WorldWideScience

Sample records for state-of-the-art pattern recognition

  1. Pattern Recognition and Natural Language Processing: State of the Art

    Directory of Open Access Journals (Sweden)

    Mirjana Kocaleva

    2016-05-01

    Full Text Available Development of information technologies is growing steadily. With the latest software technologies development and application of the methods of artificial intelligence and machine learning intelligence embededs in computers, the expectations are that in near future computers will be able to solve problems themselves like people do. Artificial intelligence emulates human behavior on computers. Rather than executing instructions one by one, as theyare programmed, machine learning employs prior experience/data that is used in the process of system’s training. In this state of the art paper, common methods in AI, such as machine learning, pattern recognition and the natural language processing (NLP are discussed. Also are given standard architecture of NLP processing system and the level thatisneeded for understanding NLP. Lastly the statistical NLP processing and multi-word expressions are described.

  2. Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    Energy Technology Data Exchange (ETDEWEB)

    Deptuch, Gregory; Hoff, Jim; Kwan, Simon; Lipton, Ron; Liu, Ted; Ramberg, Erik; Todri, Aida; Yarema, Ray; /Fermilab; Demarteua, Marcel,; Drake, Gary; Weerts, Harry; /Argonne /Chicago U. /Padua U. /INFN, Padua

    2010-10-01

    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.

  3. Subspace methods for pattern recognition in intelligent environment

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

  4. Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

    Science.gov (United States)

    Yevin, Igor; Koblyakov, Alexander

    The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

  5. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

  6. Online recognition of Chinese characters: the state-of-the-art.

    Science.gov (United States)

    Liu, Cheng-Lin; Jaeger, Stefan; Nakagawa, Masaki

    2004-02-01

    Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

  7. Weighted Local Active Pixel Pattern (WLAPP for Face Recognition in Parallel Computation Environment

    Directory of Open Access Journals (Sweden)

    Gundavarapu Mallikarjuna Rao

    2013-10-01

    Full Text Available Abstract  - The availability of multi-core technology resulted totally new computational era. Researchers are keen to explore available potential in state of art-machines for breaking the bearer imposed by serial computation. Face Recognition is one of the challenging applications on so ever computational environment. The main difficulty of traditional Face Recognition algorithms is lack of the scalability. In this paper Weighted Local Active Pixel Pattern (WLAPP, a new scalable Face Recognition Algorithm suitable for parallel environment is proposed.  Local Active Pixel Pattern (LAPP is found to be simple and computational inexpensive compare to Local Binary Patterns (LBP. WLAPP is developed based on concept of LAPP. The experimentation is performed on FG-Net Aging Database with deliberately introduced 20% distortion and the results are encouraging. Keywords — Active pixels, Face Recognition, Local Binary Pattern (LBP, Local Active Pixel Pattern (LAPP, Pattern computing, parallel workers, template, weight computation.  

  8. 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

  9. Pattern activation/recognition theory of mind.

    Science.gov (United States)

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  10. 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.

  11. A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

    Directory of Open Access Journals (Sweden)

    He-Yuan Lin

    2008-03-01

    Full Text Available A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

  12. A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Li Hsin-Te

    2008-01-01

    Full Text Available Abstract A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

  13. Pattern recognition of state variables by neural networks

    International Nuclear Information System (INIS)

    Faria, Eduardo Fernandes; Pereira, Claubia

    1996-01-01

    An artificial intelligence system based on artificial neural networks can be used to classify predefined events and emergency procedures. These systems are being used in different areas. In the nuclear reactors safety, the goal is the classification of events whose data can be processed and recognized by neural networks. In this works we present a preliminary simple system, using neural networks in the recognition of patterns the recognition of variables which define a situation. (author)

  14. A new concept of vertically integrated pattern recognition associative memory

    International Nuclear Information System (INIS)

    Liu, Ted; Hoff, Jim; Deptuch, Grzegorz; Yarema, Ray

    2011-01-01

    Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing fast pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Scaling of current technologies is unlikely to satisfy the scientific needs of the future, and investments in transformational new technologies need to be made. In this paper, we will discuss a new concept of using the emerging 3D vertical integration technology to significantly advance the state-of-the-art for fast pattern recognition within and outside HEP. A generic R and D proposal based on this new concept, with a few institutions involved, has recently been submitted to DOE with the goal to design and perform the ASIC engineering necessary to realize a prototype device. The progress of this R and D project will be reported in the future. Here we will only focus on the concept of this new approach.

  15. A Learning Patterns Perspective on Student Learning in Higher Education: State of the Art and Moving Forward

    Science.gov (United States)

    Vermunt, Jan D.; Donche, Vincent

    2017-01-01

    The aim of this article is to review the state of the art of research and theory development on student learning patterns in higher education and beyond. First, the learning patterns perspective and the theoretical framework are introduced. Second, research published since 2004 on student learning patterns is systematically identified and…

  16. Graphical symbol recognition

    OpenAIRE

    K.C. , Santosh; Wendling , Laurent

    2015-01-01

    International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...

  17. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

    Science.gov (United States)

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

  18. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  19. Pattern recognition issues on anisotropic smoothed particle hydrodynamics

    Science.gov (United States)

    Pereira Marinho, Eraldo

    2014-03-01

    This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

  20. Pattern recognition issues on anisotropic smoothed particle hydrodynamics

    International Nuclear Information System (INIS)

    Marinho, Eraldo Pereira

    2014-01-01

    This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation

  1. Infrared target recognition based on improved joint local ternary pattern

    Science.gov (United States)

    Sun, Junding; Wu, Xiaosheng

    2016-05-01

    This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

  2. Automated target recognition and tracking using an optical pattern recognition neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1991-01-01

    The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

  3. Multimodality imaging and state-of-art GPU technology in discriminating benign from malignant breast lesions on real time decision support system

    International Nuclear Information System (INIS)

    Kostopoulos, S; Glotsos, D; Kalatzis, I; Asvestas, P; Cavouras, D; Sidiropoulos, K; Dimitropoulos, N

    2014-01-01

    The aim of this study was to design a pattern recognition system for assisting the diagnosis of breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology was employed based on commercial Graphics Processing Unit (GPU) cards and parallel programming. An experienced radiologist outlined breast lesions on both US and DM images from 59 patients employing a custom designed computer software application. Textural features were extracted from each lesion and were used to design the pattern recognition system. Several classifiers were tested for highest performance in discriminating benign from malignant lesions. Classifiers were also combined into ensemble schemes for further improvement of the system's classification accuracy. Following the pattern recognition system optimization, the final system was designed employing the Probabilistic Neural Network classifier (PNN) on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. The use of such state-of-art technology renders the system capable of redesigning itself on site once additional verified US and DM data are collected. Mixture of US and DM features optimized performance with over 90% accuracy in correctly classifying the lesions

  4. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  5. Pattern recognition applied to uranium prospecting

    Energy Technology Data Exchange (ETDEWEB)

    Briggs, P L; Press, F [Massachusetts Inst. of Tech., Cambridge (USA). Dept. of Earth and Planetary Sciences

    1977-07-14

    It is stated that pattern recognition techniques provide one way of combining quantitative and descriptive geological data for mineral prospecting. A quantified decision process using computer-selected patterns of geological data has the potential for selecting areas with undiscovered deposits of uranium or other minerals. When a natural resource is mined more rapidly than it is discovered, its continued production becomes increasingly difficult, and it has been noted that, although a considerable uranium reserve may remain in the U.S.A., the discovery rate for uranium is decreasing exponentially with cumulative exploration footage drilled. Pattern recognition methods of organising geological information for prospecting may provide new predictive power, as well as insight into the occurrence of uranium ore deposits. Often the task of prospecting consists of three stages of information processing: (1) collection of data on known ore deposits; (2) noting any regularities common to the known examples of an ore; (3) selection of new exploration targets based on the results of the second stage. A logical pattern recognition algorithm is here described that implements this geological procedure to demonstrate the possibility of building a quantified uranium prospecting guide from diverse geologic data.

  6. The principles of the pattern recognition of skeletal structures

    International Nuclear Information System (INIS)

    Motto, J.A.

    2006-01-01

    Request of the skeletal system form a lage proportion of plain film radiographic examinations. A sound knowledge of normal radiographic appearances is vital if abnormal patterns are to be recognized.The ABCS, SPACED and SASNOES methods of applying pattern recognition to plain radiographers of bones and joints will be presented in an attempt to make pattern recognition and offer an opinion constitutes role extension of radiographers

  7. Applications of chaotic neurodynamics in pattern recognition

    Science.gov (United States)

    Baird, Bill; Freeman, Walter J.; Eeckman, Frank H.; Yao, Yong

    1991-08-01

    Network algorithms and architectures for pattern recognition derived from neural models of the olfactory system are reviewed. These span a range from highly abstract to physiologically detailed, and employ the kind of dynamical complexity observed in olfactory cortex, ranging from oscillation to chaos. A simple architecture and algorithm for analytically guaranteed associative memory storage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored. There are N units of capacity in an N node network with 3N2 weights. It costs one unit per static attractor, two per Fourier component of each sequence, and three to four per chaotic attractor. There are no spurious attractors, and for sequences there is a Liapunov function in a special coordinate system which governs the approach of transient states to stored trajectories. Unsupervised or supervised incremental learning algorithms for pattern classification, such as competitive learning or bootstrap Widrow-Hoff can easily be implemented. The architecture can be ''folded'' into a recurrent network with higher order weights that can be used as a model of cortex that stores oscillatory and chaotic attractors by a Hebb rule. Network performance is demonstrated by application to the problem of real-time handwritten digit recognition. An effective system with on-line learning has been written by Eeckman and Baird for the Macintosh. It utilizes static, oscillatory, and/or chaotic attractors of two kinds--Lorenze attractors, or attractors resulting from chaotically interacting oscillatory modes. The successful application to an industrial pattern recognition problem of a network architecture of considerable physiological and dynamical complexity, developed by Freeman and Yao, is described. The data sets of the problem come in three classes of difficulty, and performance of the biological network is

  8. Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    International Nuclear Information System (INIS)

    Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; Shochet, M.; Tang, F.; Demarteau, M.

    2011-01-01

    Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition

  9. 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.

  10. Teaching pain recognition through art: the Ramsay-Caravaggio sedation scale.

    Science.gov (United States)

    Poropat, Federico; Cozzi, Giorgio; Magnolato, Andrea; Monasta, Lorenzo; Borrometi, Fabio; Krauss, Baruch; Ventura, Alessandro; Barbi, Egidio

    2018-01-31

    Clinical observation is a key component of medical ability, enabling immediate evaluation of the patient's emotional state and contributing to a clinical clue that leads to final decision making. In medical schools, the art of learning to look can be taught using medical humanities and especially visual arts. By presenting a Ramsay sedation score (RSS) integrated with Caravaggio's paintings during a procedural sedation conference for pediatric residents, we want to test the effectiveness of this approach to improve the quality of learning. In this preliminary study, we presented videos showing sedated pediatric patients in the setting of a procedural sedation lesson to two randomized groups of residents, one attending a lesson on RSS explained through the masterpieces of Caravaggio, the other without artistic support. A week later we tested their learning with ten multi-choice questions focused on theoretical questions about sedation monitoring and ten more questions focused on recognizing the appropriate RSS viewing the videos. The primary outcome was the comparison of the total number of RSS layers properly recognized in both groups. We also evaluated the appreciation of the residents of the use of works of art integrated with the lesson. Eleven students were randomized to each group. Two residents in the standard lesson did not attend the test. The percentage of correct answers on the theoretical part was similar, 82% in the art group and 89% in the other (p > 0.05). No difference was found in the video recognition part of the RSS recognition test. Residents exposed to paintings shown great appreciation for the integration of the lesson with the Caravaggio's masterpieces. Adding artwork to a standard medical conference does not improve the performance of student tests, although this approach has been greatly appreciated by residents.

  11. Staff Report to the Senior Department Official on Recognition Compliance Issues. Recommendation Page: National Accrediting Commission Of Cosmetology Arts and Sciences

    Science.gov (United States)

    US Department of Education, 2010

    2010-01-01

    The National Accrediting Commission of Cosmetology Arts and Sciences (NACCAS) is a national accreditor whose scope of recognition is for the accreditation throughout the United States of postsecondary schools and departments of cosmetology arts and sciences and massage therapy. The agency accredits approximately 1,300 institutions offering…

  12. Nonlinear dynamics of pattern formation and pattern recognition in the rabbit olfactory bulb

    Science.gov (United States)

    Baird, Bill

    1986-10-01

    A mathematical model of the process of pattern recognition in the first olfactory sensory cortex of the rabbit is presented. It explains the formation and alteration of spatial patterns in neural activity observed experimentally during classical Pavlovian conditioning. On each inspiration of the animal, a surge of receptor input enters the olfactory bulb. EEG activity recorded at the surface of the bulb undergoes a transition from a low amplitude background state of temporal disorder to coherent oscillation. There is a distinctive spatial pattern of rms amplitude in this oscillation which changes reliably to a second pattern during each successful recognition by the animal of a conditioned stimulus odor. When a new odor is paired as conditioned stimulus, these patterns are replaced by new patterns that stabilize as the animal adapts to the new environment. I will argue that a unification of the theories of pattern formation and associative memory is required to account for these observations. This is achieved in a model of the bulb as a discrete excitable medium with spatially inhomogeneous coupling expressed by a connection matrix. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of competing unstable oscillatory modes. These may be created in the system by proper coupling and selectively evoked by specific classes of inputs. This allows a view of limit cycle attractors as “stored” fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

  13. PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

    Science.gov (United States)

    Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

    2004-11-01

    Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

  14. Listening for recollection: a multi-voxel pattern analysis of recognition memory retrieval strategies

    Directory of Open Access Journals (Sweden)

    Joel R Quamme

    2010-08-01

    Full Text Available Recent studies of recognition memory indicate that subjects can strategically vary how much they rely on recollection of specific details vs. feelings of familiarity when making recognition judgments. One possible explanation of these results is that subjects can establish an internally-directed attentional state (listening for recollection that enhances retrieval of studied details; fluctuations in this attentional state over time should be associated with fluctuations in subjects' recognition behavior. In this study, we used multi-voxel pattern analysis of fMRI data to identify brain regions that are involved in listening for recollection. Specifically, we looked for brain regions that met the following criteria: 1 Distinct neural patterns should be present when subjects are instructed to rely on recollection vs. familiarity, and 2 fluctuations in these neural patterns should be related to recognition behavior in the manner predicted by dual-process theories of recognition: Specifically, the presence of the recollection pattern during the pre-stimulus interval (indicating that subjects are listening for recollection at that moment should be associated with a selective decrease in false alarms to related lures. We found that pre-stimulus activity in the right supramarginal gyrus met all of these criteria, suggesting that this region proactively establishes an internally-directed attentional state that fosters recollection. We also found other regions (e.g., left middle temporal gyrus where the pattern of neural activity was related to subjects’ responding to related lures after stimulus onset (but not before, suggesting that these regions implement processes that are engaged in a reactive fashion to boost recollection.

  15. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

    The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

  16. Comparative study of state-of-the-art myoelectric controllers for multigrasp prosthetic hands.

    Science.gov (United States)

    Segil, Jacob L; Controzzi, Marco; Weir, Richard F ff; Cipriani, Christian

    2014-01-01

    A myoelectric controller should provide an intuitive and effective human-machine interface that deciphers user intent in real-time and is robust enough to operate in daily life. Many myoelectric control architectures have been developed, including pattern recognition systems, finite state machines, and more recently, postural control schemes. Here, we present a comparative study of two types of finite state machines and a postural control scheme using both virtual and physical assessment procedures with seven nondisabled subjects. The Southampton Hand Assessment Procedure (SHAP) was used in order to compare the effectiveness of the controllers during activities of daily living using a multigrasp artificial hand. Also, a virtual hand posture matching task was used to compare the controllers when reproducing six target postures. The performance when using the postural control scheme was significantly better (p state machines during the physical assessment when comparing within-subject averages using the SHAP percent difference metric. The virtual assessment results described significantly greater completion rates (97% and 99%) for the finite state machines, but the movement time tended to be faster (2.7 s) for the postural control scheme. Our results substantiate that postural control schemes rival other state-of-the-art myoelectric controllers.

  17. Data structures, computer graphics, and pattern recognition

    CERN Document Server

    Klinger, A; Kunii, T L

    1977-01-01

    Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

  18. The Pandora software development kit for pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, J.S.; Thomson, M.A. [University of Cambridge, Cavendish Laboratory, Cambridge (United Kingdom)

    2015-09-15

    The development of automated solutions to pattern recognition problems is important in many areas of scientific research and human endeavour. This paper describes the implementation of the Pandora software development kit, which aids the process of designing, implementing and running pattern recognition algorithms. The Pandora Application Programming Interfaces ensure simple specification of the building-blocks defining a pattern recognition problem. The logic required to solve the problem is implemented in algorithms. The algorithms request operations to create or modify data structures and the operations are performed by the Pandora framework. This design promotes an approach using many decoupled algorithms, each addressing specific topologies. Details of algorithms addressing two pattern recognition problems in High Energy Physics are presented: reconstruction of events at a high-energy e{sup +}e{sup -} linear collider and reconstruction of cosmic ray or neutrino events in a liquid argon time projection chamber. (orig.)

  19. 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.

  20. Design and testing of the first 2D Prototype Vertically Integrated Pattern Recognition Associative Memory

    Energy Technology Data Exchange (ETDEWEB)

    Liu, T.; Deptuch, G.; Hoff, J.; Jindariani, S.; Joshi, S.; Olsen, J.; Tran, N.; Trimpl, M.

    2015-02-01

    An associative memory-based track finding approach has been proposed for a Level 1 tracking trigger to cope with increasing luminosities at the LHC. The associative memory uses a massively parallel architecture to tackle the intrinsically complex combinatorics of track finding algorithms, thus avoiding the typical power law dependence of execution time on occupancy and solving the pattern recognition in times roughly proportional to the number of hits. This is of crucial importance given the large occupancies typical of hadronic collisions. The design of an associative memory system capable of dealing with the complexity of HL-LHC collisions and with the short latency required by Level 1 triggering poses significant, as yet unsolved, technical challenges. For this reason, an aggressive R&D program has been launched at Fermilab to advance state of-the-art associative memory technology, the so called VIPRAM (Vertically Integrated Pattern Recognition Associative Memory) project. The VIPRAM leverages emerging 3D vertical integration technology to build faster and denser Associative Memory devices. The first step is to implement in conventional VLSI the associative memory building blocks that can be used in 3D stacking, in other words, the building blocks are laid out as if it is a 3D design. In this paper, we report on the first successful implementation of a 2D VIPRAM demonstrator chip (protoVIPRAM00). The results show that these building blocks are ready for 3D stacking.

  1. Fine-grained recognition of plants from images.

    Science.gov (United States)

    Šulc, Milan; Matas, Jiří

    2017-01-01

    Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition "in the wild". We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition "in the wild". The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition "in the wild" where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

  2. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open......CV library is used for signal processing. We conclude that the approach presented here is a viable solution to pattern recognition problems. Since it requires no network connection, it shows promise in fields such as wildlife research....

  3. 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

  4. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  5. Description and recognition of patterns in stochastic signals. [Electroencephalograms

    Energy Technology Data Exchange (ETDEWEB)

    Flik, T [Technische Univ. Berlin (F.R. Germany). Informatik-Forschungsgruppe Rechnerorganisation und Schaltwerke

    1975-10-01

    A method is shown for the description and recognition of patterns in stochastic signals such as electroencephalograms. For pattern extraction the signal is segmented at times of minimum amplitudes. The describing features consist of geometric values of the so defined patterns. The classification algorithm is based on the regression analysis, which is well known in the field of character recognition. For an economic classification a method is proposed which reduces the number of features. The quality of this pattern recognition method is demonstrated by the detection of spike wave complexes in electroencephalograms. The pattern description and recognition are provided for processing on a digital computer. (DE)

  6. Star pattern recognition algorithm aided by inertial information

    Science.gov (United States)

    Liu, Bao; Wang, Ke-dong; Zhang, Chao

    2011-08-01

    Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

  7. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  8. State of the States, 2012: Arts Education State Policy Summary

    Science.gov (United States)

    Arts Education Partnership (NJ1), 2012

    2012-01-01

    The "State of the States 2012" summarizes state policies for arts education identified in statute or code for all 50 states and the District of Columbia. Information is based primarily on results from the AEP Arts Education State Policy Survey conducted in 2010-11, and updated in April 2012.

  9. Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

    Science.gov (United States)

    Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

    2018-04-01

    Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

  10. The Role of Binocular Disparity in Rapid Scene and Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Matteo Valsecchi

    2013-04-01

    Full Text Available We investigated the contribution of binocular disparity to the rapid recognition of scenes and simpler spatial patterns using a paradigm combining backward masked stimulus presentation and short-term match-to-sample recognition. First, we showed that binocular disparity did not contribute significantly to the recognition of briefly presented natural and artificial scenes, even when the availability of monocular cues was reduced. Subsequently, using dense random dot stereograms as stimuli, we showed that observers were in principle able to extract spatial patterns defined only by disparity under brief, masked presentations. Comparing our results with the predictions from a cue-summation model, we showed that combining disparity with luminance did not per se disrupt the processing of disparity. Our results suggest that the rapid recognition of scenes is mediated mostly by a monocular comparison of the images, although we can rely on stereo in fast pattern recognition.

  11. Application Of t-Cherry Junction Trees in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Edith Kovacs

    2010-06-01

    Full Text Available Pattern recognition aims to classify data (patterns based ei-
    ther on a priori knowledge or on statistical information extracted from the data. In this paper we will concentrate on statistical pattern recognition using a new probabilistic approach which makes possible to select the so called 'informative' features. We develop a pattern recognition algorithm which is based on the conditional independence structure underlying the statistical data. Our method was succesfully applied on a real problem of recognizing Parkinson's disease on the basis of voice disorders.

  12. Fringe patterns generated by micro-optical sensors for pattern recognition.

    Science.gov (United States)

    Tamee, Kreangsak; Chaiwong, Khomyuth; Yothapakdee, Kriengsak; Yupapin, Preecha P

    2015-01-01

    We present a new result of pattern recognition generation scheme using a small-scale optical muscle sensing system, which consisted of an optical add-drop filter incorporating two nonlinear optical side ring resonators. When light from laser source enters into the system, the device is stimulated by an external physical parameter that introduces a change in the phase of light propagation within the sensing device, which can be formed by the interference fringe patterns. Results obtained have shown that the fringe patterns can be used to form the relationship between signal patterns and fringe pattern recognitions.

  13. Pattern Recognition Control Design

    Science.gov (United States)

    Gambone, Elisabeth A.

    2018-01-01

    Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

  14. 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.

  15. Distorted Pattern Recognition and Analysis with the Help of IEf Graph Representation

    Directory of Open Access Journals (Sweden)

    Adam Sedziwy

    2002-01-01

    Full Text Available An algorithm for distorted pattern recognition is presented. lt's generalization of M Flasinski results (Pattern Recognition, 27, 1-16, 1992. A new formalism allows to make both qualitative and quantitive distortion analysis. It also enlarges parser flexibility by extending the set of patterns which may be recognized.

  16. Pattern Recognition of the Multiple Sclerosis Syndrome

    Science.gov (United States)

    Stewart, Renee; Healey, Kathleen M.

    2017-01-01

    During recent decades, the autoimmune disease neuromyelitis optica spectrum disorder (NMOSD), once broadly classified under the umbrella of multiple sclerosis (MS), has been extended to include autoimmune inflammatory conditions of the central nervous system (CNS), which are now diagnosable with serum serological tests. These antibody-mediated inflammatory diseases of the CNS share a clinical presentation to MS. A number of practical learning points emerge in this review, which is geared toward the pattern recognition of optic neuritis, transverse myelitis, brainstem/cerebellar and hemispheric tumefactive demyelinating lesion (TDL)-associated MS, aquaporin-4-antibody and myelin oligodendrocyte glycoprotein (MOG)-antibody NMOSD, overlap syndrome, and some yet-to-be-defined/classified demyelinating disease, all unspecifically labeled under MS syndrome. The goal of this review is to increase clinicians’ awareness of the clinical nuances of the autoimmune conditions for MS and NMSOD, and to highlight highly suggestive patterns of clinical, paraclinical or imaging presentations in order to improve differentiation. With overlay in clinical manifestations between MS and NMOSD, magnetic resonance imaging (MRI) of the brain, orbits and spinal cord, serology, and most importantly, high index of suspicion based on pattern recognition, will help lead to the final diagnosis. PMID:29064441

  17. The art and learning patterns of knowing in nursing

    Directory of Open Access Journals (Sweden)

    Cristina Lavareda Baixinho

    2014-12-01

    Full Text Available Objective To identify the perception of the students about the use of art as a pedagogical strategy in learning the patterns of knowing in nursing; to identify the dimensions of each pattern valued in the analysis of pieces of art. Method Descriptive mixed study. Data collection used a questionnaire applied to 31 nursing students. Results In the analysis of the students’ discourse, it was explicit that empirical knowledge includes scientific knowledge, tradition and nature of care. The aesthetic knowledge implies expressiveness, subjectivity and sensitivity. Self-knowledge, experience, reflective attitude and relationships with others are the subcategories of personal knowledge and the moral and ethics support ethical knowledge. Conclusion It is possible to learn patterns of knowledge through art, especially the aesthetic, ethical and personal. It is necessary to investigate further pedagogical strategies that contribute to the learning patterns of nursing knowledge.

  18. 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

  19. Degraded character recognition based on gradient pattern

    Science.gov (United States)

    Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

    2010-02-01

    Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

  20. Haar-like Rectangular Features for Biometric Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam

    2013-01-01

    Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...

  1. Pattern recognition in high energy physics

    International Nuclear Information System (INIS)

    Tenner, A.G.

