédéric; Dahan, Ofer; Vanclooster, Marnik; Brouyère, Serge

    2014-05-01

    In order to improve risk characterization and remediation measures for soil and groundwater contamination, there is a need to improve in situ vadose zone characterization. However, most available technologies have been developed in the context of agricultural soils. Such methodologies are not applicable at industrial sites, where soils and contamination differ in origin and composition. In addition, most technologies are applicable only in the first meters of soils, leaving deeper vadose zones with lack of information, in particular on field scale heterogeneity. In order to overcome such difficulties, a vadose zone experiment has been setup at a former industrial site in Belgium. Industrial activities carried out on site left a legacy of soil and groundwater contamination in BTEX, PAH, cyanide and heavy metals. The experiment comprises the combination of two techniques: the Vadose Zone Monitoring System (VMS) and cross-hole geophysics. The VMS allows continuous measurements of water content and temperature at different depths of the vadose zone. In addition, it provides the possibility of pore water sampling at different depths. The system is formed by a flexible sleeve containing monitoring units along its depth which is installed in a slanted borehole. The flexible sleeve contains three types of monitoring units in the vadose zone: Time Domain Transmissometry (TDT), which allows water content measurements; Vadose Sampling Ports (VSP), used for collecting water samples coming from the matrix; the Fracture Samplers (FS), which are used for retrieving water samples from the fractures. Cross-hole geophysics techniques consist in the injection of an electrical current using electrodes installed in vertical boreholes. From measured potential differences, detailed spatial patterns about electrical properties of the subsurface can be inferred. Such spatial patterns are related with subsurface heterogeneities, water content and solute concentrations. Two VMS were

  2. 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)

  3. Spin One Hawking Radiation from Dirty Black Holes

    OpenAIRE

    Petarpa Boonserm; Tritos Ngampitipan; Matt Visser

    2013-01-01

    A “clean” black hole is a black hole in vacuum such as the Schwarzschild black hole. However in real physical systems, there are matter fields around a black hole. Such a black hole is called a “dirty black hole”. In this paper, the effect of matter fields on the black hole and the greybody factor is investigated. The results show that matter fields make a black hole smaller. They can increase the potential energy to a black hole to obstruct Hawking radiation to propagate. This causes the gre...

  4. Interactions in 2D electron and hole systems in the intermediate and ballistic regimes

    International Nuclear Information System (INIS)

    Proskuryakov, Y Y; Savchenko, A K; Safonov, S S; Li, L; Pepper, M; Simmons, M Y; Ritchie, D A; Linfield, E H; Kvon, Z D

    2003-01-01

    In different 2D semiconductor systems we study the interaction correction to the Drude conductivity in the intermediate and ballistic regimes, where the parameter k B Tτ/ h-bar changes from 0.1 to 10 (τ is momentum relaxation time). The temperature dependence of the resistance and magnetoresistance in parallel and perpendicular magnetic fields is analysed in terms of the recent theories of electron-electron interactions in systems with different degree of disorder and different character of the fluctuation potential. Generally, good agreement is found between the experiments and the theories

  5. 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.

  6. 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…

  7. 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

  8. 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

  9. On the Use of Evolutionary Algorithms to Improve the Robustness of Continuous Speech Recognition Systems in Adverse Conditions

    Directory of Open Access Journals (Sweden)

    Sid-Ahmed Selouani

    2003-07-01

    Full Text Available Limiting the decrease in performance due to acoustic environment changes remains a major challenge for continuous speech recognition (CSR systems. We propose a novel approach which combines the Karhunen-Loève transform (KLT in the mel-frequency domain with a genetic algorithm (GA to enhance the data representing corrupted speech. The idea consists of projecting noisy speech parameters onto the space generated by the genetically optimized principal axis issued from the KLT. The enhanced parameters increase the recognition rate for highly interfering noise environments. The proposed hybrid technique, when included in the front-end of an HTK-based CSR system, outperforms that of the conventional recognition process in severe interfering car noise environments for a wide range of signal-to-noise ratios (SNRs varying from 16 dB to −4 dB. We also showed the effectiveness of the KLT-GA method in recognizing speech subject to telephone channel degradations.

  10. [Research on the application of grey system theory in the pattern recognition for chromatographic fingerprints of traditional Chinese medicine].