    1980-01-01

    In high energy physics experiments tracks of elementary particles are recorded by different types of equipment. Coordinates of points of these tracks have to be measured for the geometrical reconstruction and the further analysis of the observed events. Pattern recognition methods may facilitate the detection of tracks or whole events and the separation of relevant from non-relevant information. They may also serve for the automation of measurement. Generally, all work is done by digital computation. In a bubble chamber tracks appear as strings of vapour bubbles that can be recorded photographically. Two methods of pattern recognition are discussed. The flying spot digitizer encodes the pattern on the photograph into point coordinates in the memory of a computer. The computer carries out the pattern recognition procedure entirely on the basis of the stored information. Cathode ray instruments scan the photograph by means of a computer steered optical device. Data acquisition from the film is performed in a feedback loop of the computation. In electronic experimental equipment tracks are defined by the spacial distribution of hits of counters (wire counters, scintillation counters, spark chambers). Pattern recognition is generally performed in various stages both by on-line and off-line equipment. Problems in the data handling arise both from the great abundance of data and from the time limits imposed on the on-line computation by high measuring rates. The on-line computation is carried out by hardwired logic, small computers, and to an increasing extent by microprocessors. (Auth.)

  2. Pattern recognition of neurotransmitters using multimode sensing.

    Science.gov (United States)

    Stefan-van Staden, Raluca-Ioana; Moldoveanu, Iuliana; van Staden, Jacobus Frederick

    2014-05-30

    Pattern recognition is essential in chemical analysis of biological fluids. Reliable and sensitive methods for neurotransmitters analysis are needed. Therefore, we developed for pattern recognition of neurotransmitters: dopamine, epinephrine, norepinephrine a method based on multimode sensing. Multimode sensing was performed using microsensors based on diamond paste modified with 5,10,15,20-tetraphenyl-21H,23H-porphyrine, hemin and protoporphyrin IX in stochastic and differential pulse voltammetry modes. Optimized working conditions: phosphate buffer solution of pH 3.01 and KCl 0.1mol/L (as electrolyte support), were determined using cyclic voltammetry and used in all measurements. The lowest limits of quantification were: 10(-10)mol/L for dopamine and epinephrine, and 10(-11)mol/L for norepinephrine. The multimode microsensors were selective over ascorbic and uric acids and the method facilitated reliable assay of neurotransmitters in urine samples, and therefore, the pattern recognition showed high reliability (RSDneurotransmitters on biological fluids at a lower determination level than chromatographic methods. The sampling of the biological fluids referees only to the buffering (1:1, v/v) with a phosphate buffer pH 3.01, while for chromatographic methods the sampling is laborious. Accordingly with the statistic evaluation of the results at 99.00% confidence level, both modes can be used for pattern recognition and quantification of neurotransmitters with high reliability. The best multimode microsensor was the one based on diamond paste modified with protoporphyrin IX. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Molecularly imprinted polymers for the recognition of proteins: the state of the art.

    Science.gov (United States)

    Bossi, A; Bonini, F; Turner, A P F; Piletsky, S A

    2007-01-15

    Molecular imprinting has proved to be an effective technique for the creation of recognition sites on a polymer scaffold. Protein imprinting has been a focus for many chemists working in the area of molecular recognition, since the creation of synthetic polymers that can specifically recognise proteins is a very challenging but potentially extremely rewarding objective. It is expected that molecularly imprinted polymers (MIPs) with specificity for proteins will find application in medicine, diagnostics, proteomics, environmental analysis, sensors and drug delivery. In this review, the authors provide an overview of the progress achieved in the decade between 1994 and 2005, with respect to the challenging area of MIPs for protein recognition. The discussion furnishes a comparative analysis of different approaches developed, underlining their relative advantages and disadvantages and highlighting trends and possible future directions.

  4. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    Energy Technology Data Exchange (ETDEWEB)

    Acciarri, R.; Bagby, L.; Baller, B.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Greenlee, H.; James, C.; Jostlein, H.; Ketchum, W.; Kirby, M.; Kobilarcik, T.; Lockwitz, S.; Lundberg, B.; Marchionni, A.; Moore, C.D.; Palamara, O.; Pavlovic, Z.; Raaf, J.L.; Schukraft, A.; Snider, E.L.; Spentzouris, P.; Strauss, T.; Toups, M.; Wolbers, S.; Yang, T.; Zeller, G.P. [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Adams, C. [Harvard University, Cambridge, MA (United States); Yale University, New Haven, CT (United States); An, R.; Littlejohn, B.R.; Martinez Caicedo, D.A. [Illinois Institute of Technology (IIT), Chicago, IL (United States); Anthony, J.; Escudero Sanchez, L.; De Vries, J.J.; Marshall, J.; Smith, A.; Thomson, M. [University of Cambridge, Cambridge (United Kingdom); Asaadi, J. [University of Texas, Arlington, TX (United States); Auger, M.; Ereditato, A.; Goeldi, D.; Kreslo, I.; Lorca, D.; Luethi, M.; Rudolf von Rohr, C.; Sinclair, J.; Weber, M. [Universitaet Bern, Bern (Switzerland); Balasubramanian, S.; Fleming, B.T.; Gramellini, E.; Hackenburg, A.; Luo, X.; Russell, B.; Tufanli, S. [Yale University, New Haven, CT (United States); Barnes, C.; Mousseau, J.; Spitz, J. [University of Michigan, Ann Arbor, MI (United States); Barr, G.; Bass, M.; Del Tutto, M.; Laube, A.; Soleti, S.R.; De Pontseele, W.V. [University of Oxford, Oxford (United Kingdom); Bay, F. [TUBITAK Space Technologies Research Institute, Ankara (Turkey); Bishai, M.; Chen, H.; Joshi, J.; Kirby, B.; Li, Y.; Mooney, M.; Qian, X.; Viren, B.; Zhang, C. [Brookhaven National Laboratory (BNL), Upton, NY (United States); Blake, A.; Devitt, D.; Lister, A.; Nowak, J. [Lancaster University, Lancaster (United Kingdom); Bolton, T.; Horton-Smith, G.; Meddage, V.; Rafique, A. [Kansas State University (KSU), Manhattan, KS (United States); Camilleri, L.; Caratelli, D.; Crespo-Anadon, J.I.; Fadeeva, A.A.; Genty, V.; Kaleko, D.; Seligman, W.; Shaevitz, M.H. [Columbia University, New York, NY (United States); Church, E. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Cianci, D.; Karagiorgi, G. [Columbia University, New York, NY (United States); The University of Manchester (United Kingdom); Cohen, E.; Piasetzky, E. [Tel Aviv University, Tel Aviv (Israel); Collin, G.H.; Conrad, J.M.; Hen, O.; Hourlier, A.; Moon, J.; Wongjirad, T.; Yates, L. [Massachusetts Institute of Technology (MIT), Cambridge, MA (United States); Convery, M.; Eberly, B.; Rochester, L.; Tsai, Y.T.; Usher, T. [SLAC National Accelerator Laboratory, Menlo Park, CA (United States); Dytman, S.; Graf, N.; Jiang, L.; Naples, D.; Paolone, V.; Wickremasinghe, D.A. [University of Pittsburgh, Pittsburgh, PA (United States); Esquivel, J.; Hamilton, P.; Pulliam, G.; Soderberg, M. [Syracuse University, Syracuse, NY (United States); Foreman, W.; Ho, J.; Schmitz, D.W.; Zennamo, J. [University of Chicago, IL (United States); Furmanski, A.P.; Garcia-Gamez, D.; Hewes, J.; Hill, C.; Murrells, R.; Porzio, D.; Soeldner-Rembold, S.; Szelc, A.M. [The University of Manchester (United Kingdom); Garvey, G.T.; Huang, E.C.; Louis, W.C.; Mills, G.B.; De Water, R.G.V. [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Gollapinni, S. [Kansas State University (KSU), Manhattan, KS (United States); University of Tennessee, Knoxville, TN (United States); and others

    2018-01-15

    The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies. (orig.)

  5. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    Science.gov (United States)

    Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2018-01-01

    The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

  6. Pattern recognition methods in air pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Tauber, S

    1978-01-01

    The use of pattern recognition methods for predicting air pollution developments is discussed. Computer analysis of historical pollution data allows comparison in graphical form. An example of crisis prediction for carbon monoxide concentrations, using the pattern recognition method of analysis, is presented. Results of the analysis agreed well with actual CO conditions. (6 graphs, 4 references, 1 table)

  7. The Role of Verbal Instruction and Visual Guidance in Training Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Jamie S. North

    2017-09-01

    Full Text Available We used a novel approach to examine whether it is possible to improve the perceptual–cognitive skill of pattern recognition using a video-based training intervention. Moreover, we investigated whether any improvements in pattern recognition transfer to an improved ability to make anticipation judgments. Finally, we compared the relative effectiveness of verbal and visual guidance interventions compared to a group that merely viewed the same sequences without any intervention and a control group that only completed pre- and post-tests. We found a significant effect for time of testing. Participants were more sensitive in their ability to perceive patterns and distinguish between novel and familiar sequences at post- compared to pre-test. However, this improvement was not influenced by the nature of the intervention, despite some trends in the data. An analysis of anticipation accuracy showed no change from pre- to post-test following the pattern recognition training intervention, suggesting that the link between pattern perception and anticipation may not be strong. We present a series of recommendations for scientists and practitioners when employing training methods to improve pattern recognition and anticipation.

  8. A pattern recognition account of decision making.

    Science.gov (United States)

    Massaro, D W

    1994-09-01

    In the domain of pattern recognition, experiments have shown that perceivers integrate multiple sources of information in an optimal manner. In contrast, other research has been interpreted to mean that decision making is nonoptimal. As an example, Tversky and Kahneman (1983) have shown that subjects commit a conjunction fallacy because they judge it more likely that a fictitious person named Linda is a bank teller and a feminist than just a bank teller. This judgment supposedly violates probability theory, because the probability of two events can never be greater than the probability of either event alone. The present research tests the hypothesis that subjects interpret this judgment task as a pattern recognition task. If this hypothesis is correct, subjects' judgments should be described accurately by the fuzzy logical model of perception (FLMP)--a successful model of pattern recognition. In the first experiment, the Linda task was extended to an expanded factorial design with five vocations and five avocations. The probability ratings were described well by the FLMP and described poorly by a simple probability model. The second experiment included (1) two fictitious people, Linda and Joan, as response alternatives and (2) both ratings and categorization judgments. Although the ratings were accurately described by both the FLMP and an averaging of the sources of information, the categorization judgments were described better by the FLMP. These results reveal important similarities in recognizing patterns and in decision making. Given that the FLMP is an optimal method for combining multiple sources of information, the probability judgments appear to be optimal in the same manner as pattern-recognition judgments.

  9. State-of-the-art

    DEFF Research Database (Denmark)

    Pecher, Arthur; Kofoed, Jens Peter

    This report presents a short overview on the state-of-the-art of wave tank testing of wave energy converters (WEC). Here for, it focuses mainly on the Phase 1 and 2 development phases of wave energy converters, as these are done in the wave tank (WEC), while the other development phases are perfo......This report presents a short overview on the state-of-the-art of wave tank testing of wave energy converters (WEC). Here for, it focuses mainly on the Phase 1 and 2 development phases of wave energy converters, as these are done in the wave tank (WEC), while the other development phases...

  10. Optical Pattern Recognition for Missile Guidance.

    Science.gov (United States)

    1982-11-15

    directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

  11. Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

    Science.gov (United States)

    Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

    2017-12-01

    The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Technical Reviews on Pattern Recognition in Process Analytical Technology

    International Nuclear Information System (INIS)

    Kim, Jong Yun; Choi, Yong Suk; Ji, Sun Kyung; Park, Yong Joon; Song, Kyu Seok; Jung, Sung Hee

    2008-12-01

    Pattern recognition is one of the first and the most widely adopted chemometric tools among many active research area in chemometrics such as design of experiment(DoE), pattern recognition, multivariate calibration, signal processing. Pattern recognition has been used to identify the origin of a wine and the time of year that the vine was grown by using chromatography, cause of fire by using GC/MS chromatography, detection of explosives and land mines, cargo and luggage inspection in seaports and airports by using a prompt gamma-ray activation analysis, and source apportionment of environmental pollutant by using a stable isotope ratio mass spectrometry. Recently, pattern recognition has been taken into account as a major chemometric tool in the so-called 'process analytical technology (PAT)', which is a newly-developed concept in the area of process analytics proposed by US Food and Drug Administration (US FDA). For instance, identification of raw material by using a pattern recognition analysis plays an important role for the effective quality control of the production process. Recently, pattern recognition technique has been used to identify the spatial distribution and uniformity of the active ingredients present in the product such as tablet by transforming the chemical data into the visual information

  13. Artvision: State Arts Plan, 2009-2011

    Science.gov (United States)

    South Dakota Arts Council, 2010

    2010-01-01

    The South Dakota Legislature, being aware of the impact of culture on a stable economy, desires to stimulate, encourage, and give recognition and assistance to the arts which, in order to grow and flourish, depend upon freedom, imagination and individual initiative. While the development of the arts has long been considered a matter of local…

  14. Pattern recognition and modelling of earthquake registrations with interactive computer support

    International Nuclear Information System (INIS)

    Manova, Katarina S.

    2004-01-01

    The object of the thesis is Pattern Recognition. Pattern recognition i.e. classification, is applied in many fields: speech recognition, hand printed character recognition, medical analysis, satellite and aerial-photo interpretations, biology, computer vision, information retrieval and so on. In this thesis is studied its applicability in seismology. Signal classification is an area of great importance in a wide variety of applications. This thesis deals with the problem of (automatic) classification of earthquake signals, which are non-stationary signals. Non-stationary signal classification is an area of active research in the signal and image processing community. The goal of the thesis is recognition of earthquake signals according to their epicentral zone. Source classification i.e. recognition is based on transformation of seismograms (earthquake registrations) to images, via time-frequency transformations, and applying image processing and pattern recognition techniques for feature extraction, classification and recognition. The tested data include local earthquakes from seismic regions in Macedonia. By using actual seismic data it is shown that proposed methods provide satisfactory results for classification and recognition.(Author)

  15. Two Challenges of Correct Validation in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Thomas eNowotny

    2014-09-01

    Full Text Available Supervised pattern recognition is the process of mapping patterns to class labelsthat define their meaning. The core methods for pattern recognitionhave been developed by machine learning experts but due to their broadsuccess an increasing number of non-experts are now employing andrefining them. In this perspective I will discuss the challenge ofcorrect validation of supervised pattern recognition systems, in particular whenemployed by non-experts. To illustrate the problem I will give threeexamples of common errors that I have encountered in the lastyear. Much of this challenge can be addressed by strict procedure invalidation but there are remaining problems of correctlyinterpreting comparative work on exemplary data sets, which I willelucidate on the example of the well-used MNIST data set of handwrittendigits.

  16. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  17. Data analysis and pattern recognition in multiple databases

    CERN Document Server

    Adhikari, Animesh; Pedrycz, Witold

    2014-01-01

    Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyse them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery, and mining patterns of select items provide different...

  18. Investigation of pattern recognition techniques for the indentification of splitting surfaces in Monte Carlo particle transport calculations

    International Nuclear Information System (INIS)

    Macdonald, J.L.

    1975-08-01

    Statistical and deterministic pattern recognition systems are designed to classify the state space of a Monte Carlo transport problem into importance regions. The surfaces separating the regions can be used for particle splitting and Russian roulette in state space in order to reduce the variance of the Monte Carlo tally. Computer experiments are performed to evaluate the performance of the technique using one and two dimensional Monte Carlo problems. Additional experiments are performed to determine the sensitivity of the technique to various pattern recognition and Monte Carlo problem dependent parameters. A system for applying the technique to a general purpose Monte Carlo code is described. An estimate of the computer time required by the technique is made in order to determine its effectiveness as a variance reduction device. It is recommended that the technique be further investigated in a general purpose Monte Carlo code. (auth)

  19. A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies.

    Science.gov (United States)

    Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

    2017-04-15

    Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller.

  20. Applications of evolutionary computation in image processing and pattern recognition

    CERN Document Server

    Cuevas, Erik; Perez-Cisneros, Marco

    2016-01-01

    This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...

  1. 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)

  2. Environmental Sound Recognition Using Time-Frequency Intersection Patterns

    Directory of Open Access Journals (Sweden)

    Xuan Guo

    2012-01-01

    Full Text Available Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we use a multistage perceptron neural network system for environmental sound recognition. The input data is a combination of time-variance pattern of instantaneous powers and frequency-variance pattern with instantaneous spectrum at the power peak, referred to as a time-frequency intersection pattern. Spectra of many environmental sounds change more slowly than those of speech or voice, so the intersectional time-frequency pattern will preserve the major features of environmental sounds but with drastically reduced data requirements. Two experiments were conducted using an original database and an open database created by the RWCP project. The recognition rate for 20 kinds of environmental sounds was 92%. The recognition rate of the new method was about 12% higher than methods using only an instantaneous spectrum. The results are also comparable with HMM-based methods, although those methods need to treat the time variance of an input vector series with more complicated computations.

  3. Cultivating Demand for the Arts: Arts Learning, Arts Engagement, and State Arts Policy. Summary

    Science.gov (United States)

    Zakaras, Laura; Lowell, Julia F.

    2008-01-01

    The findings summarized in this report are intended to shed light on what it means to cultivate demand for the arts, why it is necessary and important to cultivate this demand, and what state arts agencies (SAAs) and other arts and education policymakers can do to help. The research considered only the benchmark arts central to public policy:…

  4. Instruction of pattern recognition by MATLAB practice 1

    International Nuclear Information System (INIS)

    1999-06-01

    This book describes the pattern recognition by MATLAB practice. It includes possibility and limit of AI, introduction of pattern recognition a vector and matrix, basic status and a probability theory, a random variable and probability distribution, statistical decision theory, data-mining, gaussian mixture model, a nerve cell modeling such as Hebb's learning rule, LMS learning rule, genetic algorithm, dynamic programming and DTW, HMN on Markov model and HMM's three problems and solution, introduction of SVM with KKT condition and margin optimum, kernel trick and MATLAB practice.

  5. Type-2 fuzzy graphical models for pattern recognition

    CERN Document Server

    Zeng, Jia

    2015-01-01

    This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

  6. Algorithms for adaptive nonlinear pattern recognition

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary

    2011-09-01

    In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral

  7. Alterations in Resting-State Activity Relate to Performance in a Verbal Recognition Task

    Science.gov (United States)

    López Zunini, Rocío A.; Thivierge, Jean-Philippe; Kousaie, Shanna; Sheppard, Christine; Taler, Vanessa

    2013-01-01

    In the brain, resting-state activity refers to non-random patterns of intrinsic activity occurring when participants are not actively engaged in a task. We monitored resting-state activity using electroencephalogram (EEG) both before and after a verbal recognition task. We show a strong positive correlation between accuracy in verbal recognition and pre-task resting-state alpha power at posterior sites. We further characterized this effect by examining resting-state post-task activity. We found marked alterations in resting-state alpha power when comparing pre- and post-task periods, with more pronounced alterations in participants that attained higher task accuracy. These findings support a dynamical view of cognitive processes where patterns of ongoing brain activity can facilitate –or interfere– with optimal task performance. PMID:23785436

  8. Support for Arts Education. State Arts Agency Fact Sheet

    Science.gov (United States)

    National Assembly of State Arts Agencies, 2011

    2011-01-01

    Supporting lifelong learning in the arts is a top priority for state arts agencies. By supporting arts education in the schools, state arts agencies foster young imaginations, address core academic standards, and promote the critical thinking and creativity skills essential to a 21st century work force. State arts agencies also support…

  9. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2012-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions

  10. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2011-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

  11. Modeling the Process of Color Image Recognition Using ART2 Neural Network

    Directory of Open Access Journals (Sweden)

    Todor Petkov

    2015-09-01

    Full Text Available This paper thoroughly describes the use of unsupervised adaptive resonance theory ART2 neural network for the purposes of image color recognition of x-ray images and images taken by nuclear magnetic resonance. In order to train the network, the pixel values of RGB colors are regarded as learning vectors with three values, one for red, one for green and one for blue were used. At the end the trained network was tested by the values of pictures and determines the design, or how to visualize the converted picture. As a result we had the same pictures with colors according to the network. Here we use the generalized net to prepare a model that describes the process of the color image recognition.

  12. State Arts Agency Fact Sheet: Support for Arts Education

    Science.gov (United States)

    Online Submission, 2015

    2015-01-01

    This national overview of state arts agency grants and services for arts education includes summary statistics and geographic distribution. The fact sheet uses data from Final Descriptive Reports of state arts agency grant-making activities submitted annually to the National Assembly of State Arts Agencies (NASAA) and the National Endowment for…

  13. Applications of pattern recognition theory in diagnostics of nuclear power plants

    International Nuclear Information System (INIS)

    Cech, J.

    1982-01-01

    The questions are discussed of the application of the theory of pattern recognition in the diagnostics of nuclear power plants. For the future use of recognition systems in the diagnostics of nuclear power plants it is obvious that like with other complex systems, optimal models will have to be used which will organize the optimal recognition algorithm. The conclusion is presented that for the needs of nuclear power plants special systems will be more suitable for pattern recognition than digital computers which are flexible and adaptible but have a lower decision rate, an insufficient working memory, complicated programs, etc. (Z.M.)

  14. An Approach for Pattern Recognition of EEG Applied in Prosthetic Hand Drive

    Directory of Open Access Journals (Sweden)

    Xiao-Dong Zhang

    2011-12-01

    Full Text Available For controlling the prosthetic hand by only electroencephalogram (EEG, it has become the hot spot in robotics research to set up a direct communication and control channel between human brain and prosthetic hand. In this paper, the EEG signal is analyzed based on multi-complicated hand activities. And then, two methods of EEG pattern recognition are investigated, a neural prosthesis hand system driven by BCI is set up, which can complete four kinds of actions (arm’s free state, arm movement, hand crawl, hand open. Through several times of off-line and on-line experiments, the result shows that the neural prosthesis hand system driven by BCI is reasonable and feasible, the C-support vector classifiers-based method is better than BP neural network on the EEG pattern recognition for multi-complicated hand activities.

  15. Application of pattern recognition techniques to crime analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

    1976-08-15

    The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

  16. Pattern recognition approach to nondestructive evaluation of materials

    International Nuclear Information System (INIS)

    Chen, C.H.

    1987-01-01

    In this paper, a pattern recognition approach to the ultrasonic nondestructive evaluation of materials is examined. Emphasis is placed on identifying effective features from time and frequency domains, correlation functions and impulse responses to classify aluminum plate specimens into three major defect geometry categories: flat, angular cut and circular hole defects. A multi-stage classification procedure is developed which can further determine the angles and sizes for defect characterization and classification. The research clearly demonstrates that the pattern recognition approach can significantly improve the nondestructive material evaluation capability of the ultrasonic methods without resorting to the solution of highly complex mathematical inverse problems

  17. State of the States 2016: Arts Education State Policy Summary

    Science.gov (United States)

    Aragon, Stephanie

    2016-01-01

    The "State of the States 2016" summarizes state policies for arts education identified in statute or administrative code for all 50 states and the District of Columbia. Information is based on a comprehensive search of state education statute and codes on each state's relevant websites. Complete results from this review are available in…

  18. 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

  19. 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.

  20. Running Improves Pattern Separation during Novel Object Recognition.

    Science.gov (United States)

    Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

    2015-10-09

    Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

  1. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  2. State of the art

    International Nuclear Information System (INIS)

    Lederman, L.M.

    1983-01-01

    There is a large body of experience in high luminosity data taking in fixed target research. We try to consider a wide variety of high rate experiments which were limited by the detector (not by available beam) to a preset number of collisions per second. We then attempt to translate these state-of-the-art experiments to effective collider experiments. To this end, we extend the chosen detector to a comparison 4π collider detector operating near 1 TeV. There are several issues: (1) effective solid angle must be translated to approx. = 4π, (2) environments may be quite different, e.g., beam dump near fixed target or beam halo muons vs. collider backgrounds, (3) the multiplicity varies over the experiments selected and (4) we have to treat open vs closed geometries. The large variety of experiments selected is designed to average over the causes for detector limitation. Finally we chose detectors which have produced physics in order to gauge the state of the art

  3. Image processing and recognition for biological images.

    Science.gov (United States)

    Uchida, Seiichi

    2013-05-01

    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

  4. Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

    Science.gov (United States)

    Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

    2015-12-01

    Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. Unconstrained Iris Acquisition and Recognition Using COTS PTZ Camera

    Directory of Open Access Journals (Sweden)

    Venugopalan Shreyas

    2010-01-01

    Full Text Available Abstract Uniqueness of iris patterns among individuals has resulted in the ubiquity of iris recognition systems in virtual and physical spaces, at high security facilities around the globe. Traditional methods of acquiring iris patterns in commercial systems scan the iris when an individual is at a predetermined location in front of the scanner. Most state-of-the-art techniques for unconstrained iris acquisition in literature use expensive custom equipment and are composed of a multicamera setup, which is bulky, expensive, and requires calibration. This paper investigates a method of unconstrained iris acquisition and recognition using a single commercial off-the-shelf (COTS pan-tilt-zoom (PTZ camera, that is compact and that reduces the cost of the final system, compared to other proposed hierarchical multicomponent systems. We employ state-of-the-art techniques for face detection and a robust eye detection scheme using active shape models for accurate landmark localization. Additionally, our system alleviates the need for any calibration stage prior to its use. We present results using a database of iris images captured using our system, while operating in an unconstrained acquisition mode at 1.5 m standoff, yielding an iris diameter in the 150–200 pixels range.

  6. Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

    Science.gov (United States)

    Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

    2016-03-01

    In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats

  7. Threats of Password Pattern Leakage Using Smartwatch Motion Recognition Sensors

    Directory of Open Access Journals (Sweden)

    Jihun Kim

    2017-06-01

    Full Text Available Thanks to the development of Internet of Things (IoT technologies, wearable markets have been growing rapidly. Smartwatches can be said to be the most representative product in wearable markets, and involve various hardware technologies in order to overcome the limitations of small hardware. Motion recognition sensors are a representative example of those hardware technologies. However, smartwatches and motion recognition sensors that can be worn by users may pose security threats of password pattern leakage. In the present paper, passwords are inferred through experiments to obtain password patterns inputted by users using motion recognition sensors, and verification of the results and the accuracy of the results is shown.