    Science.gov (United States)

    Wei, Hang; Lin, Li; Zhang, Yuan; Wang, Lianjing; Chen, Qinqun

    2013-02-01

    A model based on grey system theory was proposed for pattern recognition in chromatographic fingerprints (CF) of traditional Chinese medicine (TCM). The grey relational grade among the data series of each testing CF and the ideal CF was obtained by entropy and norm respectively, then the principle of "maximal matching degree" was introduced to make judgments, so as to achieve the purpose of variety identification and quality evaluation. A satisfactory result in the high performance liquid chromatographic (HPLC) analysis of 56 batches of different varieties of Exocarpium Citrus Grandis was achieved with this model. The errors in the chromatographic fingerprint analysis caused by traditional similarity method or grey correlation method were overcome, as the samples of Citrus grandis 'Tomentosa' and Citrus grandis (L.) Osbeck were correctly distinguished in the experiment. Furthermore in the study on the variety identification of Citrus grandis 'Tomentosa', the recognition rates were up to 92.85%, although the types and the contents of the chemical compositions of the samples were very close. At the same time, the model had the merits of low computation complexity and easy operation by computer programming. The research indicated that the grey system theory has good applicability to pattern recognition in the chromatographic fingerprints of TCM.

  11. Green's tensor calculations of plasmon resonances of single holes and hole pairs in thin gold films

    International Nuclear Information System (INIS)

    Alegret, Joan; Kaell, Mikael; Johansson, Peter

    2008-01-01

    We present numerical calculations of the plasmon properties of single-hole and hole-pair structures in optically thin gold films obtained with the Green's tensor formalism for stratified media. The method can be used to obtain the optical properties of a given hole system, without problems associated with the truncation of the infinite metal film. The calculations are compared with previously published experimental data and an excellent agreement is found. In particular, the calculations are shown to reproduce the evolution of the hole plasmon resonance spectrum as a function of hole diameter, film thickness and hole separation.

  12. A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

    Science.gov (United States)

    Biondich, Paul G; Overhage, J Marc; Dexter, Paul R; Downs, Stephen M; Lemmon, Larry; McDonald, Clement J

    2002-01-01

    Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.

  13. Quantum mechanics of black holes.

    Science.gov (United States)

    Witten, Edward

    2012-08-03

    The popular conception of black holes reflects the behavior of the massive black holes found by astronomers and described by classical general relativity. These objects swallow up whatever comes near and emit nothing. Physicists who have tried to understand the behavior of black holes from a quantum mechanical point of view, however, have arrived at quite a different picture. The difference is analogous to the difference between thermodynamics and statistical mechanics. The thermodynamic description is a good approximation for a macroscopic system, but statistical mechanics describes what one will see if one looks more closely.

  14. Black-hole bomb and superradiant instabilities

    International Nuclear Information System (INIS)

    Cardoso, Vitor; Dias, Oscar J.C.; Lemos, Jose P.S.; Yoshida, Shijun

    2004-01-01

    A wave impinging on a Kerr black hole can be amplified as it scatters off the hole if certain conditions are satisfied, giving rise to superradiant scattering. By placing a mirror around the black hole one can make the system unstable. This is the black-hole bomb of Press and Teukolsky. We investigate in detail this process and compute the growing time scales and oscillation frequencies as a function of the mirror's location. It is found that in order for the system black hole plus mirror to become unstable there is a minimum distance at which the mirror must be located. We also give an explicit example showing that such a bomb can be built. In addition, our arguments enable us to justify why large Kerr-AdS black holes are stable and small Kerr-AdS black holes should be unstable

  15. Application of pattern recognition technique on randon signals for automatic monitoring of dynamic systems with emphasis on nuclear reactors

    International Nuclear Information System (INIS)

    Nascimento, J.A. do.