  8. Quantitative EEG Applying the Statistical Recognition Pattern Method

    DEFF Research Database (Denmark)

    Engedal, Knut; Snaedal, Jon; Hoegh, Peter

    2015-01-01

    BACKGROUND/AIM: The aim of this study was to examine the discriminatory power of quantitative EEG (qEEG) applying the statistical pattern recognition (SPR) method to separate Alzheimer's disease (AD) patients from elderly individuals without dementia and from other dementia patients. METHODS...

  9. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

    Science.gov (United States)

    Swartz, R. Andrew

    2013-01-01

    This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

  10. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Wenjia Liu

    2013-01-01

    Full Text Available This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.

  11. Exploring How User Routine Affects the Recognition Performance of a Lock Pattern

    NARCIS (Netherlands)

    de Wide, Lisa; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2015-01-01

    To protect an Android smartphone against attackers, a lock pattern can be used. Nevertheless, shoulder-surfing and smudge attacks can be used to get access despite of this protection. To combat these attacks, biometric recognition can be added to the lock pattern, such that the lock-pattern

  12. Structural pattern recognition methods based on string comparison for fusion databases

    International Nuclear Information System (INIS)

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

    2008-01-01

    Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed

  13. Structural pattern recognition methods based on string comparison for fusion databases

    Energy Technology Data Exchange (ETDEWEB)

    Dormido-Canto, S. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain)], E-mail: sebas@dia.uned.es; Farias, G.; Dormido, R. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain); Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Ratta, G.; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain)

    2008-04-15

    Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed.

  14. Reactor noise analysis by statistical pattern recognition methods

    International Nuclear Information System (INIS)

    Howington, L.C.; Gonzalez, R.C.

    1976-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis is presented. 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, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system

  15. Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

    CERN Document Server

    Pisharady, Pramod Kumar; Poh, Loh Ai

    2014-01-01

    This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

  16. Pattern recognition methods for acoustic emission analysis

    International Nuclear Information System (INIS)

    Doctor, P.G.; Harrington, T.P.; Hutton, P.H.

    1979-07-01

    Models have been developed that relate the rate of acoustic emissions to structural integrity. The implementation of these techniques in the field has been hindered by the noisy environment in which the data must be taken. Acoustic emissions from noncritical sources are recorded in addition to those produced by critical sources, such as flaws. A technique is discussed for prescreening acoustic events and filtering out those that are produced by noncritical sources. The methodology that was investigated is pattern recognition. Three different pattern recognition techniques were applied to a data set that consisted of acoustic emissions caused by crack growth and acoustic signals caused by extraneous noise sources. Examination of the acoustic emission data presented has uncovered several features of the data that can provide a reasonable filter. Two of the most valuable features are the frequency of maximum response and the autocorrelation coefficient at Lag 13. When these two features and several others were combined with a least squares decision algorithm, 90% of the acoustic emissions in the data set were correctly classified. It appears possible to design filters that eliminate extraneous noise sources from flaw-growth acoustic emissions using pattern recognition techniques

  17. The time course of individual face recognition: A pattern analysis of ERP signals.

    Science.gov (United States)

    Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

    2016-05-15

    An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. A study on the extraction of feature variables for the pattern recognition for welding flaws

    International Nuclear Information System (INIS)

    Kim, J. Y.; Kim, C. H.; Kim, B. H.

    1996-01-01

    In this study, the researches classifying the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing, feature extraction, feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function classifier, the empirical Bayesian classifier. Also, the pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack, lack of penetration, lack of fusion, porosity, and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately teamed the neural network classifier is better than stastical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

  19. Data complexity in pattern recognition

    CERN Document Server

    Kam Ho Tin

    2006-01-01

    Machines capable of automatic pattern recognition have many fascinating uses. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book looks at data complexity and its role in shaping the theories and techniques in different disciplines

  20. Surveillance of a nuclear reactor core by use of a pattern recognition method

    International Nuclear Information System (INIS)

    Invernizzi, Michel.

    1982-07-01

    A pattern recognition system is described for the surveillance of a PWR reactor. This report contains four chapters. The first one succinctly deals with statistical pattern recognition principles. In the second chapter we show how a surveillance problem may be treated by pattern recognition and we present methods for surveillances (detection of abnormalities), controls (kind of running recognition) and diagnotics (kind of abnormality recognition). The third chapter shows a surveillance method of a nuclear plant. The signals used are the neutron noise observations made by the ionization chambers inserted in the reactor. Abnormality is defined in opposition with the training set witch is supposed to be an exhaustive summary of normality. In the fourth chapter we propose a scheme for an adaptative recognition and a method based on classes modelisations by hyper-spheres. This method has been tested on simulated training sets in two-dimensional feature spaces. It gives solutions to problems of non-linear separability [fr

  1. Processing emotional body expressions: state-of-the-art.

    Science.gov (United States)

    Enea, Violeta; Iancu, Sorina

    2016-10-01

    Processing emotional body expressions has become recently an important topic in affective and social neuroscience along with the investigation of facial expressions. The objective of the study is to review the literature on emotional body expressions in order to discuss the current state of knowledge on this topic and identify directions for future research. The following electronic databases were searched: PsychINFO, Ebsco, ERIC, ProQuest, Sagepub, and SCOPUS using terms such as "body," "bodily expression," "body perception," "emotions," "posture," "body recognition" and combinations of them. The synthesis revealed several research questions that were addressed in neuroimaging, electrophysiological and behavioral studies. Among them, one important question targeted the neural mechanisms of emotional processing of body expressions to specific subsections regarding the time course for the integration of emotional signals from face and body, as well as the role of context in the perception of emotional signals. Processing bodily expression of emotion is similar to processing facial expressions, and the holistic processing is extended to the whole person. The current state-of-the-art in processing emotional body expressions may lead to a better understanding of the underlying neural mechanisms of social behavior. At the end of the review, suggestions for future research directions are presented.

  2. Biometric verification based on grip-pattern recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.; Delp, Edward J.; Wong, Ping W.

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements is used to measure the grip pattern. An interface has been

  3. Biometric verification based on grip-pattern recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 £ 44 piezoresistive elements is used to measure the grip pattern. An interface has been

  4. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

    Science.gov (United States)

    Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

    2015-11-01

    This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

  5. Peptide Pattern Recognition for high-throughput protein sequence analysis and clustering

    DEFF Research Database (Denmark)

    Busk, Peter Kamp

    2017-01-01

    Large collections of protein sequences with divergent sequences are tedious to analyze for understanding their phylogenetic or structure-function relation. Peptide Pattern Recognition is an algorithm that was developed to facilitate this task but the previous version does only allow a limited...... number of sequences as input. I implemented Peptide Pattern Recognition as a multithread software designed to handle large numbers of sequences and perform analysis in a reasonable time frame. Benchmarking showed that the new implementation of Peptide Pattern Recognition is twenty times faster than...... the previous implementation on a small protein collection with 673 MAP kinase sequences. In addition, the new implementation could analyze a large protein collection with 48,570 Glycosyl Transferase family 20 sequences without reaching its upper limit on a desktop computer. Peptide Pattern Recognition...

  6. Higher-order neural network software for distortion invariant object recognition

    Science.gov (United States)

    Reid, Max B.; Spirkovska, Lilly

    1991-01-01

    The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

  7. The Art of the Renaissance Capitalist State

    Directory of Open Access Journals (Sweden)

    Rebeka Vidrih

    2007-12-01

    This article also highlights the fact that the concept of art developed in Florence – a city-state that played an important role in the early-capitalist world of the Renaissance, but never assumed a leading role like Venice and Genoa. »Art« was thus created through Florence’s efforts to demonstrate its equality and importance and, although it failed to achieve this in the field of the (capitalist economy, it at least succeeded in the field of the (absolutist state that was subordinate to this economy.

  8. Auditory orientation in crickets: Pattern recognition controls reactive steering

    Science.gov (United States)

    Poulet, James F. A.; Hedwig, Berthold

    2005-10-01

    Many groups of insects are specialists in exploiting sensory cues to locate food resources or conspecifics. To achieve orientation, bees and ants analyze the polarization pattern of the sky, male moths orient along the females' odor plume, and cicadas, grasshoppers, and crickets use acoustic signals to locate singing conspecifics. In comparison with olfactory and visual orientation, where learning is involved, auditory processing underlying orientation in insects appears to be more hardwired and genetically determined. In each of these examples, however, orientation requires a recognition process identifying the crucial sensory pattern to interact with a localization process directing the animal's locomotor activity. Here, we characterize this interaction. Using a sensitive trackball system, we show that, during cricket auditory behavior, the recognition process that is tuned toward the species-specific song pattern controls the amplitude of auditory evoked steering responses. Females perform small reactive steering movements toward any sound patterns. Hearing the male's calling song increases the gain of auditory steering within 2-5 s, and the animals even steer toward nonattractive sound patterns inserted into the speciesspecific pattern. This gain control mechanism in the auditory-to-motor pathway allows crickets to pursue species-specific sound patterns temporarily corrupted by environmental factors and may reflect the organization of recognition and localization networks in insects. localization | phonotaxis

  9. Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    2008-06-01

    Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

  10. Creating symmetry the artful mathematics of wallpaper patterns

    CERN Document Server

    Farris, Frank A

    2015-01-01

    This lavishly illustrated book provides a hands-on, step-by-step introduction to the intriguing mathematics of symmetry. Instead of breaking up patterns into blocks-a sort of potato-stamp method-Frank Farris offers a completely new waveform approach that enables you to create an endless variety of rosettes, friezes, and wallpaper patterns: dazzling art images where the beauty of nature meets the precision of mathematics. Featuring more than 100 stunning color illustrations and requiring only a modest background in math, Creating Symmetry begins by addressing the enigma of a simple curve, who

  11. Fuzzy tree automata and syntactic pattern recognition.

    Science.gov (United States)

    Lee, E T

    1982-04-01

    An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

  12. Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

    Directory of Open Access Journals (Sweden)

    Cai Wingfield

    2017-09-01

    Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

  13. 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...

  14. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  15. Pattern recognition approach to quantify the atomic structure of graphene

    DEFF Research Database (Denmark)

    Kling, Jens; Vestergaard, Jacob Schack; Dahl, Anders Bjorholm

    2014-01-01

    We report a pattern recognition approach to detect the atomic structure in high-resolution transmission electron microscopy images of graphene. The approach provides quantitative information such as carbon-carbon bond lengths and bond length variations on a global and local scale alike. © 2014...

  16. Pattern recognition neural-net by spatial mapping of biology visual field

    Science.gov (United States)

    Lin, Xin; Mori, Masahiko

    2000-05-01

    The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

  17. Quantum pattern recognition with multi-neuron interactions

    Science.gov (United States)

    Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

    2018-03-01

    We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

  18. Optimal pattern synthesis for speech recognition based on principal component analysis

    Science.gov (United States)

    Korsun, O. N.; Poliyev, A. V.

    2018-02-01

    The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

  19. An inverse problem approach to pattern recognition in industry

    Directory of Open Access Journals (Sweden)

    Ali Sever

    2015-01-01

    Full Text Available Many works have shown strong connections between learning and regularization techniques for ill-posed inverse problems. A careful analysis shows that a rigorous connection between learning and regularization for inverse problem is not straightforward. In this study, pattern recognition will be viewed as an ill-posed inverse problem and applications of methods from the theory of inverse problems to pattern recognition are studied. A new learning algorithm derived from a well-known regularization model is generated and applied to the task of reconstruction of an inhomogeneous object as pattern recognition. Particularly, it is demonstrated that pattern recognition can be reformulated in terms of inverse problems defined by a Riesz-type kernel. This reformulation can be employed to design a learning algorithm based on a numerical solution of a system of linear equations. Finally, numerical experiments have been carried out with synthetic experimental data considering a reasonable level of noise. Good recoveries have been achieved with this methodology, and the results of these simulations are compatible with the existing methods. The comparison results show that the Regularization-based learning algorithm (RBA obtains a promising performance on the majority of the test problems. In prospects, this method can be used for the creation of automated systems for diagnostics, testing, and control in various fields of scientific and applied research, as well as in industry.

  20. 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...

  1. Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

    Science.gov (United States)

    Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

    2017-11-26

    Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

  2. Pattern Recognition-Based Analysis of COPD in CT

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs

    recognition part is used to turn the texture measures, measured in a CT image of the lungs, into a quantitative measure of disease. This is done by applying a classifier that is trained on a training set of data examples with known lung tissue patterns. Different classification systems are considered, and we...... will in particular use the pattern recognition concepts of supervised learning, multiple instance learning, and dissimilarity representation-based classification. The proposed texture-based measures are applied to CT data from two different sources, one comprising low dose CT slices from subjects with manually...... annotated regions of emphysema and healthy tissue, and one comprising volumetric low dose CT images from subjects that are either healthy or suffer from COPD. Several experiments demonstrate that it is clearly beneficial to take the lung tissue texture into account when classifying or quantifying emphysema...

  3. Spatial pattern recognition of seismic events in South West Colombia

    Science.gov (United States)

    Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

    2013-09-01

    Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

  4. Sub-pattern based multi-manifold discriminant analysis for face recognition

    Science.gov (United States)

    Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

    2018-04-01

    In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

  5. Optimal spatiotemporal representation of multichannel EEG for recognition of brain states associated with distinct visual stimulus

    Science.gov (United States)

    Hramov, Alexander; Musatov, Vyacheslav Yu.; Runnova, Anastasija E.; Efremova, Tatiana Yu.; Koronovskii, Alexey A.; Pisarchik, Alexander N.

    2018-04-01

    In the paper we propose an approach based on artificial neural networks for recognition of different human brain states associated with distinct visual stimulus. Based on the developed numerical technique and the analysis of obtained experimental multichannel EEG data, we optimize the spatiotemporal representation of multichannel EEG to provide close to 97% accuracy in recognition of the EEG brain states during visual perception. Different interpretations of an ambiguous image produce different oscillatory patterns in the human EEG with similar features for every interpretation. Since these features are inherent to all subjects, a single artificial network can classify with high quality the associated brain states of other subjects.

  6. Pattern recognition receptors and the inflammasome in kidney disease

    NARCIS (Netherlands)

    Leemans, Jaklien C.; Kors, Lotte; Anders, Hans-Joachim; Florquin, Sandrine

    2014-01-01

    Toll-like receptors (TLRs) and nucleotide-binding oligomerization domain receptors (NLRs) are families of pattern recognition receptors that, together with inflammasomes, sense and respond to highly conserved pathogen motifs and endogenous molecules released upon cell damage or stress. Evidence

  7. Deep Learning For Sequential Pattern Recognition

    OpenAIRE

    Safari, Pooyan

    2013-01-01

    Projecte realitzat en el marc d’un programa de mobilitat amb la Technische Universität München (TUM) In recent years, deep learning has opened a new research line in pattern recognition tasks. It has been hypothesized that this kind of learning would capture more abstract patterns concealed in data. It is motivated by the new findings both in biological aspects of the brain and hardware developments which have made the parallel processing possible. Deep learning methods come along with ...

  8. Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

    Science.gov (United States)

    Juday, Richard D. (Editor)

    1988-01-01

    The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

  9. 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.

  10. State-of-the-art inventory

    NARCIS (Netherlands)

    Verhagen, H.J.; Van Gerven, K.A.J.; Akkerman, G.J.

    2005-01-01

    The present report provides a state-of-the-art inventory of relevant information and technical concepts for the ComCoast project, being the first phase of the research stages of Work Package 3 (WP3). This project was assigned to Royal Haskoning by CUR. The information scan was set-up in a systematic

  11. Multimodal Dialogue Management - State of the art

    NARCIS (Netherlands)

    Bui Huu Trung, B.H.T.

    This report is about the state of the art in dialogue management. We first introduce an overview of a multimodal dialogue system and its components. Second, four main approaches to dialogue management are described (finite-state and frame-based, information-state based and probabilistic, plan-based,

  12. Greenhouse mechanization: State of the art and future perspective

    NARCIS (Netherlands)

    Henten, van E.

    2006-01-01

    This paper reviews the state of the art and future perspective of greenhouse mechanization. Driving forces for mechanization are identified. Dutch greenhouse crop production is used as an example. Analysis of a generic crop production process combined with a review of the state of the art in

  13. Fuel cells: state of the art

    International Nuclear Information System (INIS)

    Campanari, S.; Casalegno, A.

    2007-01-01

    This paper deals with the main features at present state-of-the-art fuel cell and hybrid cycle technologies, discussing their actual performance, possible applications, market entry perspectives and potential development [it

  14. Towards discrete wavelet transform-based human activity recognition

    Science.gov (United States)

    Khare, Manish; Jeon, Moongu

    2017-06-01

    Providing accurate recognition of human activities is a challenging problem for visual surveillance applications. In this paper, we present a simple and efficient algorithm for human activity recognition based on a wavelet transform. We adopt discrete wavelet transform (DWT) coefficients as a feature of human objects to obtain advantages of its multiresolution approach. The proposed method is tested on multiple levels of DWT. Experiments are carried out on different standard action datasets including KTH and i3D Post. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures. The proposed method is found to have better recognition accuracy in comparison to the state-of-the-art methods.

  15. Grip-pattern recognition: Applied to a smart gun

    NARCIS (Netherlands)

    Shang, X.

    2008-01-01

    In our work the verification performance of a biometric recognition system based on grip patterns, as part of a smart gun for use by the police ocers, has been investigated. The biometric features are extracted from a two-dimensional pattern of the pressure, exerted on the grip of a gun by the hand

  16. Heteronomy in the arts field: state funding and British arts organizations.

    Science.gov (United States)

    Alexander, Victoria D

    2018-03-01

    For Bourdieu, the field of cultural production is comprised of an autonomous and a heteronomous sector. A heteronomous sector is one that is interpenetrated by the commercial field. I discuss an arena that, until recently, was part of the relatively autonomous sector in the field of cultural production - the supported arts sector in the United Kingdom - and argue that it became more heteronomous, due to the penetration by the state. Heteronomy due to the commercial field is present but secondary to, and driven by, the actions of the state. Political parties' attempts to diffuse and legitimate a particular economic ideology have led to state demands that arts institutions adopt neoliberal business practices in exchange for funding. Government giving to the arts, previously at arm's length, proved to be a Faustian bargain that demanded significant repayment in the form of lost autonomy. Coercive pressures from the state, enacted over time, show how the domination of one field over another can occur, even when the domination is resisted. © London School of Economics and Political Science 2017.

  17. Simultaneous pattern recognition and track fitting by the Kalman filtering method

    International Nuclear Information System (INIS)

    Billoir, P.

    1990-01-01

    A progressive pattern recognition algorithm based on the Kalman filtering method has been tested. The algorithm starts from a small track segment or from a fitted track of a neighbouring detector, then extends the candidate tracks by adding measured points one by one. The fitted parameters and weight matrix of the candidate track are updated when adding a point, and give an increasing precision on prediction of the next point. Thus, pattern recognition and track fitting can be accomplished simultaneously. The method has been implemented and tested for track reconstruction for the vertex detector of the ZEUS experiment at DESY. Detailed procedures of the method and its performance are presented. Its flexibility is described as well. (orig.)

  18. Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

    CERN Document Server

    Blacknell, David

    2013-01-01

    The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

  19. Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

    Science.gov (United States)

    Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

    2018-01-01

    Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

  20. State of the art undersøgelse

    DEFF Research Database (Denmark)

    Nielsen, Nils

    1998-01-01

    Dette skrift omhandler nogle af de erfaringer der til dato er opnået i forbindelse med standby projektets udførelse. Hovedtemaet er en “State of the art undersøgelse” der omhandler standby-spændingsforsyninger, samt komponenter der kan anvendes til konstruktion af dem......Dette skrift omhandler nogle af de erfaringer der til dato er opnået i forbindelse med standby projektets udførelse. Hovedtemaet er en “State of the art undersøgelse” der omhandler standby-spændingsforsyninger, samt komponenter der kan anvendes til konstruktion af dem...

  1. State of the art in marketing hospital foodservice departments.

    Science.gov (United States)

    Pickens, C W; Shanklin, C W

    1985-11-01

    The purposes of this study were to identify the state of the art relative to the utilization of marketing techniques within hospital foodservice departments throughout the United States and to determine whether any relationships existed between the degree of utilization of marketing techniques and selected demographic characteristics of the foodservice administrators and/or operations. A validated questionnaire was mailed to 600 randomly selected hospital foodservice administrators requesting information related to marketing in their facilities. Forty-five percent of the questionnaires were returned and analyzed for frequency of response and significant relationship between variables. Chi-square was used for nominal data and Spearman rho for ranked data. Approximately 73% of the foodservice administrators stated that marketing was extremely important in the success of a hospital foodservice department. Respondents (79%) further indicated that marketing had become more important in their departments in the past 2 years. Departmental records, professional journals, foodservice suppliers, observation, and surveys were the sources most often used to obtain marketing data, a responsibility generally assumed by the foodservice director (86.2%). Merchandising, public relations, and word-of-mouth reputation were regarded as the most important aspects of marketing. Increased sales, participation, good will, departmental recognition, and employee satisfaction were used most frequently to evaluate the success of implemented marketing techniques. Marketing audits as a means of evaluating the success of marketing were used to a limited extent by the respondents.

  2. 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.

  3. Application of digital pattern-less molding technology to produce art casting

    Directory of Open Access Journals (Sweden)

    Chen Li1

    2014-11-01

    Full Text Available Compared with the conventional casting process, digital pattern-less casting technology has many advantages such as good machining accuracy, a short processing cycle, and low production cost. It is a new rapid manufacturing technology for castings, integrated with CAD/CAM, casting, CNC machining and many other advanced technologies. With this digital casting technology, no pattern is needed for making molds; it is precise, flexible, and green. Usually, art castings have complex structures and are made in small batches or even made in a single-piece, especially for large-sized art castings. So it has the shortcomings of high cost, low efficiency and long time for making a pattern to produce art castings with the conventional casting processes. However, the digital pattern-less casting technology can be applied to fabricate art castings, since it can greatly shorten the manufacturing cycle and lower the production cost, thus having a very good prospect. In this study, based on the digital pattern-less casting technology, a plaque casting with artistic Chinese characters (a Chinese poem was designed and manufactured, and the production process was demonstrated in detail.

  4. Artificial intelligence tools for pattern recognition

    Science.gov (United States)

    Acevedo, Elena; Acevedo, Antonio; Felipe, Federico; Avilés, Pedro

    2017-06-01

    In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

  5. Where is your state of the art?

    Science.gov (United States)

    Ríos Gaona, Manuel

    2015-04-01

    Beyond the purposes of publishing, questioning and/or hypothesizing, every research has the noble aim to quench the constant human need of pushing farther away the boundaries of knowledge, may such frontier exist. The state of the art is the generic expression coined to limit the whereabouts of any particular knowledge. We use it just like a compass, it tells us how far we are, what has been done and where we should go. Take for instance quantum field theory, the state of the art in particle physics will tell you that everything that exists in this universe is made of bosons, quarks and leptons. What!?. Hold on, I was taught (and luckily maybe you weren't) that the fundamental particles were electrons, neutrons and protons, right?. Indeed, that is the state of the art but from almost one century ago. So, if I may ask... where is your state of the art? This is not about quantum physics; it is not even about hydrology; it is about everything. Today, everybody doing or not a PhD fiercely believes that their research is important, extremely unique, life changing (and help us God if we are wrong); but how can you be so sure that what you do, isn't already done?. We live in a modern world, cool environmental scientists now have tagged this era as the Anthropocene; globalization is everywhere and of course knowledge has not escaped to it. Not only knowledge is now global but is totally diversified, any crazy idea you can think of (or actually you can't) it is very likely that somebody already has his/hers hands on it. Nevertheless, this is a good thing, isn't it?. Well, that is the whole point. Every time I should write my research's state of the art, I always get overwhelmed because it actually is pretty difficult to establish, and later when I think I get it, it seems that I am solving issues that somebody already bothered to solve 30 years ago. Therefore, does it really have some purpose to be swimming in a huge pool of knowledge, not knowing where exactly I am? or

  6. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Lahiru Iddamalgoda; Partha Sarathi Das; Partha Sarathi Das; Achala Aponso; Vijayaraghava Seshadri Sundararajan; Prashanth Suravajhala; Prashanth Suravajhala; Prashanth Suravajhala; Jayaraman K Valadi

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern r...

  7. Action recognition using mined hierarchical compound features.

    Science.gov (United States)

    Gilbert, Andrew; Illingworth, John; Bowden, Richard

    2011-05-01

    The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical

  8. State of the Art in the Cramer Classification Scheme and ...

    Science.gov (United States)

    Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD. Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD.

  9. Granular neural networks, pattern recognition and bioinformatics

    CERN Document Server

    Pal, Sankar K; Ganivada, Avatharam

    2017-01-01

    This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinf...

  10. Mechanisms of Expression and Internalisation of FIBCD1; a novel Pattern Recognition Receptor in the Gut Mucosa

    DEFF Research Database (Denmark)

    Hammond, Mark; Schlosser, Anders; Dubey, Lalit Kumar

    2012-01-01

    is a carbohydrate recognition domain also expressed by the ficolins, which are pattern recognition molecules that activate the complement system via the lectin pathway. Chitin is a highly ace¬tylated homopolymer of β-1,4-N-acetyl-glucosamine carbohydrate found abundantly in nature in organisms such as fungi...... pattern recognition receptor that binds chitin and directs acetylated structures for de¬gradation in the endosome via clathrin-mediated endocytosis. The localisation of FIBCD1 in the intestinal mucosal epithelia points towards a functional role in innate immunity and/or gut homeostasis....

  11. Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

    Directory of Open Access Journals (Sweden)

    MORARIU, N.

    2007-04-01

    Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

  12. Guide to state-of-the-art electron devices

    CERN Document Server

    2013-01-01

    Concise, high quality and comparative overview of state-of-the-art electron device development, manufacturing technologies and applications Guide to State-of-the-Art Electron Devices marks the 60th anniversary of the IEEE Electron Devices Committee and the 35th anniversary of the IEEE Electron Devices Society, as such it defines the state-of-the-art of electron devices, as well as future directions across the entire field. Spans full range of electron device types such as photovoltaic devices, semiconductor manufacturing and VLSI technology and circuits, covered by IEEE Electron and Devices Society Contributed by internationally respected members of the electron devices community A timely desk reference with fully-integrated colour and a unique lay-out with sidebars to highlight the key terms Discusses the historical developments and speculates on future trends to give a more rounded picture of the topics covered A valuable resource R&D managers; engineers in the semiconductor industry; applied scientists...