    1981-01-01

    The time varying or noise component of dynamic system parameters contains information on the system state. Pattern recognition analysis of noise signals for such systems is a powerful technique for assessing 'system normality' or 'correct operation'. Data analysis with modern small computers enables the otherwise unmanageable volumes of data to be processed on line and the results presented in a meaningful form. These informations provide necessary data for maintaining the system at optimum operating conditions. An automatic pattern recognition program, PSDREC, developmed for the surveillance of nuclear reactor and rotating machinery is described, and the relevant theory is outlined. This program, which applies 8 statistical tests to calculated power spectral density (PSD) distributions, was earlier installed in a PDP-11/45 computer at IPEN. In this work it has been used to separately analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel motor (vibration signals). The latter two were, respectively, operated over a wide-range of flow and load conditions. The statistical tests were applied to frequency bands of (0,1-40) Hz, (0-1000) Hz and (0,20000) Hz. for the BWR, pump and diesel signal data, respectively. Operation and analysis conditions are given together with representative graphs of the analysed PSD distributions. Results of the tests - discussed in some detail - are considered to be satisfactory. (Author) [pt

  16. Impact of a PACS/RIS-integrated speech recognition system on radiology reporting time and report availability

    International Nuclear Information System (INIS)

    Trumm, C.G.; Glaser, C.; Paasche, V.; Kuettner, B.; Francke, M.; Nissen-Meyer, S.; Reiser, M.; Crispin, A.; Popp, P.

    2006-01-01

    Purpose: Quantification of the impact of a PACS/RIS-integrated speech recognition system (SRS) on the time expenditure for radiology reporting and on hospital-wide report availability (RA) in a university institution. Material and Methods: In a prospective pilot study, the following parameters were assessed for 669 radiographic examinations (CR): 1. time requirement per report dictation (TED: dictation time (s)/number of images [examination] x number of words [report]) with either a combination of PACS/tape-based dictation (TD: analog dictation device/minicassette/transcription) or PACS/RIS/speech recognition system (RR: remote recognition/transcription and OR: online recognition/self-correction by radiologist), respectively, and 2. the Report Turnaround Time (RTT) as the time interval from the entry of the first image into the PACS to the available RIS/HIS report. Two equal time periods were chosen retrospectively from the RIS database: 11/2002-2/2003 (only TD) and 11/2003-2/2004 (only RR or OR with speech recognition system [SRS]). The midterm (≥24 h, 24 h intervals) and short-term (< 24 h, 1 h intervals), RA after examination completion were calculated for all modalities and for Cr, CT, MR and XA/DS separately. The relative increase in the mid-term RA (RIMRA: related to total number of examinations in each time period) and increase in the short-term RA (ISRA: ratio of available reports during the 1st to 24th hour) were calculated. Results: Prospectively, there was a significant difference between TD/RR/OR (n=151/257/261) regarding mean TED (0.44/0.54/0.62 s [per word and image]) and mean RTT (10.47/6.65/1.27 h), respectively. Retrospectively, 37 898/39 680 reports were computed from the RIS database for the time periods of 11/2002-2/2003 and 11/2003-2/2004. For CR/CT there was a shift of the short-term RA to the first 6 hours after examination completion (mean cumulative RA 20% higher) with a more than three-fold increase in the total number of available

  17. A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor.

    Science.gov (United States)

    Park, Young Ho; Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

    2015-06-15

    An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM). Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line) sensor instead of a conventional two-dimensional (area) sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD) images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.

  18. EBR-II [Experimental Breeder Reactor-II] system surveillance using pattern recognition software

    International Nuclear Information System (INIS)

    Mott, J.E.; Radtke, W.H.; King, R.W.

    1986-02-01

    The problem of most accurately determining the Experimental Breeder Reactor-II (EBR-II) reactor outlet temperature from currently available plant signals is investigated. Historically, the reactor outlet pipe was originally instrumented with 8 temperature sensors but, during 22 years of operation, all these instruments have failed except for one remaining thermocouple, and its output had recently become suspect. Using pattern recognition methods to compare values of 129 plant signals for similarities over a 7 month period spanning reconfiguration of the core and recalibration of many plant signals, it was determined that the remaining reactor outlet pipe thermocouple is still useful as an indicator of true mixed mean reactor outlet temperature. Application of this methodology to investigate one specific signal has automatically validated the vast majority of the 129 signals used for pattern recognition and also highlighted a few inconsistent signals for further investigation

  19. Black holes: the membrane paradigm

    International Nuclear Information System (INIS)

    Thorne, K.S.; Price, R.H.; Macdonald, D.A.