  13. 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.

  14. Recognition of neural brain activity patterns correlated with complex motor activity

    Science.gov (United States)

    Kurkin, Semen; Musatov, Vyacheslav Yu.; Runnova, Anastasia E.; Grubov, Vadim V.; Efremova, Tatyana Yu.; Zhuravlev, Maxim O.

    2018-04-01

    In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.

  15. The state-of-the-art of ART sealants.

    Science.gov (United States)

    Frencken, Jo E

    2014-03-01

    Sealing caries-prone pits and fissure systems is an effective caries-preventive measure. There are basically two types of sealant materials: glass-ionomer and resin-based materials. Low- and medium-viscosity glass-ionomers were initially used and showed a low level of retention. With the advent of the ART approach in the mid-nineties, high-viscosity glass-ionomers were introduced as sealant material and the retention rate of ART sealants increased substantially. As the effectiveness of a sealant is measured by its capacity to prevent (dentine) carious lesion development, sealant retention is considered a surrogate endpoint. The ART sealant protocol is described. Systematic reviews and meta-analysis covering low- medium- and high-viscosity glass-ionomer (ART) sealants have concluded that there is no evidence that either glass-ionomer or resin-based sealants prevent dentine carious lesions better. The annual dentine carious lesion development in teeth with high-viscosity glass-ionomer ART sealants over the first three years is 1%. These ART sealants have a high capacity of preventing carious lesion development. Because no electricity and running water is required, ART sealants can be placed both inside and outside the dental surgery. High-viscosity glass-ionomer ART sealants can be used alongside resin-based sealants.41:119-124

  16. State of the art in video system performance

    Science.gov (United States)

    Lewis, Michael J.

    1990-01-01

    The closed circuit television (CCTV) system that is onboard the Space Shuttle has the following capabilities: camera, video signal switching and routing unit (VSU); and Space Shuttle video tape recorder. However, this system is inadequate for use with many experiments that require video imaging. In order to assess the state-of-the-art in video technology and data storage systems, a survey was conducted of the High Resolution, High Frame Rate Video Technology (HHVT) products. The performance of the state-of-the-art solid state cameras and image sensors, video recording systems, data transmission devices, and data storage systems versus users' requirements are shown graphically.

  17. The state-of-the-art of ART restorations.

    Science.gov (United States)

    Frencken, Jo E

    2014-04-01

    ART is less anxiety- and pain-provoking than traditional restorative treatments; administration of local anaesthesia is rarely required. Systematic reviews have provided evidence of the high level of effectiveness of high-viscosity glass-ionomer ART restoration in restoring single-surface cavities, both in primary and permanent posterior teeth, but its survival rates in restoring multiple-surface cavities in primary posterior teeth needs to be improved. Insufficient information is available regarding the survival rates of multiple-surface ART restorations in permanent teeth. Evidence from these reviews indicates no difference in the survival rates of single-surface high-viscosity glass-ionomer ART restorations and amalgam restorations in primary and permanent posterior teeth. Where indicated, high-viscosity glass-ionomer ART restorations can be used alongside traditional restorations. ART provides a much more acceptable introduction to dental restorative care than the traditional 'injection, drill and fill'.

  18. 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

  19. Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

    Science.gov (United States)

    Carpenter, Gail A.

    1997-11-01

    A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network.

  20. MCAW-DB: A glycan profile database capturing the ambiguity of glycan recognition patterns.

    Science.gov (United States)

    Hosoda, Masae; Takahashi, Yushi; Shiota, Masaaki; Shinmachi, Daisuke; Inomoto, Renji; Higashimoto, Shinichi; Aoki-Kinoshita, Kiyoko F

    2018-05-11

    Glycan-binding protein (GBP) interaction experiments, such as glycan microarrays, are often used to understand glycan recognition patterns. However, oftentimes the interpretation of glycan array experimental data makes it difficult to identify discrete GBP binding patterns due to their ambiguity. It is known that lectins, for example, are non-specific in their binding affinities; the same lectin can bind to different monosaccharides or even different glycan structures. In bioinformatics, several tools to mine the data generated from these sorts of experiments have been developed. These tools take a library of predefined motifs, which are commonly-found glycan patterns such as sialyl-Lewis X, and attempt to identify the motif(s) that are specific to the GBP being analyzed. In our previous work, as opposed to using predefined motifs, we developed the Multiple Carbohydrate Alignment with Weights (MCAW) tool to visualize the state of the glycans being recognized by the GBP under analysis. We previously reported on the effectiveness of our tool and algorithm by analyzing several glycan array datasets from the Consortium of Functional Glycomics (CFG). In this work, we report on our analysis of 1081 data sets which we collected from the CFG, the results of which we have made publicly and freely available as a database called MCAW-DB. We introduce this database, its usage and describe several analysis results. We show how MCAW-DB can be used to analyze glycan-binding patterns of GBPs amidst their ambiguity. For example, the visualization of glycan-binding patterns in MCAW-DB show how they correlate with the concentrations of the samples used in the array experiments. Using MCAW-DB, the patterns of glycans found to bind to various GBP-glycan binding proteins are visualized, indicating the binding "environment" of the glycans. Thus, the ambiguity of glycan recognition is numerically represented, along with the patterns of monosaccharides surrounding the binding region. The

  1. Threshold models of recognition and the recognition heuristic

    Directory of Open Access Journals (Sweden)

    Edgar Erdfelder

    2011-02-01

    Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

  2. 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)

  3. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  4. One Step Closer to the Marketplace for State-of-the-Art Wind Turbine

    Science.gov (United States)

    Drivetrain | News | NREL One Step Closer to the Marketplace for State-of-the-Art Wind Turbine Drivetrain One Step Closer to the Marketplace for State-of-the-Art Wind Turbine Drivetrain April 1, 2016 modeling, and testing in state-of-the-art facilities designed to put the drivetrain through its paces

  5. RECOG-ORNL, Pattern Recognition Data Analysis

    International Nuclear Information System (INIS)

    Begovich, C.L.; Larson, N.M.

    2000-01-01

    Description of program or function: RECOG-ORNL, a general-purpose pattern recognition code, is a modification of the RECOG program, written at Lawrence Livermore National Laboratory. RECOG-ORNL contains techniques for preprocessing, analyzing, and displaying data, and for unsupervised and supervised learning. Data preprocessing routines transform the data into useful representations by auto-calling, selecting important variables, and/or adding products or transformations of the variables of the data set. Data analysis routines use correlations to evaluate the data and interrelationships among the data. Display routines plot the multidimensional patterns in two dimensions or plot histograms, patterns, or one variable versus another. Unsupervised learning techniques search for classes contained inherently in the data. Supervised learning techniques use known information about some of the data to generate predicted properties for an unknown set

  6. Performance Study of the First 2D Prototype of Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    Energy Technology Data Exchange (ETDEWEB)

    Deptuch, Gregory [Fermilab; Hoff, James [Fermilab; Jindariani, Sergo [Fermilab; Liu, Tiehui [Fermilab; Olsen, Jamieson [Fermilab; Tran, Nhan [Fermilab; Joshi, Siddhartha [Northwestern U.; Li, Dawei [Northwestern U.; Ogrenci-Memik, Seda [Northwestern U.

    2017-09-24

    Extremely fast pattern recognition capabilities are necessary to find and fit billions of tracks at the hardware trigger level produced every second anticipated at high luminosity LHC (HL-LHC) running conditions. Associative Memory (AM) based approaches for fast pattern recognition have been proposed as a potential solution to the tracking trigger. However, at the HL-LHC, there is much less time available and speed performance must be improved over previous systems while maintaining a comparable number of patterns. The Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) Project aims to achieve the target pattern density and performance goal using 3DIC technology. The first step taken in the VIPRAM work was the development of a 2D prototype (protoVIPRAM00) in which the associative memory building blocks were designed to be compatible with the 3D integration. In this paper, we present the results from extensive performance studies of the protoVIPRAM00 chip in both realistic HL-LHC and extreme conditions. Results indicate that the chip operates at the design frequency of 100 MHz with perfect correctness in realistic conditions and conclude that the building blocks are ready for 3D stacking. We also present performance boundary characterization of the chip under extreme conditions.

  7. Pattern Recognition as a Human Centered non-Euclidean Problem

    NARCIS (Netherlands)

    Duin, R.P.W.

    2010-01-01

    Regularities in the world are human defined. Patterns in the observed phenomena are there because we define and recognize them as such. Automatic pattern recognition tries to bridge the gap between human judgment and measurements made by artificial sensors. This is done in two steps: representation

  8. Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

    Directory of Open Access Journals (Sweden)

    Md. Abdullah-al-mamun

    2015-08-01

    Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

  9. Orientation and phase mapping in the transmission electron microscope using precession-assisted diffraction spot recognition: state-of-the-art results.

    Science.gov (United States)

    Viladot, D; Véron, M; Gemmi, M; Peiró, F; Portillo, J; Estradé, S; Mendoza, J; Llorca-Isern, N; Nicolopoulos, S

    2013-10-01

    A recently developed technique based on the transmission electron microscope, which makes use of electron beam precession together with spot diffraction pattern recognition now offers the possibility to acquire reliable orientation/phase maps with a spatial resolution down to 2 nm on a field emission gun transmission electron microscope. The technique may be described as precession-assisted crystal orientation mapping in the transmission electron microscope, precession-assisted crystal orientation mapping technique-transmission electron microscope, also known by its product name, ASTAR, and consists in scanning the precessed electron beam in nanoprobe mode over the specimen area, thus producing a collection of precession electron diffraction spot patterns, to be thereafter indexed automatically through template matching. We present a review on several application examples relative to the characterization of microstructure/microtexture of nanocrystalline metals, ceramics, nanoparticles, minerals and organics. The strengths and limitations of the technique are also discussed using several application examples. ©2013 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

  10. Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

    Directory of Open Access Journals (Sweden)

    Tomasz Ciszewski

    2006-01-01

    Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

  11. The State of Comic Art Bibliography in North America

    Directory of Open Access Journals (Sweden)

    Michael Rhode

    2010-08-01

    Full Text Available Within the past two decades, several American bibliographies of comic art have been published to aid in research on comics and cartooning. Professor John Lent’s ten-volume Comic Art Bibliographies is one of the largest such projects and he began it with a self-published volume in 1986. Librarian Randy Scott published The Comic Art Collection Catalog: An Author, Artist, Title and Subject Catalog Of The Comic Art Collection, Special Collections Division, Michigan State University Libraries, whi...

  12. The memory state heuristic: A formal model based on repeated recognition judgments.

    Science.gov (United States)

    Castela, Marta; Erdfelder, Edgar

    2017-02-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. State of the art in microfabrication

    NARCIS (Netherlands)

    Schmitz, Jurriaan

    2014-01-01

    In this review paper the state of the art in microfabrication is presented. The focus is on trends in integrated circuit fabrication by mainstream industrial players. The article starts with Moore’s Law, describing its inception as well as the evolution of Moore’s metric of the number of components

  14. A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Zhenhua Zhang

    2013-01-01

    Full Text Available We present dynamic interval-valued intuitionistic fuzzy sets (DIVIFS, which can improve the recognition accuracy when they are applied to pattern recognition. By analyzing the degree of hesitancy, we propose some DIVIFS models from intuitionistic fuzzy sets (IFS and interval-valued IFS (IVIFS. And then we present a novel ranking condition on the distance of IFS and IVIFS and introduce some distance measures of DIVIFS satisfying the ranking condition. Finally, a pattern recognition example applied to medical diagnosis decision making is given to demonstrate the application of DIVIFS and its distances. The simulation results show that the DIVIFS method is more comprehensive and flexible than the IFS method and the IVIFS method.

  15. Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

    Science.gov (United States)

    Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

    2018-01-01

    Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

  16. Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

    Science.gov (United States)

    Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

    2018-03-12

    Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

  17. Natural Cytotoxicity Receptors: Pattern Recognition and Involvement of Carbohydrates

    Directory of Open Access Journals (Sweden)

    Angel Porgador

    2005-01-01

    Full Text Available Natural cytotoxicity receptors (NCRs, expressed by natural killer (NK cells, trigger NK lysis of tumor and virus-infected cells on interaction with cell-surface ligands of these target cells. We have determined that viral hemagglutinins expressed on the surface of virus-infected cells are involved in the recognition by the NCRs, NKp44 and NKp46. Recognition of tumor cells by the NCRs NKp30 and NKp46 involves heparan sulfate epitopes expressed on the tumor cell membrane. Our studies provide new evidence for the identity of the ligands for NCRs and indicate that a broader definition should be applied to pathological patterns recognized by innate immune receptors. Since nonmicrobial endogenous carbohydrate structures contribute significantly to this recognition, there is an imperative need to develop appropriate tools for the facile sequencing of carbohydrate moieties.

  18. Introduction of pattern recognition by MATLAB practice 2

    International Nuclear Information System (INIS)

    1999-06-01

    The contents of this book starts introduction and examples of pattern recognition. This book describes a vector and matrix, basic statistics and a probability distribution, statistical decision theory and probability density function, liner shunt, vector quantizing and clustering GMM, PCA and KL conversion, LDA, ID 3, a nerve cell modeling, HMM, SVM and Ada boost. It has direction of MATLAB in the appendix.

  19. Do pattern recognition skills transfer across sports? A preliminary analysis.

    Science.gov (United States)

    Smeeton, Nicholas J; Ward, Paul; Williams, A Mark

    2004-02-01

    The ability to recognize patterns of play is fundamental to performance in team sports. While typically assumed to be domain-specific, pattern recognition skills may transfer from one sport to another if similarities exist in the perceptual features and their relations and/or the strategies used to encode and retrieve relevant information. A transfer paradigm was employed to compare skilled and less skilled soccer, field hockey and volleyball players' pattern recognition skills. Participants viewed structured and unstructured action sequences from each sport, half of which were randomly represented with clips not previously seen. The task was to identify previously viewed action sequences quickly and accurately. Transfer of pattern recognition skill was dependent on the participant's skill, sport practised, nature of the task and degree of structure. The skilled soccer and hockey players were quicker than the skilled volleyball players at recognizing structured soccer and hockey action sequences. Performance differences were not observed on the structured volleyball trials between the skilled soccer, field hockey and volleyball players. The skilled field hockey and soccer players were able to transfer perceptual information or strategies between their respective sports. The less skilled participants' results were less clear. Implications for domain-specific expertise, transfer and diversity across domains are discussed.

  20. Human activity recognition from wireless sensor network data: benchmark and software

    NARCIS (Netherlands)

    van Kasteren, T.L.M.; Englebienne, G.; Kröse, B.J.A.; Chen, L.; Nugent, C.; Biswas, J.; Hoey, J.

    2011-01-01

    Although activity recognition is an active area of research no common benchmark for evaluating the performance of activity recognition methods exists. In this chapter we present the state of the art probabilistic models used in activity recognition and show their performance on several real world

  1. Defect Pattern Recognition Based on Partial Discharge Characteristics of Oil-Pressboard Insulation for UHVDC Converter Transformer

    Directory of Open Access Journals (Sweden)

    Wen Si

    2018-03-01

    Full Text Available The ultra high voltage direct current (UHVDC transmission system has advantages in delivering electrical energy over long distance at high capacity. UHVDC converter transformer is a key apparatus and its insulation state greatly affects the safe operation of the transmission system. Partial discharge (PD characteristics of oil-pressboard insulation under combined AC-DC voltage are the foundation for analyzing the insulation state of UHVDC converter transformers. The defect pattern recognition based on PD characteristics is an important part of the state monitoring of converter transformers. In this paper, PD characteristics are investigated with the established experimental platform of three defect models (needle-plate, surface discharge and air gap under 1:1 combined AC-DC voltage. The different PD behaviors of three defect models are discussed and explained through simulation of electric field strength distribution and discharge mechanism. For the recognition of defect types when multiple types of sources coexist, the Random Forests algorithm is used for recognition. In order to reduce the computational layer and the loss of information caused by the extraction of traditional features, the preprocessed single PD pulses and phase information are chosen to be the features for learning and test. Zero-padding method is discussed for normalizing the features. Based on the experimental data, Random Forests and Least Squares Support Vector Machine are compared in the performance of computing time, recognition accuracy and adaptability. It is proved that Random Forests is more suitable for big data analysis.

  2. State-of-the-art of home networking

    NARCIS (Netherlands)

    Koonen, A.M.J.; Popov, M.

    2012-01-01

    To introduce the Symposium on "Indoor Optical Networks: a Promising Way to a Converged Service Delivery", this presentation will give a brief overview of state-of-the-art home networking architectures, technologies and applications covering both technical and techno-economic aspects.

  3. State Toleration, Religious Recognition and Equality

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2013-01-01

    In debates about multiculturalism, it is widely claimed that ‘toleration is not enough’ and that we need to go ‘beyond toleration’ to some form of politics of recognition in order to satisfactorily address contemporary forms of cultural diversity (e.g. the presence in Europe of Muslim minorities...... a conceptual question of whether the relation between states and minorities can be categoriseized in terms of recognition or toleration, but about a normative question of whether and how toleration and recognition secures equality. When toleration is inadequate, this is often because it institutionaliseizes...... and upholds specific inequalities. But politics of recognition may equally well institute inequalities, and in such cases unequal recognition may not be preferable to toleration....

  4. New simulators from old - achieving state-of-the-art simulation without state-of-the-art costs

    International Nuclear Information System (INIS)

    Heilmeier, H.J.; Rosser, R.M.; Fyffe, K.L.; Gaerttner, G.F.; Chulick, E.T.

    1990-01-01

    Achieving a state-of-the-art simulator for operator training requires neither the expensive remodeling of old simulators nor the acquisition of very expensive new machines. In this paper the authors present two distinct cases where older training simulators have been upgraded to meet training requirements with a minimum of inexpensive hardware additions, including plug-in/-out panels, and software changes

  5. Application of pattern recognition techniques to the detection of the Phenix reactor control rods vibrations

    International Nuclear Information System (INIS)

    Zwingelstein, G.; Deat, M.; Le Guillou, G.

    1979-01-01

    The incipient detection of control rods vibrations is very important for the safety of the operating plants. This detection can be achieved by an analysis of the peaks of the power spectrum density of the neutron noise. Pattern Recognition techniques were applied to detect the rod vibrations which occured at the fast breeder Phenix (250MWe). In the first part we give a description of the basic pattern which is used to characterize the behavior of the plant. The pattern is considered as column vector in n dimensional Euclidian space where the components are the samples of the power spectral density of the neutron noise. In the second part, a recursive learning procedure of the normal patterns which provides the mean and the variance of the estimates is described. In the third part the classification problem has been framed in terms of a partitioning procedure in n dimensional space which encloses regions corresponding to normal operations. This pattern recognition scheme was applied to the detection of rod vibrations with neutron data collected at the Phenix site before and after occurence of the vibrations. The analysis was carried out with a 42-dimensional measurement space. The learned pattern was estimated with 150 measurement vectors which correspond to the period without vibrations. The efficiency of the surveillance scheme is then demonstrated by processing separately 119 measurement vectors recorded during the rod vibration period

  6. 14 CFR 1203.403 - State-of-the-art and intelligence.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false State-of-the-art and intelligence. 1203.403... PROGRAM Guides for Original Classification § 1203.403 State-of-the-art and intelligence. A logical... available from intelligence sources is known or is available to others. It is also important to consider...

  7. A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

    Science.gov (United States)

    Perception of pathogen-associated molecular patterns (PAMPs) by surface-localised pattern-recognition receptors (PRRs) is a key component of plant innate immunity. Most known plant PRRs are receptor kinases and initiation of PAMP-triggered immunity (PTI) signalling requires phosphorylation of the PR...

  8. A self-organized learning strategy for object recognition by an embedded line of attraction

    Science.gov (United States)

    Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

    2012-04-01

    on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

  9. Track recognition with an associative pattern memory

    International Nuclear Information System (INIS)

    Bok, H.W. den; Visschers, J.L.; Borgers, A.J.; Lourens, W.

    1991-01-01

    Using Programmable Gate Arrays (PGAs), a prototype for a fast Associative Pattern Memory module has been realized. The associative memory performs the recognition of tracks within the hadron detector data acquisition system at NIKHEF-K. The memory matches the detector state with a set of 24 predefined tracks to identify the particle tracks that occur during an event. This information enables the trigger hardware to classify and select or discriminate the event. Mounted on a standard size (6U) VME board, several PGAs together form an associative memory. The internal logic architecture of the Gate Array is used in such a way as to minimize signal propagation delay. The memory cells, containing a binary representation of the particle tracks, are dynamically loadable through a VME bus interface, providing a high level of flexibility. The hadron detector and its readout system are briefly described and our track representation method is presented. Results from measurements under experimental conditions are discussed. (orig.)

  10. How the United States Funds the Arts. Third Edition

    Science.gov (United States)

    National Endowment for the Arts, 2012

    2012-01-01

    The infrastructure for arts and cultural support in the United States is complex and adaptive. Citizens who enjoy the arts can choose from a wide array of drama, visual and media arts, dance, music, and literature available in formal and informal settings--theaters, museums, and concert halls, but also libraries, schools, places of worship,…

  11. Platelet kinetics: the state of the art

    International Nuclear Information System (INIS)

    Heyns, A. duP

    1984-01-01

    In this paper an overview of the state of the art of platelet kinetics 1982 is presented. The subjects considered include a discussion of the advantages and disadvantages of some of the many radionuclide platelet labels, viz 51 Cr, 111 In, focussing briefly on models for analysis of platelets survival. (Auth.)

  12. Face Recognition Using Local Quantized Patterns and Gabor Filters

    Science.gov (United States)

    Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

    2015-05-01

    The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

  13. Pattern recognition as a method of data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Caputo, M.

    1978-11-15

    The method of pattern recognition has been used in biological and social sciences and has been recently introduced for the solution of geological and geophysical problems such as oil and ore prospecting and seismological prediction. The method is briefly illustrated by an application to earthquake prediction in Italy in which topographic and geologic maps are used in conjunction with earthquake catalogs. 3 figures, 1 table.

  14. DNA pattern recognition using canonical correlation algorithm.

    Science.gov (United States)

    Sarkar, B K; Chakraborty, Chiranjib

    2015-10-01

    We performed canonical correlation analysis as an unsupervised statistical tool to describe related views of the same semantic object for identifying patterns. A pattern recognition technique based on canonical correlation analysis (CCA) was proposed for finding required genetic code in the DNA sequence. Two related but different objects were considered: one was a particular pattern, and other was test DNA sequence. CCA found correlations between two observations of the same semantic pattern and test sequence. It is concluded that the relationship possesses maximum value in the position where the pattern exists. As a case study, the potential of CCA was demonstrated on the sequence found from HIV-1 preferred integration sites. The subsequences on the left and right flanking from the integration site were considered as the two views, and statistically significant relationships were established between these two views to elucidate the viral preference as an important factor for the correlation.

  15. State-of-the-art in Heterogeneous Computing

    Directory of Open Access Journals (Sweden)

    Andre R. Brodtkorb

    2010-01-01

    Full Text Available Node level heterogeneous architectures have become attractive during the last decade for several reasons: compared to traditional symmetric CPUs, they offer high peak performance and are energy and/or cost efficient. With the increase of fine-grained parallelism in high-performance computing, as well as the introduction of parallelism in workstations, there is an acute need for a good overview and understanding of these architectures. We give an overview of the state-of-the-art in heterogeneous computing, focusing on three commonly found architectures: the Cell Broadband Engine Architecture, graphics processing units (GPUs, and field programmable gate arrays (FPGAs. We present a review of hardware, available software tools, and an overview of state-of-the-art techniques and algorithms. Furthermore, we present a qualitative and quantitative comparison of the architectures, and give our view on the future of heterogeneous computing.

  16. Macrophage pattern recognition receptors in immunity, homeostasis and self tolerance.

    Science.gov (United States)

    Mukhopadhyay, Subhankar; Plüddemann, Annette; Gordon, Siamon

    2009-01-01

    Macrophages, a major component of innate immune defence, express a large repertoire of different classes of pattern recognition receptors and other surface antigens which determine the immunologic and homeostatic potential of these versatile cells. In the light of present knowledge ofmacrophage surface antigens, we discuss self versus nonself recognition, microbicidal effector functions and self tolerance in the innate immune system.

  17. Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

    Science.gov (United States)

    Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

    2017-09-01

    Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

  18. Stage-specific sampling by pattern recognition receptors during Candida albicans phagocytosis.

    Directory of Open Access Journals (Sweden)

    Sigrid E M Heinsbroek

    2008-11-01

    Full Text Available Candida albicans is a medically important pathogen, and recognition by innate immune cells is critical for its clearance. Although a number of pattern recognition receptors have been shown to be involved in recognition and phagocytosis of this fungus, the relative role of these receptors has not been formally examined. In this paper, we have investigated the contribution of the mannose receptor, Dectin-1, and complement receptor 3; and we have demonstrated that Dectin-1 is the main non-opsonic receptor involved in fungal uptake. However, both Dectin-1 and complement receptor 3 were found to accumulate at the site of uptake, while mannose receptor accumulated on C. albicans phagosomes at later stages. These results suggest a potential role for MR in phagosome sampling; and, accordingly, MR deficiency led to a reduction in TNF-alpha and MCP-1 production in response to C. albicans uptake. Our data suggest that pattern recognition receptors sample the fungal phagosome in a sequential fashion.

  19. The Arts and State Governments: At Arm's Length or Arm in Arm?

    Science.gov (United States)

    Lowell, Julia F.; Ondaatje, Elizabeth Heneghan

    2006-01-01

    Even though a majority of Americans claim to support public funding of the arts, state government spending on the arts is minimal--and may be losing ground relative to other types of state expenditures. Moreover, most state arts agencies, or SAAs, have not succeeded in convincing state government leaders that the arts should be integral to their…

  20. Development of a Pattern Recognition Methodology for Determining Operationally Optimal Heat Balance Instrumentation Calibration Schedules

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Beran; John Christenson; Dragos Nica; Kenny Gross

    2002-12-15

    The goal of the project is to enable plant operators to detect with high sensitivity and reliability the onset of decalibration drifts in all of the instrumentation used as input to the reactor heat balance calculations. To achieve this objective, the collaborators developed and implemented at DBNPS an extension of the Multivariate State Estimation Technique (MSET) pattern recognition methodology pioneered by ANAL. The extension was implemented during the second phase of the project and fully achieved the project goal.

  1. From Digital Imaging to Computer Image Analysis of Fine Art

    Science.gov (United States)

    Stork, David G.

    An expanding range of techniques from computer vision, pattern recognition, image analysis, and computer graphics are being applied to problems in the history of art. The success of these efforts is enabled by the growing corpus of high-resolution multi-spectral digital images of art (primarily paintings and drawings), sophisticated computer vision methods, and most importantly the engagement of some art scholars who bring questions that may be addressed through computer methods. This paper outlines some general problem areas and opportunities in this new inter-disciplinary research program.

  2. 77 FR 5281 - State-of-the-Art Reactor Consequence Analyses Reports

    Science.gov (United States)

    2012-02-02

    ... NUCLEAR REGULATORY COMMISSION [Docket ID: NRC-2012-0022] State-of-the-Art Reactor Consequence... release of Draft NUREG-1935, ``State-of-the-Art Reactor Consequence Analyses (SOARCA) Report,'' for public... offsite radiological health consequences for potential severe reactor accidents for the Peach Bottom...

  3. Conditional Random Fields for Pattern Recognition Applied to Structured Data

    Directory of Open Access Journals (Sweden)

    Tom Burr

    2015-07-01

    Full Text Available Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building or “natural” (such as a tree. Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs model structured data using the conditional distribution P(Y|X = x, without specifying a model for P(X, and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches in the output domain. Second, we identify research topics and present numerical examples.

  4. Bifurcation analysis of oscillating network model of pattern recognition in the rabbit olfactory bulb

    Science.gov (United States)

    Baird, Bill

    1986-08-01

    A neural network model describing pattern recognition in the rabbit olfactory bulb is analysed to explain the changes in neural activity observed experimentally during classical Pavlovian conditioning. EEG activity recorded from an 8×8 arry of 64 electrodes directly on the surface on the bulb shows distinct spatial patterns of oscillation that correspond to the animal's recognition of different conditioned odors and change with conditioning to new odors. The model may be considered a variant of Hopfield's model of continuous analog neural dynamics. Excitatory and inhibitory cell types in the bulb and the anatomical architecture of their connection requires a nonsymmetric coupling matrix. As the mean input level rises during each breath of the animal, the system bifurcates from homogenous equilibrium to a spatially patterned oscillation. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of these unstable oscillatory modes independent of frequency. This allows a view of stored periodic attractors as fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

  5. The DELPHI Silicon Tracker in the global pattern recognition

    CERN Document Server

    Elsing, M

    2000-01-01

    ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI.

  6. The DELPHI Silicon Tracker in the global pattern recognition

    International Nuclear Information System (INIS)

    Elsing, M.

    2000-01-01

    ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI

  7. Wavelet-based moment invariants for pattern recognition

    Science.gov (United States)

    Chen, Guangyi; Xie, Wenfang

    2011-07-01

    Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.

  8. State Arts Policy: Trends and Future Prospects

    Science.gov (United States)

    Lowell, Julia F.

    2008-01-01

    State arts agencies (SAAs)--key players within the U.S. system of public support for the arts--face growing economic, political, and demographic challenges to the roles and missions they adopted when founded in the mid-1960s. This report, the fourth and final in a multiyear study, looks at state arts agencies' efforts to rethink their roles and…

  9. Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid

    Directory of Open Access Journals (Sweden)

    Yujia Jiang

    2018-01-01

    Full Text Available Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP in spatial pyramid is applied to recognize fingerprint liveness in this paper. Firstly, preprocessing operation for each fingerprint is necessary. Then, to solve image rotation and scale invariance, three-layer spatial pyramids of fingerprints are introduced in this paper. Next, texture information for three layers spatial pyramids is described by using uniform local binary pattern to extract features of given fingerprints. The accuracy of our proposed method has been compared with several state-of-the-art methods in fingerprint liveness detection. Experiments based on standard databases, taken from Liveness Detection Competition 2013 composed of four different fingerprint sensors, have been carried out. Finally, classifier model based on extracted features is trained using SVM classifier. Experimental results present that our proposed method can achieve high recognition accuracy compared with other methods.

  10. Similarity-based pattern analysis and recognition

    CERN Document Server

    Pelillo, Marcello

    2013-01-01

    This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification alg

  11. Definition of new 3D invariants. Applications to pattern recognition problems with neural networks

    International Nuclear Information System (INIS)

    Proriol, J.

    1996-01-01

    We propose a definition of new 3D invariants. Usual pattern recognition methods use 2D descriptions of 3D objects, we propose a 2D approximation of the defined 3D invariants which can be used with neural networks to solve pattern recognition problems. We describe some methods to use the 2 D approximants. This work is an extension of previous 3D invariants used to solve some high energy physics problems. (author)

  12. Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Aleš Procházka

    2018-05-01

    Full Text Available Multimodal signal analysis based on sophisticated sensors, efficient communicationsystems and fast parallel processing methods has a rapidly increasing range of multidisciplinaryapplications. The present paper is devoted to pattern recognition, machine learning, and the analysisof sleep stages in the detection of sleep disorders using polysomnography (PSG data, includingelectroencephalography (EEG, breathing (Flow, and electro-oculogram (EOG signals. The proposedmethod is based on the classification of selected features by a neural network system with sigmoidaland softmax transfer functions using Bayesian methods for the evaluation of the probabilities of theseparate classes. The application is devoted to the analysis of the sleep stages of 184 individualswith different diagnoses, using EEG and further PSG signals. Data analysis points to an averageincrease of the length of the Wake stage by 2.7% per 10 years and a decrease of the length of theRapid Eye Movement (REM stages by 0.8% per 10 years. The mean classification accuracy for givensets of records and single EEG and multimodal features is 88.7% ( standard deviation, STD: 2.1 and89.6% (STD:1.9, respectively. The proposed methods enable the use of adaptive learning processesfor the detection and classification of health disorders based on prior specialist experience andman–machine interaction.

  13. Comparison of Object Recognition Behavior in Human and Monkey

    Science.gov (United States)

    Rajalingham, Rishi; Schmidt, Kailyn

    2015-01-01

    Although the rhesus monkey is used widely as an animal model of human visual processing, it is not known whether invariant visual object recognition behavior is quantitatively comparable across monkeys and humans. To address this question, we systematically compared the core object recognition behavior of two monkeys with that of human subjects. To test true object recognition behavior (rather than image matching), we generated several thousand naturalistic synthetic images of 24 basic-level objects with high variation in viewing parameters and image background. Monkeys were trained to perform binary object recognition tasks on a match-to-sample paradigm. Data from 605 human subjects performing the same tasks on Mechanical Turk were aggregated to characterize “pooled human” object recognition behavior, as well as 33 separate Mechanical Turk subjects to characterize individual human subject behavior. Our results show that monkeys learn each new object in a few days, after which they not only match mean human performance but show a pattern of object confusion that is highly correlated with pooled human confusion patterns and is statistically indistinguishable from individual human subjects. Importantly, this shared human and monkey pattern of 3D object confusion is not shared with low-level visual representations (pixels, V1+; models of the retina and primary visual cortex) but is shared with a state-of-the-art computer vision feature representation. Together, these results are consistent with the hypothesis that rhesus monkeys and humans share a common neural shape representation that directly supports object perception. SIGNIFICANCE STATEMENT To date, several mammalian species have shown promise as animal models for studying the neural mechanisms underlying high-level visual processing in humans. In light of this diversity, making tight comparisons between nonhuman and human primates is particularly critical in determining the best use of nonhuman primates to

  14. Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

    Science.gov (United States)

    Amador, Jose J (Inventor)

    2007-01-01

    A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.

  15. Hidden Markov model analysis reveals the advantage of analytic eye movement patterns in face recognition across cultures.

    Science.gov (United States)

    Chuk, Tim; Crookes, Kate; Hayward, William G; Chan, Antoni B; Hsiao, Janet H

    2017-12-01

    It remains controversial whether culture modulates eye movement behavior in face recognition. Inconsistent results have been reported regarding whether cultural differences in eye movement patterns exist, whether these differences affect recognition performance, and whether participants use similar eye movement patterns when viewing faces from different ethnicities. These inconsistencies may be due to substantial individual differences in eye movement patterns within a cultural group. Here we addressed this issue by conducting individual-level eye movement data analysis using hidden Markov models (HMMs). Each individual's eye movements were modeled with an HMM. We clustered the individual HMMs according to their similarities and discovered three common patterns in both Asian and Caucasian participants: holistic (looking mostly at the face center), left-eye-biased analytic (looking mostly at the two individual eyes in addition to the face center with a slight bias to the left eye), and right-eye-based analytic (looking mostly at the right eye in addition to the face center). The frequency of participants adopting the three patterns did not differ significantly between Asians and Caucasians, suggesting little modulation from culture. Significantly more participants (75%) showed similar eye movement patterns when viewing own- and other-race faces than different patterns. Most importantly, participants with left-eye-biased analytic patterns performed significantly better than those using either holistic or right-eye-biased analytic patterns. These results suggest that active retrieval of facial feature information through an analytic eye movement pattern may be optimal for face recognition regardless of culture. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Ascertaining the international state of the art of PSA methodology

    International Nuclear Information System (INIS)

    Linden, J. von

    1998-01-01

    Plant-specific PSAs, to be performed within the framework of the Periodic Safety Review of German Nuclear Power Plants require further development of the methodology. For that purpose foreign PSA-guidelines and PSA-reviewes as well as relevant literature are examined and appropriate insights are adopted within task A.2 of project SR 2096. The main goal of these activities is to achieve a comparison of the state of the art of PSA-methodologies applied abroad and in Germany. The German state of the art refers to the extent as is documented in the German PSA Guide (Leitfaden Probabilistische Sicherheitsanalyse /PSUe97/) which has to be used for the Periodic Safety Review of German Nuclear Power Plants. The structure for the evaluation is based on the working steps of a PSA. In total, according to the objectives of the Periodic Safety Review the German approach for plant-specific PSAs based on the German PSA Guide is conform to the state of the art abroad. Identified deviations in some details are evaluated reflecting the view of GRS. Particular aspects resulting from the evaluation should be considered for further development of the German PSA Guide. (orig.) [de

  17. Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

    Science.gov (United States)

    Noh, Soo Rim; Isaacowitz, Derek M.

    2014-01-01

    While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

  18. State of the art magnetic resonance imaging

    International Nuclear Information System (INIS)

    Weissman, J.D.

    1987-01-01

    In less than a decade Magnetic Resonance Imaging (MRI) has evolved from a laboratory demonstration to a safe and effective technique for clinical diagnosis. This evolutionary process continues. At this time 2-D and 3-D imaging of the head and body is firmly established in clinical use. Surface coil imaging, two-component chemical shift imaging, in-vivo spectroscopy and flow imaging are currently in various stages of development. The present state of the art of MRI is a function of an array of technologies: magnet, Rf coil, Rf pulse amplifier, gradient coil and driver, pulse programmer, A/D converter, computer system architecture, array processors and mass storage (both magnetic and optical). The overall product design is the result of a complex process which balances the advantages and disadvantages of each component for optimal system performance and flexibility. The author discusses the organization of a state-of-the-art MRI system. Several examples of the kinds of system interactions affecting design choices are given. (Auth.)

  19. The "State of Art" of Organisational Blogging

    Science.gov (United States)

    Baxter, Gavin J.; Connolly, Thomas M.

    2013-01-01

    Purpose: The aim of this paper is to provide an overview of the "state of art" of organisational blogging. It also aims to provide a critical review of the literature on organisational blogging and propose recommendations on how to advance the subject area in terms of academic research. Design/methodology/approach: A systematic literature review…

  20. Hardware processors for pattern recognition tasks in experiments with wire chambers

    International Nuclear Information System (INIS)

    Verkerk, C.

    1975-01-01

    Hardware processors for pattern recognition tasks in experiments with multiwire proportional chambers or drift chambers are described. They vary from simple ones used for deciding in real time if particle trajectories are straight to complex ones for recognition of curved tracks. Schematics and block-diagrams of different processors are shown

  1. The State of the Art Ten Years After a State of the Art

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2014-01-01

    A decade has passed since the first review of research on a ``flagship application" of music information retrieval (MIR): the problem of music genre recognition (MGR). During this time, about 500 works addressing MGR have been published, and at least 10 campaigns have been run to evaluate MGR sys......, the problems of validity in evaluation also affect research in music emotion recognition and autotagging. We conclude by discussing the implications of our work for MGR and MIR in the next ten years....

  2. PATTER, Pattern Recognition Data Analysis

    International Nuclear Information System (INIS)

    Cox, L.C. Jr.; Bender, C.F.

    1986-01-01

    1 - Description of program or function: PATTER is an interactive program with extensive facilities for modeling analytical processes and solving complex data analysis problems using statistical methods, spectral analysis, and pattern recognition techniques. PATTER addresses the type of problem generally stated as follows: given a set of objects and a list of measurements made on these objects, is it possible to find or predict a property of the objects which is not directly measurable but is known to define some unknown relationship? When employed intelligently, PATTER will act upon a data set in such a way it becomes apparent if useful information, beyond that already discerned, is contained in the data. 2 - Method of solution: In order to solve the general problem, PATTER contains preprocessing techniques to produce new variables that are related to the values of the measurements which may reduce the number of variables and/or reveal useful information about the 'obscure' property; display techniques to represent the variable space in some way that can be easily projected onto a two- or three-dimensional plot for human observation to see if any significant clustering of points occurs; and learning techniques based on both unsupervised and supervised methods, to extract as much information from the data as possible so that the optimum solution can be found

  3. Oxidation-specific epitopes are danger-associated molecular patterns recognized by pattern recognition receptors of innate immunity

    DEFF Research Database (Denmark)

    Miller, Yury I; Choi, Soo-Ho; Wiesner, Philipp

    2011-01-01

    are a major target of innate immunity, recognized by a variety of "pattern recognition receptors" (PRRs). By analogy with microbial "pathogen-associated molecular patterns" (PAMPs), we postulate that host-derived, oxidation-specific epitopes can be considered to represent "danger (or damage......)-associated molecular patterns" (DAMPs). We also argue that oxidation-specific epitopes present on apoptotic cells and their cellular debris provided the primary evolutionary pressure for the selection of such PRRs. Furthermore, because many PAMPs on microbes share molecular identity and/or mimicry with oxidation...

  4. Contemporary Romanian Art in the United States1

    Directory of Open Access Journals (Sweden)

    Altman Dana

    2014-08-01

    Full Text Available The article discusses the recent international interest in contemporary Romanian art and its growth in market share, with a focus on the United States. The theme is followed thorough in numerous museum exhibitions, increased collector following, art fair presence, gallery representation and auction activity initially in Europe and the United States. The phenomenon is discussed both in the context of the larger international movement conducive to the contemporary art price bubble, and in that of the local socio-economic changes. My chief interest lies in the factors leading up to the entry of post 1989 Romanian art in the global arena as a manifestation of market forces in the field. The analysis follows its grass roots local emergence through non-profit institutions, individual artists, small publications, low budget galleries, as well as the lack of contribution (with few notable exceptions of state institutions, while pointing out the national context of increasing deregulation of social support systems resulting in lack of focus on cultural manifestations. The conclusion is that the recent ascent of contemporary Romanian art (and coincidentally, the award winning contemporary Romanian cinematography is a fortuitous convergence of various factors, among which, increased international mobility and sharing. At the same time, it is also the result of the evolution of various individual artists that pursued a form of art rooted in Romanian artistic tradition but with a focus on the symbolic figurative. The result is a personal semiotics of raising the mundane to extraordinary levels that reconfigured the anxiety of entering a new system into an unmistakable and lasting visual language.

  5. Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

    Science.gov (United States)

    Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

    2013-01-01

    The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD. © 2012 Blackwell Publishing Ltd.

  6. Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance

    NARCIS (Netherlands)

    Lacombe, S.; Rougon-Cardoso, A.; Sherwood, E.; Peeters, N.; Dahlbeck, D.; Esse, van H.P.; Smoker, M.; Rallapalli, G.; Thomma, B.P.H.J.; Staskawicz, B.; Jones, J.D.G.; Zipfel, C.

    2010-01-01

    Plant diseases cause massive losses in agriculture. Increasing the natural defenses of plants may reduce the impact of phytopathogens on agricultural productivity. Pattern-recognition receptors (PRRs) detect microbes by recognizing conserved pathogen-associated molecular patterns (PAMPs)1, 2, 3.

  7. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document

  8. Combining Biometric Fractal Pattern and Particle Swarm Optimization-Based Classifier for Fingerprint Recognition

    Directory of Open Access Journals (Sweden)

    Chia-Hung Lin

    2010-01-01

    Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.

  9. Recent progress in invariant pattern recognition

    Science.gov (United States)

    Arsenault, Henri H.; Chang, S.; Gagne, Philippe; Gualdron Gonzalez, Oscar

    1996-12-01

    We present some recent results in invariant pattern recognition, including methods that are invariant under two or more distortions of position, orientation and scale. There are now a few methods that yield good results under changes of both rotation and scale. Some new methods are introduced. These include locally adaptive nonlinear matched filters, scale-adapted wavelet transforms and invariant filters for disjoint noise. Methods using neural networks will also be discussed, including an optical method that allows simultaneous classification of multiple targets.

  10. Mission Accomplished: Working with State Arts Agencies

    Science.gov (United States)

    Boyer, Johanna Misey

    2005-01-01

    Most everyone involved professionally in the non-profit arts comes in contact with a state arts agency. A person may be on the Teaching Artist roster, works for a grantee organization, or has directly received a grant or fellowship. The work that one does in the school is probably funded by the state arts agency. Or, at a more basic level, the…

  11. 20 CFR 408.1205 - How can a State have SSA administer its State recognition payment program?

    Science.gov (United States)

    2010-04-01

    ... recognition payment program? 408.1205 Section 408.1205 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SPECIAL BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1205 How can a State have SSA administer its State recognition payment program? A State (or...

  12. The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

    CERN Document Server

    Acciarri, R.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-01-01

    The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the...

  13. 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

  14. 20 CFR 408.1201 - What are State recognition payments?

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false What are State recognition payments? 408.1201 Section 408.1201 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SPECIAL BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1201 What are State...

  15. Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data.

    Science.gov (United States)

    Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

    2015-05-21

    Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our

  16. Improving Pattern Recognition and Neural Network Algorithms with Applications to Solar Panel Energy Optimization

    Science.gov (United States)

    Zamora Ramos, Ernesto

    Artificial Intelligence is a big part of automation and with today's technological advances, artificial intelligence has taken great strides towards positioning itself as the technology of the future to control, enhance and perfect automation. Computer vision includes pattern recognition and classification and machine learning. Computer vision is at the core of decision making and it is a vast and fruitful branch of artificial intelligence. In this work, we expose novel algorithms and techniques built upon existing technologies to improve pattern recognition and neural network training, initially motivated by a multidisciplinary effort to build a robot that helps maintain and optimize solar panel energy production. Our contributions detail an improved non-linear pre-processing technique to enhance poorly illuminated images based on modifications to the standard histogram equalization for an image. While the original motivation was to improve nocturnal navigation, the results have applications in surveillance, search and rescue, medical imaging enhancing, and many others. We created a vision system for precise camera distance positioning motivated to correctly locate the robot for capture of solar panel images for classification. The classification algorithm marks solar panels as clean or dirty for later processing. Our algorithm extends past image classification and, based on historical and experimental data, it identifies the optimal moment in which to perform maintenance on marked solar panels as to minimize the energy and profit loss. In order to improve upon the classification algorithm, we delved into feedforward neural networks because of their recent advancements, proven universal approximation and classification capabilities, and excellent recognition rates. We explore state-of-the-art neural network training techniques offering pointers and insights, culminating on the implementation of a complete library with support for modern deep learning architectures

  17. For What Purpose the Arts? An Analysis of the Mission Statements of Urban Arts High Schools in Canada and the United States

    Science.gov (United States)

    Gaztambide-Fernández, Rubén; Nicholls, Rachael; Arráiz-Matute, Alexandra

    2016-01-01

    While general arts programs have declined in many schools across the United States and Canada, the number of specialized art programs in public secondary schools has swelled since the 1980s. While this increase is often celebrated by arts educators, questions about the justification of specialized arts programs are rarely raised, and their value…

  18. Post-editing through Speech Recognition

    DEFF Research Database (Denmark)

    Mesa-Lao, Bartolomé

    (i.e. typing, handwriting and speaking) to improve the efficiency and accuracy of the translation process. However, further studies need to be conducted to build up new knowledge about the way in which state-of-the-art speech recognition software can be applied to the post-editing process...

  19. LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Jayanti Yusmah Sari

    2015-08-01

    Full Text Available In recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris. Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP, a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is needed

  20. Application of neural network and pattern recognition software to the automated analysis of continuous nuclear monitoring of on-load reactors

    Energy Technology Data Exchange (ETDEWEB)

    Howell, J.A.; Eccleston, G.W.; Halbig, J.K.; Klosterbuer, S.F. [Los Alamos National Lab., NM (United States); Larson, T.W. [California Polytechnic State Univ., San Luis Obispo, CA (US)

    1993-08-01

    Automated analysis using pattern recognition and neural network software can help interpret data, call attention to potential anomalies, and improve safeguards effectiveness. Automated software analysis, based on pattern recognition and neural networks, was applied to data collected from a radiation core discharge monitor system located adjacent to an on-load reactor core. Unattended radiation sensors continuously collect data to monitor on-line refueling operations in the reactor. The huge volume of data collected from a number of radiation channels makes it difficult for a safeguards inspector to review it all, check for consistency among the measurement channels, and find anomalies. Pattern recognition and neural network software can analyze large volumes of data from continuous, unattended measurements, thereby improving and automating the detection of anomalies. The authors developed a prototype pattern recognition program that determines the reactor power level and identifies the times when fuel bundles are pushed through the core during on-line refueling. Neural network models were also developed to predict fuel bundle burnup to calculate the region on the on-load reactor face from which fuel bundles were discharged based on the radiation signals. In the preliminary data set, which was limited and consisted of four distinct burnup regions, the neural network model correctly predicted the burnup region with an accuracy of 92%.

  1. State of the social responsibility art

    OpenAIRE

    Varela López, Leidy Viviana; Universidad de San Buenaventura Cali.

    2015-01-01

    From the eighties, it has been addressing the issue of corporate social responsibility, specifically toward the defense of human rights and climate change. However, although they have applied corporate social responsibility principles in some of the existing institutions, it is still very small the work being done around the specific activity of solid waste management. Some works have been compiled to build a state of the art for understanding in depth the concept of corporate social responsi...

  2. Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

    Science.gov (United States)

    Huo, Guanying

    2017-01-01

    As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

  3. State of the art report on design for X

    DEFF Research Database (Denmark)

    Papanikolaou, Apostolos; Andersen, Poul; Kristensen, Hans Otto Holmegaard

    2009-01-01

    The present State of the Art report aims at defining and reviewing the curent state of the ship design process in the frame of a holistic approach, accounting for various objectives and constraints. The report addresses mainly the design of transportation carriers, though some covered aspects...

  4. Artificial immune pattern recognition for damage detection in structural health monitoring sensor networks

    Science.gov (United States)

    Chen, Bo; Zang, Chuanzhi

    2009-03-01

    This paper presents an artificial immune pattern recognition (AIPR) approach for the damage detection and classification in structures. An AIPR-based Structure Damage Classifier (AIPR-SDC) has been developed by mimicking immune recognition and learning mechanisms. The structure damage patterns are represented by feature vectors that are extracted from the structure's dynamic response measurements. The training process is designed based on the clonal selection principle in the immune system. The selective and adaptive features of the clonal selection algorithm allow the classifier to generate recognition feature vectors that are able to match the training data. In addition, the immune learning algorithm can learn and remember various data patterns by generating a set of memory cells that contains representative feature vectors for each class (pattern). The performance of the presented structure damage classifier has been validated using a benchmark structure proposed by the IASC-ASCE (International Association for Structural Control - American Society of Civil Engineers) Structural Health Monitoring Task Group. The validation results show a better classification success rate comparing to some of other classification algorithms.

  5. Study of problems met in muon pattern recognition for a deep inelastic scattering experiment at the S.P.S

    International Nuclear Information System (INIS)

    Besson, C.

    1976-01-01

    The problems of the muon pattern recognition are studied for a muon-proton deep inelastic scattering experiment at the S.P.S. The pattern recognition program is described together with the problems caused by some characteristics of the apparatus of the European muon collaboration. Several reconstruction technics are compared, and a way of handling big drift chamber problems is found. Some results on Monte-Carlo tracks are given [fr

  6. A State of the Art Overview

    DEFF Research Database (Denmark)

    Jahangiri, Tohid; Bak, Claus Leth; Silva, Filipe Miguel Faria da

    2015-01-01

    The first EHV composite cross-arms have been used since late 1990's in Switzerland. It was the first step to the compaction of towers sizes. Since then, significant advances have been made in composite cross-arms technology while the lattice construction technique has not been seriously challenged...... of EHV composite cross-arms and lightning protection methods are reviewed based on the state of the art review and subsequently some solutions are presented to overcome the two main challenges....

  7. Fast pattern recognition with the ATLAS L1 track trigger for the HL-LHC

    CERN Document Server

    Martensson, Mikael; The ATLAS collaboration

    2016-01-01

    A fast hardware based track trigger for high luminosity upgrade of the Large Hadron Collider (HL- LHC) is being developed in ATLAS. The goal is to achieve trigger levels in high pileup collisions that are similar or even better than those achieved at low pile-up running of LHC by adding tracking information to the ATLAS hardware trigger which is currently based on information from calorimeters and muon trigger chambers only. Two methods for fast pattern recognition are investigated. The first is based on matching tracker hits to pattern banks of simulated high momentum tracks which are stored in a custom made Associative Memory (AM) ASIC. The second is based on the Hough transform where detector hits are transformed into 2D Hough space with one variable related to track pt and one to track direction. Hits found by pattern recognition will be sent to a track fitting step which calculates the track parameters . The speed and precision of the track fitting depends on the quality of the hits selected by the patte...