    1986-01-01

    The physics of black holes is explored in terms of a membrane paradigm which treats the event horizon as a two-dimensional membrane embedded in three-dimensional space. A 3+1 formalism is used to split Schwarzschild space-time and the laws of physics outside a nonrotating hole, which permits treatment of the atmosphere in terms of the physical properties of thin slices. The model is applied to perturbed slowly or rapidly rotating and nonrotating holes, and to quantify the electric and magnetic fields and eddy currents passing through a membrane surface which represents a stretched horizon. Features of tidal gravitational fields in the vicinity of the horizon, quasars and active galalctic nuclei, the alignment of jets perpendicular to accretion disks, and the effects of black holes at the center of ellipsoidal star clusters are investigated. Attention is also given to a black hole in a binary system and the interactions of black holes with matter that is either near or very far from the event horizon. Finally, a statistical mechanics treatment is used to derive a second law of thermodynamics for a perfectly thermal atmosphere of a black hole

  20. Thermodynamic theory of black holes

    Energy Technology Data Exchange (ETDEWEB)

    Davies, P C.W. [King' s Coll., London (UK). Dept. of Mathematics

    1977-04-21

    The thermodynamic theory underlying black hole processes is developed in detail and applied to model systems. It is found that Kerr-Newman black holes undergo a phase transition at a = 0.68M or Q = 0.86M, where the heat capacity has an infinite discontinuity. Above the transition values the specific heat is positive, permitting isothermal equilibrium with a surrounding heat bath. Simple processes and stability criteria for various black hole situations are investigated. The limits for entropically favoured black hole formation are found. The Nernst conditions for the third law of thermodynamics are not satisfied fully for black holes. There is no obvious thermodynamic reason why a black hole may not be cooled down below absolute zero and converted into a naked singularity. Quantum energy-momentum tensor calculations for uncharged black holes are extended to the Reissner-Nordstrom case, and found to be fully consistent with the thermodynamic picture for Q < M. For Q < M the model predicts that 'naked' collapse also produces radiation, with such intensity that the collapsing matter is entirely evaporated away before a naked singularity can form.

  1. The Effects of Certain Background Noises on the Performance of a Voice Recognition System.

    Science.gov (United States)

    1980-09-01

    Principles in Experimental Design. New York: McGraw-Hill, 1962. Woodworth, R.S. and H. Schlosberg, Experimental Psychology, (Revised edition), New...collection iheet APPENDIX II EXPERIMENTAL PROTOCOL AND SUBJECTS’ INSTRICTJONS THIS IS AN EXPERIMENT DESIGNED TO EVALUJATE SOME ," lE RECOGNITION EQUIPMENT. I...37. CDR Paul Chatelier OUSD R&E Room 3D129 Pentagon Washington, D.C. 20301 38. Ralph Cleveland NFMSO Code 9333 Mechanicsburg, PA 17055 39. Clay Coler

  2. CERN's Merit Appraisal and Recognition System from the point of view of the supervisor

    CERN Multimedia

    CERN. Geneva

    2013-01-01

    The required training consists of 2 parts : This presentation explaining “CERN’s merit recognition system”, followed by a session of questions/answers – duration : 2 hours A training session on “How to get, as a supervisor, the most out of the annual interview” – duration : 1 day. This hands-on training focuses on how to set smart work and development objectives, how to give feedback and how to run the annual interview in a constructive way.

  3. FEATURE RECOGNITION BERBASIS CORNER DETECTION DENGAN METODE FAST, SURF DAN FLANN TREE UNTUK IDENTIFIKASI LOGO PADA AUGMENTED REALITY MOBILE SYSTEM

    Directory of Open Access Journals (Sweden)

    Rastri Prathivi

    2014-01-01

    Full Text Available Logo is a graphical symbol that is the identity of an organization, institution, or company. Logo is generally used to introduce to the public the existence of an organization, institution, or company. Through the existence of an agency logo can be seen by the public. Feature recognition is one of the processes that exist within an augmented reality system. One of uses augmented reality is able to recognize the identity of the logo through a camera.The first step to make a process of feature recognition is through the corner detection. Incorporation of several method such as FAST, SURF, and FLANN TREE for the feature detection process based corner detection feature matching up process, will have the better ability to detect the presence of a logo. Additionally when running the feature extraction process there are several issues that arise as scale invariant feature and rotation invariant feature. In this study the research object in the form of logo to the priority to make the process of feature recognition. FAST, SURF, and FLANN TREE method will detection logo with scale invariant feature and rotation invariant feature conditions. Obtained from this study will demonstration the accuracy from FAST, SURF, and FLANN TREE methods to solve the scale invariant and rotation invariant feature problems.