  8. Meniscal Allograft Transplantation: State of the Art.

    Science.gov (United States)

    Trentacosta, Natasha; Graham, William C; Gersoff, Wayne K

    2016-06-01

    Meniscal allograft transplantation has evolved over the years to provide a state-of-the-art technique for the sports medicine surgeon to utilize in preserving contact mechanics and function of the knee in irreparable meniscal pathology. However, this procedure continues to spark considerable debate on proper tissue processing techniques, acceptable indications, methods of implantation, and potential long-term outcomes.

  9. Application of ann-based decision making pattern recognition to fishing operations

    Energy Technology Data Exchange (ETDEWEB)

    Akhlaghinia, M.; Torabi, F.; Wilton, R.R. [University of Regina, Saskatchewan (Canada). Faculty of Engineering. Dept. of Petroleum Engineering], e-mail: Farshid.Torabi@uregina.ca

    2010-10-15

    Decision making is a crucial part of fishing operations. Proper decisions should be made to prevent wasted time and associated costs on unsuccessful operations. This paper presents a novel model to help drilling managers decide when to commence and when to quit a fishing operation. A decision making model based on Artificial Neural Network (ANN) has been developed that utilizes Pattern Recognition based on 181 fishing incidents from one of the most fish-prone fields of the southwest of Iran. All parameters chosen to train the ANN-Based Pattern Recognition Tool are assumed to play a role in the success of the fishing operation and are therefore used to decide whether a fishing operation should be performed or not. If the tool deems the operation suitable for consideration, a cost analysis of the fishing operation can then be performed to justify its overall cost. (author)

  10. Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

    Science.gov (United States)

    Chen, Cunjian; Ross, Arun

    2013-05-01

    Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.

  11. Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

    Science.gov (United States)

    Wu, Yao; Qiu, Weigen

    2017-08-01

    In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

  12. Aggregating Local Descriptors for Epigraphs Recognition

    OpenAIRE

    Amato, Giuseppe; Falchi, Fabrizio; Rabitti, Fausto; Vadicamo, Lucia

    2014-01-01

    In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors ...

  13. Identification of a β-glucosidase from the Mucor circinelloides genome by peptide pattern recognition

    DEFF Research Database (Denmark)

    Yuhong, Huang; Busk, Peter Kamp; Grell, Morten Nedergaard

    2014-01-01

    Mucor circinelloides produces plant cell wall degrading enzymes that allow it to grow on complex polysaccharides. Although the genome of M. circinelloides has been sequenced, only few plant cell wall degrading enzymes are annotated in this species. We applied peptide pattern recognition, which...

  14. Fast pattern recognition with the ATLAS L1Track trigger for HL-LHC

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00530554; The ATLAS collaboration

    2017-01-01

    A fast hardware based track trigger is being developed in ATLAS for the High Luminosity upgrade of the Large Hadron Collider. The goal is to achieve trigger levels in the high pile-up conditions of the High Luminosity Large Hadron Collider that are similar or better than those achieved at low pile-up conditions by adding tracking information to the ATLAS hardware trigger. A method for fast pattern recognition using the Hough transform is investigated. In this method, detector hits are mapped onto a 2D parameter space with one parameter related to the transverse momentum and one to the initial track direction. The performance of the Hough transform is studied at different pile-up values. It is also compared, using full event simulation of events with average pile-up of 200, with a method based on matching detector hits to pattern banks of simulated tracks stored in a custom made Associative Memory ASICs. The pattern recognition is followed by a track fitting step which calculates the track parameters. The spee...

  15. PRIVATE LAW EFFECTS OF THE NON-RECOGNITION OF STATES' EXISTENCE AND TERRITORIAL CHANGES

    Directory of Open Access Journals (Sweden)

    Ioan-Luca VLAD

    2015-07-01

    Full Text Available The study presents an outline of the effects in private law (including private international law of the non-recognition of a state or a change of territory. Specifically, it addresses the question of what measures can another state take, in the field of private law, in order to give effect to its policy of not recognizing a state or a territorial annexation, and, in parallel, what are the means available to private parties with links to the unrecognized state or territory. The study is structured in two parts, namely 1 the effects in private law of the non-recognition of a state; and 2 the effect in private law of the non-recognition of an annexation of territory. I will make specific references in particular to the situation in Transnistria and Crimea, as examples of the two issues being addressed. The study intends to be a guide of past and present state practice at the legislative and judicial level, as well as presenting the connections between instruments of public international law, such as Sanctions Resolutions of the UN Security Council, and normative instruments of private law, such as rules of civil procedure, which must adapt to the policy of non-recognition adopted by (or imposed on states. The study also presents specific examples of situations or administrative practices which create practical problems, and result from the existence of a non-recognized entity or change of territory: issues like air traffic coordination, postal traffic, the change in the official currency of a territory, questions of citizenship etc., the aim being to present the reader with a full picture of the issues and intricacies resulting from irregularities existing at the level of the international community of states.

  16. Comparison of eye imaging pattern recognition using neural network

    Science.gov (United States)

    Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

    2015-05-01

    The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

  17. Sequential pattern recognition by maximum conditional informativity

    Czech Academy of Sciences Publication Activity Database

    Grim, Jiří

    2014-01-01

    Roč. 45, č. 1 (2014), s. 39-45 ISSN 0167-8655 R&D Projects: GA ČR(CZ) GA14-02652S; GA ČR(CZ) GA14-10911S Keywords : Multivariate statistics * Statistical pattern recognition * Sequential decision making * Product mixtures * EM algorithm * Shannon information Subject RIV: IN - Informatics, Computer Sci ence Impact factor: 1.551, year: 2014 http://library.utia.cas.cz/separaty/2014/RO/grim-0428565.pdf

  18. Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors

    Directory of Open Access Journals (Sweden)

    Gaojing Wang

    2018-06-01

    Full Text Available Human activity recognition (HAR is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applied to HAR. Data segmentation using a sliding window is a basic step during the HAR procedure, wherein the window length directly affects recognition performance. However, the window length is generally randomly selected without systematic study. In this study, we examined the impact of window length on smartphone sensor-based human motion and pose pattern recognition. With data collected from smartphone sensors, we tested a range of window lengths on five popular machine-learning methods: decision tree, support vector machine, K-nearest neighbor, Gaussian naïve Bayesian, and adaptive boosting. From the results, we provide recommendations for choosing the appropriate window length. Results corroborate that the influence of window length on the recognition of motion modes is significant but largely limited to pose pattern recognition. For motion mode recognition, a window length between 2.5–3.5 s can provide an optimal tradeoff between recognition performance and speed. Adaptive boosting outperformed the other methods. For pose pattern recognition, 0.5 s was enough to obtain a satisfactory result. In addition, all of the tested methods performed well.

  19. Patterns of patient safety culture: a complexity and arts-informed project of knowledge translation.

    Science.gov (United States)

    Mitchell, Gail J; Tregunno, Deborah; Gray, Julia; Ginsberg, Liane

    2011-01-01

    The purpose of this paper is to describe patterns of patient safety culture that emerged from an innovative collaboration among health services researchers and fine arts colleagues. The group engaged in an arts-informed knowledge translation project to produce a dramatic expression of patient safety culture research for inclusion in a symposium. Scholars have called for a deeper understanding of the complex interrelationships among structure, process and outcomes relating to patient safety. Four patterns of patient safety culture--blinding familiarity, unyielding determination, illusion of control and dismissive urgency--are described with respect to how they informed creation of an arts-informed project for knowledge translation.

  20. State of the art of solid state dosimetry

    International Nuclear Information System (INIS)

    Souza, Susana O.; Yamamoto, Takayoshi; D'Errico, Francesco

    2014-01-01

    Passive solid-state detectors still dominate the personal dosimetry field. This article provides state of the art in this field and summarizes the most recent works presented on TL, OSL and RPL during the 17th International Conference on Solid State Dosimetry held in Recife in September 2013. The Article contains in particular the techniques Thermoluminescence (TL), Optically Stimulated Luminescence (OSL), radio photoluminescence (RPL). Thermoluminescence has the biggest advantage of the wide availability of commercial materials for dosimetry, and the nature tissue-equivalent of several of these materials. The limitation of the TL dosimetry presents fading luminance signal and the need for high temperatures to obtain the signal. The Optically Stimulated Luminescence has the advantages of high sensitivity, the possibility of multiple reading, while its limit is the need to use response compensating filters in addition to the high cost of equipment and dosimeters still restricted very few options trading . The radio photoluminescence has a reading that is completely non-destructive, but their dosimeters present lack of tissue-equivalent and a high cost. Presents the details of the techniques and the advantages and limitations of each of these will be discussed

  1. State of the art in semiconductor detectors

    International Nuclear Information System (INIS)

    Rehak, P.; Gatti, E.

    1990-01-01

    The state of the art in semiconductor detectors for elementary particle physics and X-ray astronomy is briefly reviewed. Semiconductor detectors are divided into two groups; i) classical semiconductor diode detectors and ii) semiconductor memory detectors. Principles of signal formation for both groups of detectors are described and their performance is compared. New developments of silicon detectors are reported here. (orig.)

  2. State of the art in semiconductor detectors

    International Nuclear Information System (INIS)

    Rehak, P.; Gatti, E.

    1989-01-01

    The state of the art in semiconductor detectors for elementary particle physics and x-ray astronomy is briefly reviewed. Semiconductor detectors are divided into two groups; classical semiconductor diode detectors; and semiconductor memory detectors. Principles of signal formation for both groups of detectors are described and their performance is compared. New developments of silicon detectors are reported here. 13 refs., 8 figs

  3. Effects of the Maximum Luminance in a Medical-grade Liquid-crystal Display on the Recognition Time of a Test Pattern: Observer Performance Using Landolt Rings.

    Science.gov (United States)

    Doi, Yasuhiro; Matsuyama, Michinobu; Ikeda, Ryuji; Hashida, Masahiro

    2016-07-01

    This study was conducted to measure the recognition time of the test pattern and to investigate the effects of the maximum luminance in a medical-grade liquid-crystal display (LCD) on the recognition time. Landolt rings as signals of the test pattern were used with four random orientations, one on each of the eight gray-scale steps. Ten observers input the orientation of the gap on the Landolt rings using cursor keys on the keyboard. The recognition times were automatically measured from the display of the test pattern on the medical-grade LCD to the input of the orientation of the gap in the Landolt rings. The maximum luminance in this study was set to one of four values (100, 170, 250, and 400 cd/m(2)), for which the corresponding recognition times were measured. As a result, the average recognition times for each observer with maximum luminances of 100, 170, 250, and 400 cd/m(2) were found to be 3.96 to 7.12 s, 3.72 to 6.35 s, 3.53 to 5.97 s, and 3.37 to 5.98 s, respectively. The results indicate that the observer's recognition time is directly proportional to the luminance of the medical-grade LCD. Therefore, it is evident that the maximum luminance of the medical-grade LCD affects the test pattern recognition time.

  4. The state-of-the-art of HSR in Europe.

    NARCIS (Netherlands)

    Hansen, J.

    2009-01-01

    In this section of the workshop we present an overview based on mapping the current state-of-the-art concerning various fields of health services research, addressing the different levels of analysis in HSR. (1) HSR at the level of health care systems, being national or sometimes regional entities,

  5. Pattern recognition in molecular dynamics. [FORTRAN

    Energy Technology Data Exchange (ETDEWEB)

    Zurek, W H; Schieve, W C [Texas Univ., Austin (USA)

    1977-07-01

    An algorithm for the recognition of the formation of bound molecular states in the computer simulation of a dilute gas is presented. Applications to various related problems in physics and chemistry are pointed out. Data structure and decision processes are described. Performance of the FORTRAN program based on the algorithm in cooperation with the molecular dynamics program is described and the results are presented.

  6. Expanding the universe of cytokines and pattern recognition receptors: galectins and glycans in innate immunity.

    Science.gov (United States)

    Cerliani, Juan P; Stowell, Sean R; Mascanfroni, Iván D; Arthur, Connie M; Cummings, Richard D; Rabinovich, Gabriel A

    2011-02-01

    Effective immunity relies on the recognition of pathogens and tumors by innate immune cells through diverse pattern recognition receptors (PRRs) that lead to initiation of signaling processes and secretion of pro- and anti-inflammatory cytokines. Galectins, a family of endogenous lectins widely expressed in infected and neoplastic tissues have emerged as part of the portfolio of soluble mediators and pattern recognition receptors responsible for eliciting and controlling innate immunity. These highly conserved glycan-binding proteins can control immune cell processes through binding to specific glycan structures on pathogens and tumors or by acting intracellularly via modulation of selective signaling pathways. Recent findings demonstrate that various galectin family members influence the fate and physiology of different innate immune cells including polymorphonuclear neutrophils, mast cells, macrophages, and dendritic cells. Moreover, several pathogens may actually utilize galectins as a mechanism of host invasion. In this review, we aim to highlight and integrate recent discoveries that have led to our current understanding of the role of galectins in host-pathogen interactions and innate immunity. Challenges for the future will embrace the rational manipulation of galectin-glycan interactions to instruct and shape innate immunity during microbial infections, inflammation, and cancer.

  7. Application of an automatic pattern recognition for aleatory signals for the surveillance of nuclear reactor and rotating machinery

    International Nuclear Information System (INIS)

    Nascimento, J.A. do.

    1982-02-01

    An automatic pattern recognition program PSDREC, developed for the surveillance of nuclear reactor and rotating machinery is described and the relevant theory is outlined. Pattern recognition analysis of noise signals is a powerful technique for assessing 'system normality' in dynamic systems. This program, with applies 8 statistical tests to calculated power spectral density (PSD) distribution, was earlier installed in a PDP-11/45 computer at IPEN. To analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel engine (vibration signals) this technique was used. Results of the tests are considered satisfactory. (Author) [pt

  8. Scanning patterns of faces do not explain impaired emotion recognition in Huntington Disease: Evidence for a high level mechanism

    Directory of Open Access Journals (Sweden)

    Marieke evan Asselen

    2012-02-01

    Full Text Available Previous studies in patients with amygdala lesions suggested that deficits in emotion recognition might be mediated by impaired scanning patterns of faces. Here we investigated whether scanning patterns also contribute to the selective impairment in recognition of disgust in Huntington disease (HD. To achieve this goal, we recorded eye movements during a two-alternative forced choice emotion recognition task. HD patients in presymptomatic (n=16 and symptomatic (n=9 disease stages were tested and their performance was compared to a control group (n=22. In our emotion recognition task, participants had to indicate whether a face reflected one of six basic emotions. In addition, and in order to define whether emotion recognition was altered when the participants were forced to look at a specific component of the face, we used a second task where only limited facial information was provided (eyes/mouth in partially masked faces. Behavioural results showed no differences in the ability to recognize emotions between presymptomatic gene carriers and controls. However, an emotion recognition deficit was found for all 6 basic emotion categories in early stage HD. Analysis of eye movement patterns showed that patient and controls used similar scanning strategies. Patterns of deficits were similar regardless of whether parts of the faces were masked or not, thereby confirming that selective attention to particular face parts is not underlying the deficits. These results suggest that the emotion recognition deficits in symptomatic HD patients cannot be explained by impaired scanning patterns of faces. Furthermore, no selective deficit for recognition of disgust was found in presymptomatic HD patients.

  9. Adaptive pattern recognition in real-time video-based soccer analysis

    DEFF Research Database (Denmark)

    Schlipsing, Marc; Salmen, Jan; Tschentscher, Marc

    2017-01-01

    are taken into account. Our contribution is twofold: (1) the deliberate use of machine learning and pattern recognition techniques allows us to achieve high classification accuracy in varying environments. We systematically evaluate combinations of image features and learning machines in the given online......Computer-aided sports analysis is demanded by coaches and the media. Image processing and machine learning techniques that allow for "live" recognition and tracking of players exist. But these methods are far from collecting and analyzing event data fully autonomously. To generate accurate results......, human interaction is required at different stages including system setup, calibration, supervision of classifier training, and resolution of tracking conflicts. Furthermore, the real-time constraints are challenging: in contrast to other object recognition and tracking applications, we cannot treat data...

  10. Ficolins and FIBCD1: Soluble and membrane bound pattern recognition molecules with acetyl group selectivity

    DEFF Research Database (Denmark)

    Thomsen, Theresa; Schlosser, Anders; Holmskov, Uffe

    2011-01-01

    as pattern recognition molecules. Ficolins are soluble oligomeric proteins composed of trimeric collagen-like regions linked to fibrinogen-related domains (FReDs) that have the ability to sense molecular patterns on both pathogens and apoptotic cell surfaces and activate the complement system. The ficolins......D-containing molecules, and discusses structural resemblance but also diversity in recognition of acetylated ligands....

  11. Assay for the pattern recognition molecule collectin liver 1 (CL-L1)

    DEFF Research Database (Denmark)

    Axelgaard, Esben; Jensenius, Jens Christian; Thiel, Steffen

    Collectin liver 1 (also termed collectin 10 and CL-L1) is a C-type lectin that functions as a pattern recognition molecule (PRM) in the innate immune system1. We have produced antibodies against CL-L1 and have developed a sandwich-type time-resolved immuno-fluorometric assay (TRIFMA...... to co-purify with MASPs, possibly rendering it a role in complement. CL-L1 showed binding activity towards mannose-TSK beads in a Ca2+-dependent manner. This binding could be inhibited by mannose and glucose, but not by galactose, indicating that CL-L1 binds via its carbohydrate-recognition domain (CRD)....

  12. Neurocomputing methods for pattern recognition in nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Gyulassy, M.; Dong, D.; Harlander, M. [Lawrence Berkeley Lab., CA (United States)

    1991-12-31

    We review recent progress on the development and applications of novel neurocomputing techniques for pattern recognition problems of relevance to RHIC experiments. The Elastic Tracking algorithm is shown to achieve sub-pad two track resolution without preprocessing. A high pass neural filter is developed for jet analysis and singular deconvolution methods are shown to recover the primordial jet distribution to a surprising high degree of accuracy.

  13. State of the art in cosmology

    International Nuclear Information System (INIS)

    Zel'dovich, Ya.B.

    1983-01-01

    The present state of the art in cosmology is under discussion. The general picture of the Universe evolution is presented, and its main stages are outlined. The prooess of formation of the large scale Universe structure is considered. The possibility of investigation into the ''inflation'' period of the ''very-very early Universe'' from the view point of theoretical physics is sown. It is noted that cosmology will become a complete science only when physics gives an exhaustive answer to all issues raised by cosmology

  14. Application of pattern recognition methods for evaluating the immune status in patients

    International Nuclear Information System (INIS)

    Stavitsky, R.B.; Guslistyj, I.V.; Miroshnichenko, I.V.; Karklinskaya, O.N.; Ryabinina, I.D.; Kosova, I.P.; Stolpnikova, V.N.; Malaeva, N.S.; Latypova, I.I.; Lebedev, L.A.

    2001-01-01

    The effectiveness of mathematical tools for pattern recognition as applied to numerical assessments of the immune status of patients exposed to ecological hazards is evaluated by experimentation. The immune status is estimated according to a two-class scheme (norm/abnormality) based on blood indicators of immunity for the patients examined. The task of categorizing patients by immunological parameters of blood is shown to be resolved with high effectiveness for determining the immune status [ru

  15. Human action recognition with depth cameras

    CERN Document Server

    Wang, Jiang; Wu, Ying

    2014-01-01

    Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, includi

  16. Aircraft wake vortices : a state-of-the-art review of the United States R&D program

    Science.gov (United States)

    1977-02-28

    The report summarizes the current state-of-the-art understanding : of the aircraft wake vortex phenomenon and the results of the United : States program to minimize the restrictions caused by aircraft wake : vortices in the terminal environment. The ...

  17. Use of nonstatistical techniques for pattern recognition to detect risk groups among liquidators of the Chernobyl NPP accident aftereffects

    International Nuclear Information System (INIS)

    Blinov, N.N.; Guslistyj, V.P.; Misyurev, A.V.; Novitskaya, N.N.; Snigireva, G.P.

    1993-01-01

    Attempt of using of the nonstatistical techniques for pattern recognition to detect the risk groups among liquidators of the Chernobyl NPP accident aftereffects was described. 14 hematologic, biochemical and biophysical blood serum parameters of the group of liquidators of the Chernobyl NPP accident impact as well as the group of donors free of any radiation dose (controlled group) were taken as the diagnostic parameters. Modification of the nonstatistical techniques for pattern recognition based on the assessment calculations were used. The patients were divided into risk group at the truth ∼ 80%

  18. Chernobyl - state of the art

    International Nuclear Information System (INIS)

    Souza, Daiane C.B. de; Vicente, Roberto; Rostelato, Maria Elisa C.M.; Borges, Jessica F.; Tiezzi, Rodrigo; Peleias Junior, Fernando S.; Souza, Carla D.; Rodrigues, Bruna T.; Benega, Marcos A.G.; Souza, Anderson S. de; Silva, Thais H. da

    2014-01-01

    This article aims to analyze what has been done so far in relation to damage caused by the accident and the state of art in Chernobyl, as well as the impact on radiation protection applied safety nuclear power plants. In the first part of the work a data survey was done through a bibliographic review and the in the second part data was collected during a visit, in June 2013 at the crash site, when was observed dose values in the affected areas and the works of repairs that have been made in the sarcophagus and surroundings as well as in official reports available through active international bodies. The main results indicate significant improvements in radiation protection systems

  19. User-Independent Motion State Recognition Using Smartphone Sensors.

    Science.gov (United States)

    Gu, Fuqiang; Kealy, Allison; Khoshelham, Kourosh; Shang, Jianga

    2015-12-04

    The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users' data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people's motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human's motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy.

  20. User-Independent Motion State Recognition Using Smartphone Sensors

    Directory of Open Access Journals (Sweden)

    Fuqiang Gu

    2015-12-01

    Full Text Available The recognition of locomotion activities (e.g., walking, running, still is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users’ data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people’s motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human’s motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy.

  1. Application of some pattern recognition methods for the early detection of failures at NPP components by means of noise diagnosis

    International Nuclear Information System (INIS)

    Weiss, F.P.

    1985-01-01

    The automation of the decisions on normality or abnormality of the plant condition being based on automated measurements is an essential step for the integration of noise diagnostics into the control and safety system of a nuclear power plant. By reason of the stochastic character of noise diagnostic measuring quantities principles of statistical pattern recognition are used in order automatically to get a decision on the plant condition. Four different pattern recognition methods complementing each other have been developed respectively tested with data from a WWER-440 type reactor. These four methods are included in a specially written software package. According to stationarity, correlation and probability distribution type of the state describing features and according to the necessary detection sensitivity to failures either the decorrelation method, the cluster method, the Parzen method or the distribution test of Wilcoxon, Mann and Whitney has to be applied. The efficiency and the limits of the investigated methods are discussed in detail. In context with the surveillance of the WWER-440 core by means of the power spectral densities of neutron flux fluctuations it could as well experimentally as theoretically be shown that the logarithmic power spectral densities follow a Gaussian probability distribution. (author)

  2. The Memory State Heuristic: A Formal Model Based on Repeated Recognition Judgments

    Science.gov (United States)

    Castela, Marta; Erdfelder, Edgar

    2017-01-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e.,…

  3. Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition.

    Science.gov (United States)

    Hansen, Mirko; Zahari, Finn; Ziegler, Martin; Kohlstedt, Hermann

    2017-01-01

    The use of interface-based resistive switching devices for neuromorphic computing is investigated. In a combined experimental and numerical study, the important device parameters and their impact on a neuromorphic pattern recognition system are studied. The memristive cells consist of a layer sequence Al/Al 2 O 3 /Nb x O y /Au and are fabricated on a 4-inch wafer. The key functional ingredients of the devices are a 1.3 nm thick Al 2 O 3 tunnel barrier and a 2.5 mm thick Nb x O y memristive layer. Voltage pulse measurements are used to study the electrical conditions for the emulation of synaptic functionality of single cells for later use in a recognition system. The results are evaluated and modeled in the framework of the plasticity model of Ziegler et al. Based on this model, which is matched to experimental data from 84 individual devices, the network performance with regard to yield, reliability, and variability is investigated numerically. As the network model, a computing scheme for pattern recognition and unsupervised learning based on the work of Querlioz et al. (2011), Sheridan et al. (2014), Zahari et al. (2015) is employed. This is a two-layer feedforward network with a crossbar array of memristive devices, leaky integrate-and-fire output neurons including a winner-takes-all strategy, and a stochastic coding scheme for the input pattern. As input pattern, the full data set of digits from the MNIST database is used. The numerical investigation indicates that the experimentally obtained yield, reliability, and variability of the memristive cells are suitable for such a network. Furthermore, evidence is presented that their strong I - V non-linearity might avoid the need for selector devices in crossbar array structures.

  4. Acoustic modeling for emotion recognition

    CERN Document Server

    Anne, Koteswara Rao; Vankayalapati, Hima Deepthi

    2015-01-01

     This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

  5. Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

    Directory of Open Access Journals (Sweden)

    Andre F Marquand

    Full Text Available Progressive supranuclear palsy (PSP, multiple system atrophy (MSA and idiopathic Parkinson's disease (IPD can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs. An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i a subcortical motor network; (ii each of its component regions and (iii the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

  6. Ética: a aprendizagem da arte de viver Ethics: learning the art of living

    Directory of Open Access Journals (Sweden)

    Nadja Hermann

    2008-04-01

    Full Text Available O trabalho discute, numa abordagem filosófica, a formação ética, a partir das possibilidades da arte de viver. Explicita que a arte de viver tem uma dimensão estética em que própria obra da vida tem a arte como modelo, por meio da criação de diferentes estratégias (desde as interativas até as literárias, articuladas com princípios universais. Esta ética, com seu apelo às condições concretas da vida e aos sentimentos, não exclui o reconhecimento de uma normatividade que ultrapassa as regras criadas pelo próprio sujeito, ou seja, universalidade e particularidade não se excluem. O texto apresenta (1 a contribuição helenística para a arte de viver, por meio do modelo terapêutico de filosofar, e (2 o papel das emoções e da phronesis na articulação entre o universal e o particular, para apontar que (3 uma educação ético-estética se constitui pelo reconhecimento da tensão entre o eu singular e o nós (ethos comum.With a philosophical approach, this work provides a discussion about ethical education from the possibilities of the art of living. It states that the art of living has an aesthetic dimension which is used by life itself as a model, with the creation of different strategies (from interactive to literary related to universal principles. With its appeal to feelings and to life's concrete conditions, this ethics does not exclude the recognition of a norm that excels the rules created by a subject; that is, universality and particularity do not exclude each other. The text presents (1 the Hellenic contribution to the art of living, through the therapeutic philosophizing model and (2 the role of emotions and phronesis in the relation between the universal and private domains to indicate that (3 an ethical-aesthetic kind of education is constituted by the recognition of tension between the singular I and (the common ethos we.

  7. Ultrasonic pattern recognition study of feedwater nozzle inner radius indication

    International Nuclear Information System (INIS)

    Yoneyama, H.; Takama, S.; Kishigami, M.; Sasahara, T.; Ando, H.

    1983-01-01

    A study was made to distinguish defects on feed-water nozzle inner radius from noise echo caused by stainless steel cladding by using ultrasonic pattern recognition method with frequency analysis technique. Experiment has been successfully performed on flat clad plates and nozzle mock-up containing fatigue cracks and the following results which shows the high capability of frequency analysis technique are obtained

  8. As pesquisas denominadas "estado da arte" Research called "state of the art"

    Directory of Open Access Journals (Sweden)

    Norma Sandra de Almeida Ferreira

    2002-08-01

    Full Text Available Nos últimos quinze anos, no Brasil e em outros países, tem se produzido um conjunto significativo de pesquisas conhecidas pela denominação "estado da arte" ou "estado do conhecimento". Definidas como de caráter bibliográfico, elas parecem trazer em comum o desafio de mapear e de discutir uma certa produção acadêmica em diferentes campos do conhecimento, tentando responder que aspectos e dimensões vêm sendo destacados e privilegiados em diferentes épocas e lugares, de que formas e em que condições têm sido produzidas certas dissertações de mestrado, teses de doutorado, publicações em periódicos e comunicações em anais de congressos e de seminários. Neste artigo levanto e tento responder as seguintes questões: seria possível fazer um esforço de interrogar a história a produção acadêmica sobre determinada área do conhecimento, optando por ler apenas dados bibliográficos e resumos dos trabalhos? O que significa ler esse lugar (catálogos, instituição de divulgação dos trabalhos, tomando-o como fonte documental para um mapeamento da produção acadêmica, em pesquisas denominadas "estado da arte"?These last fifteen years, Brazil and other countries have seen the production of a significant set of research, known as "state of the art" or "state of knowledge". Defined as having a bibliographic feature, they seem to share the challenge of mapping and discussing a certain academic production in different fields of knowledge. They try to show which aspects and dimensions have been highlighted and privileged at different times and places. They also pinpoint how and in what conditions certain kinds of master's degree thesis and doctor's degree dissertations, publications in periodicals and communications in annals of congress and seminary were produced. In this article, I pose and try to answer the following questions: Is it worth making the effort of interrogating the history of the academic production about a given area

  9. Modeling of state recognition process of plant operator

    International Nuclear Information System (INIS)

    Hatakeyama, Naoki; Furuta, Kazuo

    2000-01-01

    It is necessary to automate Machine systems because they have become larger and more complicated these years. Generally speaking, humans hardly grasp the overall state in the automated systems. In fact it is reported that the accident caused by this problem occurs. To avoid such accidents, there were many studies to give human the authority of final decision making. In general it depends on circumstances whether the authority of decision making is given humans or machine systems. It is supposed therefore that humans and machine systems exchange their information each other and efficiently share their tasks. It is necessary that machine systems infer human intention in these systems. There were not enough considerations on state recognition process which is important to infer human intention. In this paper we first reconstructed human knowledge into a hierarchy and incorporated these knowledge into a Bayesian network. Next we modeled the state recognition process by using the Bayesian network. (author)

  10. The Impact of ART on Live Birth Outcomes: Differing Experiences across Three States.

    Science.gov (United States)

    Luke, Sabrina; Sappenfield, William M; Kirby, Russell S; McKane, Patricia; Bernson, Dana; Zhang, Yujia; Chuong, Farah; Cohen, Bruce; Boulet, Sheree L; Kissin, Dmitry M

    2016-05-01

    Research has shown an association between assisted reproductive technology (ART) and adverse birth outcomes. We identified whether birth outcomes of ART-conceived pregnancies vary across states with different maternal characteristics, insurance coverage for ART services, and type of ART services provided. CDC's National ART Surveillance System data were linked to Massachusetts, Florida, and Michigan vital records from 2000 through 2006. Maternal characteristics in ART- and non-ART-conceived live births were compared between states using chi-square tests. We performed multivariable logistic regression analyses and calculated adjusted odds ratios (aOR) to assess associations between ART use and singleton preterm delivery (birth. ART use in Massachusetts was associated with significantly lower odds of twins as well as triplets and higher order births compared to Florida and Michigan (aOR 22.6 vs. 30.0 and 26.3, and aOR 37.6 vs. 92.8 and 99.2, respectively; Pinteraction order gestations per cycle was lower in Massachusetts, which may be due to the availability of insurance coverage for ART in Massachusetts. © 2016 John Wiley & Sons Ltd.

  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. A quick guide to wind power forecating : state-of-the-art 2009.

    Energy Technology Data Exchange (ETDEWEB)

    Monteiro, C.; Keko, H.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    This document contains a summary of the main findings from our full report entitled 'Wind Power Forecasting: State-of-the-Art 2009'. The aims of this document are to provide guidelines and a quick overview of the current state-of-the-art in wind power forecasting (WPF) and to point out lines of research in the future development of forecasting systems.

  14. Visual Scanning Patterns and Executive Function in Relation to Facial Emotion Recognition in Aging

    Science.gov (United States)

    Circelli, Karishma S.; Clark, Uraina S.; Cronin-Golomb, Alice

    2012-01-01

    Objective The ability to perceive facial emotion varies with age. Relative to younger adults (YA), older adults (OA) are less accurate at identifying fear, anger, and sadness, and more accurate at identifying disgust. Because different emotions are conveyed by different parts of the face, changes in visual scanning patterns may account for age-related variability. We investigated the relation between scanning patterns and recognition of facial emotions. Additionally, as frontal-lobe changes with age may affect scanning patterns and emotion recognition, we examined correlations between scanning parameters and performance on executive function tests. Methods We recorded eye movements from 16 OA (mean age 68.9) and 16 YA (mean age 19.2) while they categorized facial expressions and non-face control images (landscapes), and administered standard tests of executive function. Results OA were less accurate than YA at identifying fear (precognition of sad expressions and with scanning patterns for fearful, sad, and surprised expressions. Conclusion We report significant age-related differences in visual scanning that are specific to faces. The observed relation between scanning patterns and executive function supports the hypothesis that frontal-lobe changes with age may underlie some changes in emotion recognition. PMID:22616800

  15. The LIFE Laser Design in Context: A Comparison to the State-of-the-Art

    International Nuclear Information System (INIS)

    Deri, R.J.; Bayramian, A.J.; Erlandson, A.C.

    2011-01-01

    The current point design for the LIFE laser leverages decades of solid-state laser development in order to achieve the performance and attributes required for inertial fusion energy. This document provides a brief comparison of the LIFE laser point design to other state-of-the-art solid-state lasers. Table I compares the attributes of the current LIFE laser point design to other systems. the state-of-the-art for single-shot performance at fusion-relevant beamline energies is exemplified by performance observed on the National Ignition Facility. The state-of-the-art for high average power is exemplified by the Northrup Grumman JHPSSL laser. Several items in Table I deal with the laser efficiency; a more detailed discussion of efficiency can be found in reference 5. The electrical-to-optical efficiency of the LIFE design exceeds that of reference 4 due to the availability of higher efficiency laser diode pumps (70% vs. ∼50% used in reference 4). LIFE diode pumps are discussed in greater detail in reference 6. The 'beam steering' state of the art is represented by the deflection device that will be used in the LIFE laser, not a laser system. Inspection of Table I shows that most LIFE laser attributes have already been experimentally demonstrated. The two cases where the LIFE design is somewhat better than prior experimental work do not involve the development of new concepts: beamline power is increased simply by increasing aperture (as demonstrated by the power/aperture comparison in Table I), and efficiency increases are achieved by employing state-of-the-art diode pumps. In conclusion, the attributes anticipated for the LIFE laser are consistent with the demonstrated performance of existing solid-state lasers.

  16. Human Walking Pattern Recognition Based on KPCA and SVM with Ground Reflex Pressure Signal

    Directory of Open Access Journals (Sweden)

    Zhaoqin Peng

    2013-01-01

    Full Text Available Algorithms based on the ground reflex pressure (GRF signal obtained from a pair of sensing shoes for human walking pattern recognition were investigated. The dimensionality reduction algorithms based on principal component analysis (PCA and kernel principal component analysis (KPCA for walking pattern data compression were studied in order to obtain higher recognition speed. Classifiers based on support vector machine (SVM, SVM-PCA, and SVM-KPCA were designed, and the classification performances of these three kinds of algorithms were compared using data collected from a person who was wearing the sensing shoes. Experimental results showed that the algorithm fusing SVM and KPCA had better recognition performance than the other two methods. Experimental outcomes also confirmed that the sensing shoes developed in this paper can be employed for automatically recognizing human walking pattern in unlimited environments which demonstrated the potential application in the control of exoskeleton robots.

  17. Face recognition in the thermal infrared domain

    Science.gov (United States)

    Kowalski, M.; Grudzień, A.; Palka, N.; Szustakowski, M.

    2017-10-01

    Biometrics refers to unique human characteristics. Each unique characteristic may be used to label and describe individuals and for automatic recognition of a person based on physiological or behavioural properties. One of the most natural and the most popular biometric trait is a face. The most common research methods on face recognition are based on visible light. State-of-the-art face recognition systems operating in the visible light spectrum achieve very high level of recognition accuracy under controlled environmental conditions. Thermal infrared imagery seems to be a promising alternative or complement to visible range imaging due to its relatively high resistance to illumination changes. A thermal infrared image of the human face presents its unique heat-signature and can be used for recognition. The characteristics of thermal images maintain advantages over visible light images, and can be used to improve algorithms of human face recognition in several aspects. Mid-wavelength or far-wavelength infrared also referred to as thermal infrared seems to be promising alternatives. We present the study on 1:1 recognition in thermal infrared domain. The two approaches we are considering are stand-off face verification of non-moving person as well as stop-less face verification on-the-move. The paper presents methodology of our studies and challenges for face recognition systems in the thermal infrared domain.

  18. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    Directory of Open Access Journals (Sweden)

    Lahiru Iddamalgoda

    2016-08-01

    Full Text Available Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification and scoring based prioritization methods for determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI methods in conjunction with the K nearest neighbors’ could be used in accurately categorizing the genetic factors in disease causation

  19. The job demands-resources model : state of the art

    NARCIS (Netherlands)

    Bakker, A.B.; Demerouti, E.

    2007-01-01

    Purpose - The purpose of this paper is to give a state-of-the art overview of the Job Demands-Resources (JD-R) model Design/methodology/approach - The strengths and weaknesses of the demand-control model and the effort-reward imbalance model regarding their predictive value for employee well being

  20. Race, Ethnicity and Participation in the Arts: Patterns of Participation by Black, Hispanic and White Americans in Selected Activities from the 1982 and 1985 Surveys of Public Participation in the Arts.

    Science.gov (United States)

    DiMaggio, Paul; Ostrower, Francie

    This report utilizes data from the 1982 and 1985 Surveys of Public Participation in the Arts to describe differences in patterns of participation in selected arts related activities by Black, Hispanic, and White respondents. Arts participation by Whites is greatest for all selected activities, except for Black attendance at jazz music activities.…

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

    Directory of Open Access Journals (Sweden)

    Shouyi Yin

    2015-01-01

    Full Text Available Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

  2. Facial Expression Recognition of Various Internal States via Manifold Learning

    Institute of Scientific and Technical Information of China (English)

    Young-Suk Shin

    2009-01-01

    Emotions are becoming increasingly important in human-centered interaction architectures. Recognition of facial expressions, which are central to human-computer interactions, seems natural and desirable. However, facial expressions include mixed emotions, continuous rather than discrete, which vary from moment to moment. This paper represents a novel method of recognizing facial expressions of various internal states via manifold learning, to achieve the aim of humancentered interaction studies. A critical review of widely used emotion models is described, then, facial expression features of various internal states via the locally linear embedding (LLE) are extracted. The recognition of facial expressions is created with the pleasure-displeasure and arousal-sleep dimensions in a two-dimensional model of emotion. The recognition result of various internal state expressions that mapped to the embedding space via the LLE algorithm can effectively represent the structural nature of the two-dimensional model of emotion. Therefore our research has established that the relationship between facial expressions of various internal states can be elaborated in the two-dimensional model of emotion, via the locally linear embedding algorithm.

  3. A 'sense of urgency': The EU, the EU member states and the recognition of the Palestinian state

    OpenAIRE

    Martins, Bruno Oliveira

    2015-01-01

    In the aftermath of the July-August 2014 war in Gaza, the Swedish government officially recognized the State of Palestine. This decision triggered a cascade of resolutions adopted in national parliaments of European Union member states and, eventually, led to the adoption of a European Parliament resolution supporting in principle the recognition of Palestinian statehood. Understood collectively, these efforts constitute a multifaceted European attempt to break with the status quo of the Isra...

  4. Automated analysis of art object surfaces using time-averaged digital speckle pattern interferometry

    Science.gov (United States)

    Lukomski, Michal; Krzemien, Leszek

    2013-05-01

    Technical development and practical evaluation of a laboratory built, out-of-plane digital speckle pattern interferometer (DSPI) are reported. The instrument was used for non-invasive, non-contact detection and characterization of early-stage damage, like fracturing and layer separation, of painted objects of art. A fully automated algorithm was developed for recording and analysis of vibrating objects utilizing continuous-wave laser light. The algorithm uses direct, numerical fitting or Hilbert transformation for an independent, quantitative evaluation of the Bessel function at every point of the investigated surface. The procedure does not require phase modulation and thus can be implemented within any, even the simplest, DSPI apparatus. The proposed deformation analysis is fast and computationally inexpensive. Diagnosis of physical state of the surface of a panel painting attributed to Nicolaus Haberschrack (a late-mediaeval painter active in Krakow) from the collection of the National Museum in Krakow is presented as an example of an in situ application of the developed methodology. It has allowed the effectiveness of the deformation analysis to be evaluated for the surface of a real painting (heterogeneous colour and texture) in a conservation studio where vibration level was considerably higher than in the laboratory. It has been established that the methodology, which offers automatic analysis of the interferometric fringe patterns, has a considerable potential to facilitate and render more precise the condition surveys of works of art.

  5. Skills and the appreciation of computer art

    Science.gov (United States)

    Boden, Margaret A.

    2016-04-01

    The appreciation of art normally includes recognition of the artist's skills in making it. Most people cannot appreciate computer art in that way, because they know little or nothing about coding. Various suggestions are made about how computer artists and/or curators might design and present computer art in such a way as to make the relevant making-skills more intelligible.

  6. Development of pattern recognition algorithms for the central drift chamber of the Belle II detector

    Energy Technology Data Exchange (ETDEWEB)

    Trusov, Viktor

    2016-11-04

    In this thesis, the development of one of the pattern recognition algorithms for the Belle II experiment based on conformal and Legendre transformations is presented. In order to optimize the performance of the algorithm (CPU time and efficiency) specialized processing steps have been introduced. To show achieved results, Monte-Carlo based efficiency measurements of the tracking algorithms in the Central Drift Chamber (CDC) has been done.

  7. A New Functional Classification of Glucuronoyl Esterases by Peptide Pattern Recognition

    DEFF Research Database (Denmark)

    Wittrup Agger, Jane; Busk, Peter Kamp; Pilgaard, Bo

    2017-01-01

    of characterized enzymes exist and the exact activity is still uncertain. Here peptide pattern recognition is used as a bioinformatic tool to identify and group new CE15 proteins that are likely to have glucuronoyl esterase activity. 1024 CE15-like sequences were drawn from GenBank and grouped into 24 groups...

  8. Human serum albumin supported lipid patterns for the targeted recognition of microspheres coated by membrane based on ss-DNA hybridization

    International Nuclear Information System (INIS)

    Zhang Xiaoming; He Qiang; Cui Yue; Duan Li; Li Junbai

    2006-01-01

    Human serum albumin (HSA) patterns have been successfully fabricated for the deposition of lipid bilayer, 1,2-dimyristoyl-sglycerophosphate (DMPA), by making use of the micro-contact printing (μCP) technique and liposome fusion. Confocal laser scanning microscopy (CLSM) results indicate that lipid bilayer has been assembled in HSA patterns with a good stability. Such well-defined lipid patterns formed on HSA surface create possibility to incorporate specific components like channels or receptors for specific recognition. In view of this, microspheres coated with lipid membranes were immobilized in HSA-supported lipid patterns via the hybridization of complementary ss-DNAs. This procedure enables to transfer solid materials to a soft surface through a specific recognition

  9. Increasing the effectiveness of the hydraulic fracturing of seams with the use of the pattern recognition method

    Energy Technology Data Exchange (ETDEWEB)

    Rasizade, Ya M; Nagiev, T M; Kuznetsov, V I; Mikerin, B P

    1977-08-01

    An examination is made of using a sequential diagnostic procedure for increasing the effectiveness of the hydraulic fracturing of seams in boreholes of the gas and oil drilling administration of the Khadyzhenneft' association. The use of the pattern recognition method was shown to make it possible to increase the effectiveness of hydraulic fracturing by up to 80%. 4 references, 1 figure, 3 tables.

  10. Influence of the signer's psychophysiological state on the results of his identification using handwritten pattern by natural and artificial intelligence

    Directory of Open Access Journals (Sweden)

    Alexey E. Sulavko

    2017-11-01

    Full Text Available At present, while various mechanisms to ensure information security are actively being improved, particular attention is paid to prevent unauthorized access to information resources.  The human factor and process of identification still remain the most problematic, as well as user authentication. A progress in the technology of information resources protection from internal security threats paves its way towards biometric systems of hidden identification of computer users and their psychophysiological state. A change in psychophysiological state results in the person's handwriting. The influence of the signer’s state of fatigue and excitation on the results of its identification both by a person and by pattern recognition methods on reproduced signatures are studied. Capabilities of human and artificial intelligence are compared in equal conditions. When the state of the signer changes, the probability of erroneous recognition by artificial intelligence increases by factor 3.3 to 3.7. A person identifies a handwritten image with fewer errors in case when the signer is agitated, and with higher error rate if the signer is tired.

  11. Nickel-base superalloy powder metallurgy: state-of-the-art

    International Nuclear Information System (INIS)

    Allen, M.M.; Athey, R.L.; Moore, J.B.

    1975-01-01

    Development of powder metallurgical methods for fabrication of Ni-base superalloy turbine engine disks is reviewed. Background studies are summarized and current state-of-art is discussed for the F100 jet engine, advanced applications, and forging processes

  12. Role of pattern recognition receptors of the neurovascular unit in inflamm-aging.

    Science.gov (United States)

    Wilhelm, Imola; Nyúl-Tóth, Ádám; Kozma, Mihály; Farkas, Attila E; Krizbai, István A

    2017-11-01

    Aging is associated with chronic inflammation partly mediated by increased levels of damage-associated molecular patterns, which activate pattern recognition receptors (PRRs) of the innate immune system. Furthermore, many aging-related disorders are associated with inflammation. PRRs, such as Toll-like receptors (TLRs) and nucleotide-binding oligomerization domain-like receptors (NLRs), are expressed not only in cells of the innate immune system but also in other cells, including cells of the neurovascular unit and cerebral vasculature forming the blood-brain barrier. In this review, we summarize our present knowledge about the relationship between activation of PRRs expressed by cells of the neurovascular unit-blood-brain barrier, chronic inflammation, and aging-related pathologies of the brain. The most important damage-associated molecular pattern-sensing PRRs in the brain are TLR2, TLR4, and NLR family pyrin domain-containing protein-1 and pyrin domain-containing protein-3, which are activated during physiological and pathological aging in microglia, neurons, astrocytes, and possibly endothelial cells and pericytes. Copyright © 2017 the American Physiological Society.

  13. Symposium Connects Government Problems with State of the Art Network Science Research

    Science.gov (United States)

    2015-10-16

    Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering

  14. Research on Attribute Reduction in Hoisting Motor State Recognition of Quayside Container Crane

    Science.gov (United States)

    Li, F.; Tang, G.; Hu, X.

    2017-07-01

    In view of too many attributes in hoisting motor state recognition of quayside container crane. Attribute reduction method based on discernibility matrix is introduced to attribute reduction of lifting motor state information table. A method of attribute reduction based on the combination of rough set and genetic algorithm is proposed to deal with the hoisting motor state decision table. Under the condition that the information system's decision-making ability is unchanged, the redundant attribute is deleted. Which reduces the complexity and computation of the recognition process of the hoisting motor. It is possible to realize the fast state recognition.

  15. Shape-based hand recognition approach using the morphological pattern spectrum

    Science.gov (United States)

    Ramirez-Cortes, Juan Manuel; Gomez-Gil, Pilar; Sanchez-Perez, Gabriel; Prieto-Castro, Cesar

    2009-01-01

    We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good feature-extraction alternative for low- and medium-level hand-shape-based biometric applications.

  16. Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

    DEFF Research Database (Denmark)

    Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

    2016-01-01

    The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

  17. Pattern recognition in spectra

    International Nuclear Information System (INIS)

    Gebran, M; Paletou, F

    2017-01-01

    We present a new automated procedure that simultaneously derives the effective temperature T eff , surface gravity log g , metallicity [ Fe/H ], and equatorial projected rotational velocity v e sin i for stars. The procedure is inspired by the well-known PCA-based inversion of spectropolarimetric full-Stokes solar data, which was used both for Zeeman and Hanle effects. The efficiency and accuracy of this procedure have been proven for FGK, A, and late type dwarf stars of K and M spectral types. Learning databases are generated from the Elodie stellar spectra library using observed spectra for which fundamental parameters were already evaluated or with synthetic data. The synthetic spectra are calculated using ATLAS9 model atmospheres. This technique helped us to detect many peculiar stars such as Am, Ap, HgMn, SiEuCr and binaries. This fast and efficient technique could be used every time a pattern recognition is needed. One important application is the understanding of the physical properties of planetary surfaces by comparing aboard instrument data to synthetic ones. (paper)

  18. Extended pattern recognition scheme for self-learning kinetic Monte Carlo simulations

    International Nuclear Information System (INIS)

    Shah, Syed Islamuddin; Nandipati, Giridhar; Kara, Abdelkader; Rahman, Talat S

    2012-01-01

    We report the development of a pattern recognition scheme that takes into account both fcc and hcp adsorption sites in performing self-learning kinetic Monte Carlo (SLKMC-II) simulations on the fcc(111) surface. In this scheme, the local environment of every under-coordinated atom in an island is uniquely identified by grouping fcc sites, hcp sites and top-layer substrate atoms around it into hexagonal rings. As the simulation progresses, all possible processes, including those such as shearing, reptation and concerted gliding, which may involve fcc-fcc, hcp-hcp and fcc-hcp moves are automatically found, and their energetics calculated on the fly. In this article we present the results of applying this new pattern recognition scheme to the self-diffusion of 9-atom islands (M 9 ) on M(111), where M = Cu, Ag or Ni.

  19. Measuring the State-of-the-Art in Laser Cut Quality

    OpenAIRE

    Pocorni, Jetro; Powell, John; Ilar, Torbjörn; Schwarz, A.; Kaplan, Alexander

    2013-01-01

    This paper discusses the strategy appropriate to investigating the state of the art of laser cutting from an industrial point of view. The importance of creating the samples in a high quality industrial environment is emphasised and preliminary results are presented.

  20. 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)

  1. 20 CFR 408.1230 - Can you waive State recognition payments?

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Can you waive State recognition payments? 408.1230 Section 408.1230 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SPECIAL BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1230 Can you waive...

  2. 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.

  3. Development of a state-of-the-art solid waste characterisation facility at JRC ISPRA

    International Nuclear Information System (INIS)

    Huhtiniemi, I.; Anselmi, M.; Hubert, P.; Vassallo, G.

    2003-01-01

    This paper will review the development and construction of a state-of-the-art waste characterisation facility that represents a fundamental element in the JRC's strategy to characterise radioactive wastes originating from four decades of nuclear research activities conducted at the Ispra Site. The state-of-the-art NDA measurement solution selected by JRC-Ispra will be presented in the light of special requirements imposed by applicable Italian legislation, norms and the qualities of the waste packages. The intended plant combines the state-of-the-art-measurement solution with comprehensive process automation in an industrial environment and is therefore of significant interest to the radioactive waste management community. (orig.)

  4. Flexible AC transmission systems: the state of the art

    Energy Technology Data Exchange (ETDEWEB)

    Edris, Abdel-Aty [Electric Power Research Inst., Palo Alto, CA (United States). Electric Systems Division

    1994-12-31

    Flexible AC transmission systems (FACTS) is a concept promoting the use of power electronic controllers to enhance the controllability and usable capacity of AC transmission. This paper presents the state of the art of FACTS and the status of the current projects for the application of the FACTS controllers in transmission systems. (author) 8 refs., 8 figs.