  4. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

    Science.gov (United States)

    Arcos-García, Álvaro; Álvarez-García, Juan A; Soria-Morillo, Luis M

    2018-03-01

    This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Jet Precession Driven by a Supermassive Black Hole Binary System in the BL Lac Object PG 1553+113

    Science.gov (United States)

    Caproni, Anderson; Abraham, Zulema; Motter, Juliana Cristina; Monteiro, Hektor

    2017-12-01

    The recent discovery of a roughly simultaneous periodic variability in the light curves of the BL Lac object PG 1553+113 at several electromagnetic bands represents the first case of such odd behavior reported in the literature. Motivated by this, we analyzed 15 GHz interferometric maps of the parsec-scale radio jet of PG 1553+113 to verify the presence of a possible counterpart of this periodic variability. We used the Cross-entropy statistical technique to obtain the structural parameters of the Gaussian components present in the radio maps of this source. We kinematically identified seven jet components formed coincidentally with flare-like features seen in the γ-ray light curve. From the derived jet component positions in the sky plane and their kinematics (ejection epochs, proper motions, and sky position angles), we modeled their temporal changes in terms of a relativistic jet that is steadily precessing in time. Our results indicate a precession period in the observer’s reference frame of 2.24 ± 0.03 years, compatible with the periodicity detected in the light curves of PG 1553+113. However, the maxima of the jet Doppler boosting factor are systematically delayed relative to the peaks of the main γ-ray flares. We propose two scenarios that could explain this delay, both based on the existence of a supermassive black hole binary system in PG 1553+113. We estimated the characteristics of this putative binary system that also would be responsible for driving the inferred jet precession.

  6. Within-individual variation in bullfrog vocalizations: implications for a vocally mediated social recognition system.

    Science.gov (United States)

    Bee, Mark A

    2004-12-01

    Acoustic signals provide a basis for social recognition in a wide range of animals. Few studies, however, have attempted to relate the patterns of individual variation in signals to behavioral discrimination thresholds used by receivers to discriminate among individuals. North American bullfrogs (Rana catesbeiana) discriminate among familiar and unfamiliar individuals based on individual variation in advertisement calls. The sources, patterns, and magnitudes of variation in eight acoustic properties of multiple-note advertisement calls were examined to understand how patterns of within-individual variation might either constrain, or provide additional cues for, vocal recognition. Six of eight acoustic properties exhibited significant note-to-note variation within multiple-note calls. Despite this source of within-individual variation, all call properties varied significantly among individuals, and multivariate analyses indicated that call notes were individually distinct. Fine-temporal and spectral call properties exhibited less within-individual variation compared to gross-temporal properties and contributed most toward statistically distinguishing among individuals. Among-individual differences in the patterns of within-individual variation in some properties suggest that within-individual variation could also function as a recognition cue. The distributions of among-individual and within-individual differences were used to generate hypotheses about the expected behavioral discrimination thresholds of receivers.

  7. The impact of limbic system morphology on facial emotion recognition in bipolar I disorder and healthy controls

    Directory of Open Access Journals (Sweden)

    Bio DS

    2013-05-01

    Full Text Available Danielle Soares Bio,1 Márcio Gerhardt Soeiro-de-Souza,1 Maria Concepción Garcia Otaduy,2 Rodrigo Machado-Vieira,3 Ricardo Alberto Moreno11Mood Disorders Unit, 2Institute of Radiology, Department and Institute of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil; 3Experimental Therapeutics and Pathophysiology Branch (ETPB, National Institute of Mental Health, NIMH NIH, Bethesda, MD, USAIntroduction: Impairments in facial emotion recognition (FER have been reported in bipolar disorder (BD subjects during all mood states. This study aims to investigate the impact of limbic system morphology on FER scores in BD subjects and healthy controls.Material and methods: Thirty-nine euthymic BD I (type I subjects and 40 healthy controls were subjected to a battery of FER tests and examined with 3D structural imaging of the amygdala and hippocampus.Results: The volume of these structures demonstrated a differential pattern of influence on FER scores in BD subjects and controls. In our control sample, larger left and right amygdala demonstrated to be associated to less recognition of sadness faces. In BD group, there was no impact of amygdala volume on FER but we observed a negative impact of the left hippocampus volume in the recognition of happiness while the right hippocampus volume positively impacted on the scores of happiness.Conclusion: Our results indicate that amygdala and hippocampus volumes have distinct effects on FER in BD subjects compared to controls. Knowledge of the neurobiological basis of the illness may help to provide further insights on the role of treatments and psychosocial interventions for BD. Further studies should explore how these effects of amygdala and hippocampus volumes on FER are associated with social networks and social network functioning.Keywords: bipolar disorder, social cognition, facial emotion recognition

  8. Black Hole on a Chip: Proposal for a Physical Realization of the Sachdev-Ye-Kitaev model in a Solid-State System

    Directory of Open Access Journals (Sweden)

    D. I. Pikulin

    2017-07-01

    Full Text Available A system of Majorana zero modes with random infinite-range interactions—the Sachdev-Ye-Kitaev (SYK model—is thought to exhibit an intriguing relation to the horizons of extremal black holes in two-dimensional anti–de Sitter space. This connection provides a rare example of holographic duality between a solvable quantum-mechanical model and dilaton gravity. Here, we propose a physical realization of the SYK model in a solid-state system. The proposed setup employs the Fu-Kane superconductor realized at the interface between a three-dimensional topological insulator and an ordinary superconductor. The requisite N Majorana zero modes are bound to a nanoscale hole fabricated in the superconductor that is threaded by N quanta of magnetic flux. We show that when the system is tuned to the surface neutrality point (i.e., chemical potential coincident with the Dirac point of the topological insulator surface state and the hole has sufficiently irregular shape, the Majorana zero modes are described by the SYK Hamiltonian. We perform extensive numerical simulations to demonstrate that the system indeed exhibits physical properties expected of the SYK model, including thermodynamic quantities and two-point as well as four-point correlators, and discuss ways in which these can be observed experimentally.

  9. A REVIEW: OPTICAL CHARACTER RECOGNITION

    OpenAIRE

    Swati Tomar*1 & Amit Kishore2

    2018-01-01

    This paper presents detailed review in the field of Optical Character Recognition. Various techniques are determine that have been proposed to realize the center of character recognition in an optical character recognition system. Even though, sufficient studies and papers are describes the techniques for converting textual content from a paper document into machine readable form. Optical character recognition is a process where the computer understands automatically the image of handwritten ...

  10. States and properties of metallic systems at a threshold breakdown of the through holes under power laser action (part 2. Susceptibility

    Directory of Open Access Journals (Sweden)

    Kalashnikov E.

    2016-01-01

    Full Text Available Threshold breakdown of the through holes by power laser radiation of metallic foils is considered as response of metallic system to laser radiation. Binding experimentally determined response to the absolute temperature scale allows to determine the value of the imaginary part of the generalized susceptibility depending on temperature, the critical temperature of the transition “liquid metal - gas”, states of the electronic subsystems at this temperature, and the reflectance coefficient values.

  11. Black holes. Chapter 6

    International Nuclear Information System (INIS)

    Penrose, R.

    1980-01-01

    Conditions for the formation of a black hole are considered, and the properties of black holes. The possibility of Cygnus X-1 as a black hole is discussed. Einstein's theory of general relativity in relation to the formation of black holes is discussed. (U.K.)

  12. Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

    Directory of Open Access Journals (Sweden)

    Fernando Castaño

    2017-09-01

    Full Text Available Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.. The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

  13. Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

    Science.gov (United States)

    Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

    2017-09-14

    Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

  14. Virtualized Network Function Orchestration System and Experimental Network Based QR Recognition for a 5G Mobile Access Network

    Directory of Open Access Journals (Sweden)

    Misun Ahn

    2017-12-01

    Full Text Available This paper proposes a virtualized network function orchestration system based on Network Function Virtualization (NFV, one of the main technologies in 5G mobile networks. This system should provide connectivity between network devices and be able to create flexible network function and distribution. This system focuses more on access networks. By experimenting with various scenarios of user service established and activated in a network, we examine whether rapid adoption of new service is possible and whether network resources can be managed efficiently. The proposed method is based on Bluetooth transfer technology and mesh networking to provide automatic connections between network machines and on a Docker flat form, which is a container virtualization technology for setting and managing key functions. Additionally, the system includes a clustering and recovery measure regarding network function based on the Docker platform. We will briefly introduce the QR code perceived service as a user service to examine the proposal and based on this given service, we evaluate the function of the proposal and present analysis. Through the proposed approach, container relocation has been implemented according to a network device’s CPU usage and we confirm successful service through function evaluation on a real test bed. We estimate QR code recognition speed as the amount of network equipment is gradually increased, improving user service and confirm that the speed of recognition is increased as the assigned number of network devices is increased by the user service.

  15. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2018-02-01

    Full Text Available Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples. Therefore, a presentation attack detection (PAD method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP, local ternary pattern (LTP, and histogram of oriented gradients (HOG. As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN method to extract deep image features and the multi-level local binary pattern (MLBP method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

  16. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors.

    Science.gov (United States)

    Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

    2018-02-26

    Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

  17. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

    Science.gov (United States)

    Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

    2018-01-01

    Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases. PMID:29495417

  18. Erratic Black Hole Regulates Itself

    Science.gov (United States)

    2009-03-01

    New results from NASA's Chandra X-ray Observatory have made a major advance in explaining how a special class of black holes may shut off the high-speed jets they produce. These results suggest that these black holes have a mechanism for regulating the rate at which they grow. Black holes come in many sizes: the supermassive ones, including those in quasars, which weigh in at millions to billions of times the mass of the Sun, and the much smaller stellar-mass black holes which have measured masses in the range of about 7 to 25 times the Sun's mass. Some stellar-mass black holes launch powerful jets of particles and radiation, like seen in quasars, and are called "micro-quasars". The new study looks at a famous micro-quasar in our own Galaxy, and regions close to its event horizon, or point of no return. This system, GRS 1915+105 (GRS 1915 for short), contains a black hole about 14 times the mass of the Sun that is feeding off material from a nearby companion star. As the material swirls toward the black hole, an accretion disk forms. This system shows remarkably unpredictable and complicated variability ranging from timescales of seconds to months, including 14 different patterns of variation. These variations are caused by a poorly understood connection between the disk and the radio jet seen in GRS 1915. Chandra, with its spectrograph, has observed GRS 1915 eleven times since its launch in 1999. These studies reveal that the jet in GRS 1915 may be periodically choked off when a hot wind, seen in X-rays, is driven off the accretion disk around the black hole. The wind is believed to shut down the jet by depriving it of matter that would have otherwise fueled it. Conversely, once the wind dies down, the jet can re-emerge. "We think the jet and wind around this black hole are in a sort of tug of war," said Joseph Neilsen, Harvard graduate student and lead author of the paper appearing in the journal Nature. "Sometimes one is winning and then, for reasons we don

  19. Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2016-07-01

    Full Text Available With higher demand from users, surveillance systems are currently being designed to provide more information about the observed scene, such as the appearance of objects, types of objects, and other information extracted from detected objects. Although the recognition of gender of an observed human can be easily performed using human perception, it remains a difficult task when using computer vision system images. In this paper, we propose a new human gender recognition method that can be applied to surveillance systems based on quality assessment of human areas in visible light and thermal camera images. Our research is novel in the following two ways: First, we utilize the combination of visible light and thermal images of the human body for a recognition task based on quality assessment. We propose a quality measurement method to assess the quality of image regions so as to remove the effects of background regions in the recognition system. Second, by combining the features extracted using the histogram of oriented gradient (HOG method and the measured qualities of image regions, we form a new image features, called the weighted HOG (wHOG, which is used for efficient gender recognition. Experimental results show that our method produces more accurate estimation results than the state-of-the-art recognition method that uses human body images.

  20. Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body.

    Science.gov (United States)

    Nguyen, Dat Tien; Park, Kang Ryoung

    2016-07-21

    With higher demand from users, surveillance systems are currently being designed to provide more information about the observed scene, such as the appearance of objects, types of objects, and other information extracted from detected objects. Although the recognition of gender of an observed human can be easily performed using human perception, it remains a difficult task when using computer vision system images. In this paper, we propose a new human gender recognition method that can be applied to surveillance systems based on quality assessment of human areas in visible light and thermal camera images. Our research is novel in the following two ways: First, we utilize the combination of visible light and thermal images of the human body for a recognition task based on quality assessment. We propose a quality measurement method to assess the quality of image regions so as to remove the effects of background regions in the recognition system. Second, by combining the features extracted using the histogram of oriented gradient (HOG) method and the measured qualities of image regions, we form a new image features, called the weighted HOG (wHOG), which is used for efficient gender recognition. Experimental results show that our method produces more accurate estimation results than the state-of-the-art recognition method that uses human body images.