  5. An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

    Science.gov (United States)

    Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

    2016-04-01

    Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

  6. Fabricating biomedical origami: a state-of-the-art review.

    Science.gov (United States)

    Johnson, Meredith; Chen, Yue; Hovet, Sierra; Xu, Sheng; Wood, Bradford; Ren, Hongliang; Tokuda, Junichi; Tse, Zion Tsz Ho

    2017-11-01

    Origami-based biomedical device design is an emerging technology due to its ability to be deployed from a minimal foldable pattern to a larger volume. This paper aims to review state-of-the-art origami structures applied in the medical device field. Publications and reports of origami structure related to medical device design from the past 10 years are reviewed and categorized according to engineering specifications, including the application field, fabrication material, size/volume, deployment method, manufacturability, and advantages. This paper presents an overview of the biomedical applications of devices based on origami structures, including disposable sterilization covers, cardiac catheterization, stent grafts, encapsulation and microsurgery, gastrointestinal microsurgery, laparoscopic surgical grippers, microgrippers, microfluidic devices, and drug delivery. Challenges in terms of materials and fabrication, assembly, modeling and computation design, and clinical adoptability are discussed at the end of this paper to provide guidance for future origami-based design in the medical device field. Concepts from origami can be used to design and develop novel medical devices. Origami-based medical device design is currently progressing, with researchers improving design methods, materials, fabrication techniques, and folding efficiency.

  7. Assessment of the State of the Art of Flight Control Technologies as Applicable to Adverse Conditions

    Science.gov (United States)

    Reveley, Mary s.; Briggs, Jeffrey L.; Leone, Karen M.; Kurtoglu, Tolga; Withrow, Colleen A.

    2010-01-01

    Literature from academia, industry, and other Government agencies was surveyed to assess the state of the art in current Integrated Resilient Aircraft Control (IRAC) aircraft technologies. Over 100 papers from 25 conferences from the time period 2004 to 2009 were reviewed. An assessment of the general state of the art in adaptive flight control is summarized first, followed by an assessment of the state of the art as applicable to 13 identified adverse conditions. Specific areas addressed in the general assessment include flight control when compensating for damage or reduced performance, retrofit software upgrades to flight controllers, flight control through engine response, and finally test and validation of new adaptive controllers. The state-of-the-art assessment applicable to the adverse conditions include technologies not specifically related to flight control, but may serve as inputs to a future flight control algorithm. This study illustrates existing gaps and opportunities for additional research by the NASA IRAC Project

  8. Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

    Science.gov (United States)

    Wei, Wei; Jia, Qingxuan

    2016-01-01

    Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

  9. Changes in Reported Sexual Orientation Following US States Recognition of Same-Sex Couples

    Science.gov (United States)

    Corliss, Heather L.; Spiegelman, Donna; Williams, Kerry; Austin, S. Bryn

    2016-01-01

    Objectives. To compare changes in self-reported sexual orientation of women living in states with any recognition of same-sex relationships (e.g., hospital visitation, domestic partnerships) with those of women living in states without such recognition. Methods. We calculated the likelihood of women in the Nurses’ Health Study II (n = 69 790) changing their reported sexual orientation between 1995 and 2009. Results. We used data from the Nurses’ Health Study II and found that living in a state with same-sex relationship recognition was associated with changing one’s reported sexual orientation, particularly from heterosexual to sexual minority. Individuals who reported being heterosexual in 1995 were 30% more likely to report a minority orientation (i.e., bisexual or lesbian) in 2009 (risk ratio = 1.30; 95% confidence interval = 1.05, 1.61) if they lived in a state with any recognition of same-sex relationships compared with those who lived in a state without such recognition. Conclusions. Policies recognizing same-sex relationships may encourage women to report a sexual minority orientation. Future research is needed to clarify how other social and legal policies may affect sexual orientation self-reports. PMID:27736213

  10. Molecular recognition of AT-DNA sequences by the induced CD pattern of dibenzotetraaza[14]annulene (DBTAA)-adenine derivatives.

    Science.gov (United States)

    Stojković, Marijana Radić; Skugor, Marko; Dudek, Lukasz; Grolik, Jarosław; Eilmes, Julita; Piantanida, Ivo

    2014-01-01

    An investigation of the interactions of two novel and several known DBTAA-adenine conjugates with double-stranded DNA and RNA has revealed the DNA/RNA groove as the dominant binding site, which is in contrast to the majority of previously studied DBTAA analogues (DNA/RNA intercalators). Only DBTAA-propyladenine conjugates revealed the molecular recognition of AT-DNA by an ICD band pattern > 300 nm, whereas significant ICD bands did not appear for other ds-DNA/RNA. A structure-activity relation for the studied series of compounds showed that the essential structural features for the ICD recognition are a) the presence of DNA-binding appendages (adenine side chain and positively charged side chain) on both DBTAA side chains, and b) the presence of a short propyl linker, which does not support intramolecular aromatic stacking between DBTAA and adenine. The observed AT-DNA-ICD pattern differs from previously reported ss-DNA (poly dT) ICD recognition by a strong negative ICD band at 350 nm, which allows for the dynamic differentiation between ss-DNA (poly dT) and coupled ds-AT-DNA.

  11. Three State-of-the-Art Methods for Condition Monitoring

    NARCIS (Netherlands)

    Grimmelius, H.T.; Meiler, P.P.; Maas, H.L.M.M.; Bonnier, B.; Grevink, J.S.; Kuilenburg, R.F. van

    1999-01-01

    This paper describes and compares three different state-of-the-art condition monitoring techniques: first principles, feature extraction, and neural networks. The focus of the paper is on the application of the techniques, not on the underlying theory. Each technique is described briefly and is

  12. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-03-20

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  13. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

  14. Haar-like Features for Robust Real-Time Face Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Face recognition is still a very challenging task when the input face image is noisy, occluded by some obstacles, of very low-resolution, not facing the camera, and not properly illuminated. These problems make the feature extraction and consequently the face recognition system unstable....... The proposed system in this paper introduces the novel idea of using Haar-like features, which have commonly been used for object detection, along with a probabilistic classifier for face recognition. The proposed system is simple, real-time, effective and robust against most of the mentioned problems....... Experimental results on public databases show that the proposed system indeed outperforms the state-of-the-art face recognition systems....

  15. The review and results of different methods for facial recognition

    Science.gov (United States)

    Le, Yifan

    2017-09-01

    In recent years, facial recognition draws much attention due to its wide potential applications. As a unique technology in Biometric Identification, facial recognition represents a significant improvement since it could be operated without cooperation of people under detection. Hence, facial recognition will be taken into defense system, medical detection, human behavior understanding, etc. Several theories and methods have been established to make progress in facial recognition: (1) A novel two-stage facial landmark localization method is proposed which has more accurate facial localization effect under specific database; (2) A statistical face frontalization method is proposed which outperforms state-of-the-art methods for face landmark localization; (3) It proposes a general facial landmark detection algorithm to handle images with severe occlusion and images with large head poses; (4) There are three methods proposed on Face Alignment including shape augmented regression method, pose-indexed based multi-view method and a learning based method via regressing local binary features. The aim of this paper is to analyze previous work of different aspects in facial recognition, focusing on concrete method and performance under various databases. In addition, some improvement measures and suggestions in potential applications will be put forward.

  16. Very deep recurrent convolutional neural network for object recognition

    Science.gov (United States)

    Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

    2017-03-01

    In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

  17. Leadership and Fairness: The state of the art.

    OpenAIRE

    van Knippenberg, D.; de Cremer, D.; van Knippenberg, B.M.

    2007-01-01

    textabstractResearch in leadership effectiveness has paid less to the role of leader fairness than probably it should have. More recently, this has started to change. To capture this development, we review the empirical literature in leadership and fairness to define the field of leadership and fairness, to assess the state of the art, and to identify a research agenda for future efforts in the field. The review shows that leader distributive, procedural, and especially interactional fairness...

  18. Nuclear Liability, State of the Art

    International Nuclear Information System (INIS)

    Reitsma, S. M. S.

    2010-01-01

    Over fifty years ago states started to introduce legislation protecting the public against the potential magnitude and peculiarity of risks arising from the nuclear energy production. They did so trough a specific liability and compensation regime. Whether legislation was based on national initiatives or, as more frequently, related to international nuclear liability conventions, it was based on a number of principles being applied universally. Furthermore, it at the same time strived for not preventing the development of the nuclear industry because of an unbearable liability. This paper aims at explaining the broad outline of the above legislation, its development since its early years, the state of the art as regards its modernisation as well as the (alleged) problems underlying the delay in its introduction in a number of countries. When dealing with those problems it will be inevitable to touch upon a number of insurance related matters, which, as an insurer I am happy to tell, will lead me to familiar territory.(author).

  19. 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...

  20. Physics of Automatic Target Recognition

    CERN Document Server

    Sadjadi, Firooz

    2007-01-01

    Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

  1. Chernobyl - state of the art; Chernobyl - o estado da arte

    Energy Technology Data Exchange (ETDEWEB)

    Souza, Daiane C.B. de; Vicente, Roberto; Rostelato, Maria Elisa C.M.; Borges, Jessica F.; Tiezzi, Rodrigo; Peleias Junior, Fernando S.; Souza, Carla D.; Rodrigues, Bruna T.; Benega, Marcos A.G.; Souza, Anderson S. de; Silva, Thais H. da, E-mail: dcsouza@ipen.br, E-mail: rvicente@ipen.br, E-mail: elisaros@ipen.br, E-mail: rtiezzi@ipen.br, E-mail: carladdsouza@yahoo.com.br, E-mail: marcosagbenega@ipen.br, E-mail: bteigarodrigues@gmail.com, E-mail: thaishunk@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2014-07-01

    This article aims to analyze what has been done so far in relation to damage caused by the accident and the state of art in Chernobyl, as well as the impact on radiation protection applied safety nuclear power plants. In the first part of the work a data survey was done through a bibliographic review and the in the second part data was collected during a visit, in June 2013 at the crash site, when was observed dose values in the affected areas and the works of repairs that have been made in the sarcophagus and surroundings as well as in official reports available through active international bodies. The main results indicate significant improvements in radiation protection systems.

  2. Paediatric thoracoscopy: State of the art | Van Niekerk | South ...

    African Journals Online (AJOL)

    Many advanced procedures, including lobectomy, repair of tracheo-oesophageal fistula, excision of mediastinal tumours and diaphragmatic hernia repairs, are being done routinely in paediatric surgery centres around the world. This article reviews the state of the art of thoracoscopic surgery in children. The author selected ...

  3. Pattern recognition techniques for horizontal and vertically upward multiphase flow measurement

    Science.gov (United States)

    Arubi, Tesi I. M.; Yeung, Hoi

    2012-03-01

    The oil and gas industry need for high performing and low cost multiphase meters is ever more justified given the rapid depletion of conventional oil reserves that has led oil companies to develop smaller and marginal fields and reservoirs in remote locations and deep offshore, thereby placing great demands for compact and more cost effective solutions of on-line continuous multiphase flow measurement for well testing, production monitoring, production optimisation, process control and automation. The pattern recognition approach for clamp-on multiphase measurement employed in this study provides one means for meeting this need. High speed caesium-137 radioisotope-based densitometers were installed vertically at the top of a 50.8mm and 101.6mm riser as well as horizontally at the riser base in the Cranfield University multiphase flow test facility. A comprehensive experimental campaign comprising flow conditions typical of operating conditions found in the Petroleum Industry was conducted. The application of a single gamma densitometer unit, in conjunction with pattern recognition techniques to determine both the phase volume fractions and velocities to yield the individual phase flow rates of horizontal and vertically upward multiphase flows was investigated. The pattern recognition systems were trained to map the temporal fluctuations in the multiphase mixture density with the individual phase flow rates using statistical features extracted from the gamma counts signals as their inputs. Initial results yielded individual phase flow rate predictions to within ±5% relative error for the two phase airwater flows and ±10% for three phase air-oil-water flows data.

  4. Soluble Collectin-12 (CL-12) Is a Pattern Recognition Molecule Initiating Complement Activation via the Alternative Pathway

    DEFF Research Database (Denmark)

    Ma, Ying Jie; Hein, Estrid; Munthe-Fog, Lea

    2015-01-01

    and may recognize certain bacteria and fungi, leading to opsonophagocytosis. However, based on its structural and functional similarities with soluble collectins, we hypothesized the existence of a fluid-phase analog of CL-12 released from cells, which may function as a soluble pattern-recognition...... of the terminal complement complex. These results demonstrate the existence of CL-12 in a soluble form and indicate a novel mechanism by which the alternative pathway of complement may be triggered directly by a soluble pattern-recognition molecule....... nonreducing conditions it presented multimeric assembly forms. Immunoprecipitation and Western blot analysis of human umbilical cord plasma enabled identification of a natural soluble form of CL-12 having an electrophoretic mobility pattern close to that of shed soluble recombinant CL-12. Soluble CL-12 could...

  5. The death of marriage? The effects of new forms of legal recognition on marriage rates in the United States.

    Science.gov (United States)

    Dillender, Marcus

    2014-04-01

    Some conservative groups argue that allowing same-sex couples to marry reduces the value of marriage to opposite-sex couples. This article examines how changes in U.S. legal recognition laws occurring between 1995 and 2010 designed to include same-sex couples have altered marriage rates in the United States. Using a difference-in-differences strategy that compares how marriage rates change after legal recognition in U.S. states that alter legal recognition versus states that do not, I find no evidence that allowing same-sex couples to marry reduces the opposite-sex marriage rate. Although the opposite-sex marriage rate is unaffected by same-sex couples marrying, it decreases when domestic partnerships are available to opposite-sex couples.

  6. State of the art: alumina ceramics for energy applications

    International Nuclear Information System (INIS)

    Hauth, W.E.; Stoddard, S.D.

    1978-01-01

    Prominent ceramic raw materials and products manufacturers were surveyed to determine the state of the art for alumina ceramic fabrication. This survey emphasized current capabilities and limitations for fabrication of large, high-density, high-purity, complex shapes. Some directions are suggested for future needs and development

  7. Nuclear power plant decommissioning: state-of-the-art review

    International Nuclear Information System (INIS)

    Williams, D.H.

    1984-01-01

    A brief orientation to the state-of-the-art of nuclear power plant decommissioning discusses the related areas of experience, tools and techniques, and planning. There have been 68 nuclear reactor decommissionings to date, including 9 power plants, some of which were mothballed. The picture suggests that the term art may be misapplied since decommissioning is now more of a mature commercial industrial than a research and development endeavor. It also suggests that the nuclear industry has shown foresight by preparing for it before a crisis situation developed. Some of this has already influenced operators of coal power plants, especially where hazardous materials may be involved. 33 references, 1 table

  8. Pattern recognition methodologies and deterministic evaluation of seismic hazard: A strategy to increase earthquake preparedness

    International Nuclear Information System (INIS)

    Peresan, Antonella; Panza, Giuliano F.; Gorshkov, Alexander I.; Aoudia, Abdelkrim

    2001-05-01

    Several algorithms, structured according to a general pattern-recognition scheme, have been developed for the space-time identification of strong events. Currently, two of such algorithms are applied to the Italian territory, one for the recognition of earthquake-prone areas and the other, namely CN algorithm, for earthquake prediction purposes. These procedures can be viewed as independent experts, hence they can be combined to better constrain the alerted seismogenic area. We examine here the possibility to integrate CN intermediate-term medium-range earthquake predictions, pattern recognition of earthquake-prone areas and deterministic hazard maps, in order to associate CN Times of Increased Probability (TIPs) to a set of appropriate scenarios of ground motion. The advantage of this procedure mainly consists in the time information provided by predictions, useful to increase preparedness of safety measures and to indicate a priority for detailed seismic risk studies to be performed at a local scale. (author)

  9. Harvesting Robots for High-value Crops: State-of-the-art Review and Challenges Ahead

    NARCIS (Netherlands)

    Bac, C.W.; Henten, van E.; Hemming, J.; Edan, Y.

    2014-01-01

    This review article analyzes state-of-the-art and future perspectives for harvesting robots in high-value crops. The objectives were to characterize the crop environment relevant for robotic harvesting, to perform a literature review on the state-of-the-art of harvesting robots using quantitative

  10. Linear Programming and Its Application to Pattern Recognition Problems

    Science.gov (United States)

    Omalley, M. J.

    1973-01-01

    Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.

  11. Recognition of building group patterns in topographic maps based on graph partitioning and random forest

    Science.gov (United States)

    He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

    2018-02-01

    Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

  12. Binary pattern flavored feature extractors for Facial Expression Recognition: An overview

    DEFF Research Database (Denmark)

    Kristensen, Rasmus Lyngby; Tan, Zheng-Hua; Ma, Zhanyu

    2015-01-01

    This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression Recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER...

  13. Study on Analysis and Pattern Recognition of the Manifestation of the Pulse Detection of Cerebrovascular Disease

    Energy Technology Data Exchange (ETDEWEB)

    Jing, J; Wang, Y C; Hong, W X; Zhang, W P [Department of Biomedical Engineering, University of Yanshan, Qinhuangdao, Hebei Province, 066004 (China)

    2006-10-15

    Cerebrovascular Disease (CVD) is also called stroke in Traditional Chinese Medicine (TCM). CVD is a kind of frequent diseases with high incidence, high death rate, high deformity rate and high relapse rate. The pathogenesis of CVD has relation to many factors. In modern medicine, we can make use of various instruments to check many biochemical parameters. However, at present, the early detection of CVD can mostly be done artificially by specialists. In TCM the salted expert can detect the state of a CVD patient by felling his (or her) pulse. It is significant to apply the modern information and engineering techniques to the early discovery of CVD. It is also a challenge to do this in fact. In this paper, the authors presented a detection method of CVD basing on analysis and pattern recognition of Manifestation of the Pulse of TCM using wavelet technology and Neural Networks. Pulse signals from normal health persons and CVD patients were studied comparatively. This research method is flexible to deal with other physiological signals.

  14. Quantifying Landscape Spatial Pattern: What Is the State of the Art?

    Science.gov (United States)

    Eric J. Gustafson

    1998-01-01

    Landscape ecology is based on the premise that there are strong links between ecological pattern and ecological function and process. Ecological systems are spatially heterogeneous, exhibiting consid-erable complexity and variability in time and space. This variability is typically represented by categorical maps or by a collection of samples taken at specific spatial...

  15. Knowledge fusion: An approach to time series model selection followed by pattern recognition

    International Nuclear Information System (INIS)

    Bleasdale, S.A.; Burr, T.L.; Scovel, J.C.; Strittmatter, R.B.

    1996-03-01

    This report describes work done during FY 95 that was sponsored by the Department of Energy, Office of Nonproliferation and National Security, Knowledge Fusion Project. The project team selected satellite sensor data to use as the one main example for the application of its analysis algorithms. The specific sensor-fusion problem has many generic features, which make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series that define a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. An accompanying report (Ref 1) describes the implementation and application of this 2-step process for separating events from unusual background and applies a suite of forecasting methods followed by a suite of pattern recognition methods. This report goes into more detail about one of the forecasting methods and one of the pattern recognition methods and is applied to the same kind of satellite-sensor data that is described in Ref. 1

  16. The state of the art in static and dynamic games

    NARCIS (Netherlands)

    De Giovanni, P.

    2009-01-01

    Purpose - The purpose of this paper is to investigate the state of the art in static and dynamic games (or inter-firm relationships). This research area has changed significantly over the last 25 years through the development of phenomena such as the supply chain and the progressive overcoming of

  17. The Beijing Olympics and the art of nation-state maintenance

    NARCIS (Netherlands)

    de Kloet, J.; Pak Lei Chong, G.; Liu, W.

    2008-01-01

    This article maps out how different actors are involved in the promotion and mediation of the Olympics. It looks at the roles of, first, the nation-state, through an analysis of the promotional materials; second, the art world and global companies, through an analysis of the touring exhibition

  18. A pattern recognition approach to transistor array parameter variance

    Science.gov (United States)

    da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.

    2018-06-01

    The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.

  19. A Snapshot of State Policies for Arts Education

    Science.gov (United States)

    Arts Education Partnership, 2014

    2014-01-01

    It has been said that while history shapes the hand a state is dealt, public policy determines how the hand is played. State policy for K-12 education--and, by extension, for arts education--is shaped through the actions of various state governmental entities--governors, legislatures, courts, and commissioners and boards of education--in response…

  20. Sensors and Technologies in Spain: State-of-the-Art

    Directory of Open Access Journals (Sweden)

    Gonzalo Pajares

    2014-08-01

    Full Text Available The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

  1. Segmentation of turbo generator and reactor coolant pump vibratory patterns: a syntactic pattern recognition approach

    International Nuclear Information System (INIS)

    Tira, Z.

    1993-02-01

    This study was undertaken in the context of turbogenerator and reactor coolant pump vibration surveillance. Vibration meters are used to monitor equipment condition. An anomaly will modify the signal mean. At the present time, the expert system DIVA, developed to automate diagnosis, requests the operator to identify the nature of the pattern change thus indicated. In order to minimize operator intervention, we have to automate on the one hand classification and on the other hand, detection and segmentation of the patterns. The purpose of this study is to develop a new automatic system for the segmentation and classification of signals. The segmentation is based on syntactic pattern recognition. For the classification, a decision tree is used. The signals to process are the rms values of the vibrations measured on rotating machines. These signals are randomly sampled. All processing is automatic and no a priori statistical knowledge on the signals is required. The segmentation performances are assessed by tests on vibratory signals. (author). 31 figs

  2. The Art of Observation: Understanding Pattern Languages

    Directory of Open Access Journals (Sweden)

    Werner Ulrich

    2006-01-01

    Full Text Available [First paragraph] Christopher Alexander's book, The Timeless Way of Building, is probably the most beautiful book on the notion of quality in observation and design that I have been reading since Robert Pirsig's (1974 Zen and the Art of Motorcycle Maintenance. It was published in 1979, when Alexander was a professor of architecture at the University of California, Berkeley, where I was at that time studying. Although I was aware of some of Alexander's famous articles such as "A city is not a tree" (Alexander, 1965, the book (Alexander, 1979 never quite made it to the top of my reading list. This remained so until recently, when I met a software developer who enthusiastically talked to me on a book he was currently reading, about the importance of understanding design patterns. He was talking about the very book I had failed to read during my Berkeley years and which, as I now discovered, has since become a cult book among computer programmers and information scientists, as well as in other fields of research. I decided it was time to read the book.

  3. Local Feature Learning for Face Recognition under Varying Poses

    DEFF Research Database (Denmark)

    Duan, Xiaodong; Tan, Zheng-Hua

    2015-01-01

    In this paper, we present a local feature learning method for face recognition to deal with varying poses. As opposed to the commonly used approaches of recovering frontal face images from profile views, the proposed method extracts the subject related part from a local feature by removing the pose...... related part in it on the basis of a pose feature. The method has a closed-form solution, hence being time efficient. For performance evaluation, cross pose face recognition experiments are conducted on two public face recognition databases FERET and FEI. The proposed method shows a significant...... recognition improvement under varying poses over general local feature approaches and outperforms or is comparable with related state-of-the-art pose invariant face recognition approaches. Copyright ©2015 by IEEE....

  4. 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.

  5. State of the art Advanced Driver Assistance Systems (ADAS).

    NARCIS (Netherlands)

    OEI, H.-L.

    2017-01-01

    An overview of state-of-the-art ADA Advanced Driver Assistance systems is given. First a main structuring system for the ADA systems is presented, needed for purposes of relevancy, and consistency : the three phases in the accident process, i.e. pre-crash, crash and post-crash; the driving task at

  6. Analyst workbenches state of the art report

    CERN Document Server

    Rock-Evans, R

    1987-01-01

    Analyst Workbenches examines various aspects of analyst workbenches and the tasks and data that they should support. The major advances and state of the art in analyst workbenches are discussed. A comprehensive list of the available analyst workbenches, both the experimental and the commercial products, is provided. Comprised of three parts, this book begins by describing International Computers Ltd's approach to automating analysis and design. It then explains what business analysis really means, outlines the principal features of analyst workbenches, and considers the ways in which they can

  7. Text Generation: The State of the Art and the Literature.

    Science.gov (United States)

    Mann, William C.; And Others

    This report comprises two documents which describe the state of the art of computer generation of natural language text. Both were prepared by a panel of individuals who are active in research on text generation. The first document assesses the techniques now available for use in systems design, covering all of the technical methods by which…

  8. Teacher Evaluation in the Arts Disciplines: Three State Perspectives

    Science.gov (United States)

    Gates, Karol; Hansen, Deb; Tuttle, Lynn

    2015-01-01

    The purpose of this report is to provide insight into how state departments are implementing legislative requirements for educator evaluation, particularly the specific circumstances states encounter around arts education. Spotlights on Delaware, a first-round recipient of Race to the Top funding, and Colorado and Arizona, third-round recipients,…

  9. CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

    Science.gov (United States)

    Gong, Qian; Qu, Zhiyi; Hao, Kun

    2017-07-01

    Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

  10. 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.

  11. Complement activating soluble pattern recognition molecules with collagen-like regions, mannan-binding lectin, ficolins and associated proteins

    DEFF Research Database (Denmark)

    Thiel, Steffen

    2007-01-01

    Mannan-binding lectin (MBL), L-ficolin, M-ficolin and H-ficolin are all complement activating soluble pattern recognition molecules with recognition domains linked to collagen-like regions. All four may form complexes with four structurally related proteins, the three MBL-associated serine...... proteases (MASPs), MASP-1, MASP-2 and MASP-3, and a smaller MBL-associated protein (MAp19). The four recognition molecules recognize patterns of carbohydrate or acetyl-group containing ligands. After binding to the relevant targets all four are able to activate the complement system. We thus have a system...... where four different and/or overlapping patterns of microbial origin or patterns of altered-self may be recognized, but in all cases the signalling molecules, the MASPs, are shared. MASP-1 and MASP-3 are formed from one gene, MASP1/3, by alternative splicing generating two different mRNAs from a single...

  12. Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition

    NARCIS (Netherlands)

    Leon Rincon, Carlos; Moreno, José Fernando; Cely, Jorge

    2017-01-01

    The balance sheet is a snapshot that portraits the financial position of a firm at a specific point of time. Under the reasonable assumption that the financial position of a firm is unique and representative, we use a basic artificial neural network pattern recognition method on Colombian banks’

  13. Kazakh Traditional Dance Gesture Recognition

    Science.gov (United States)

    Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

    2014-04-01

    Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

  14. PARA'04, State-of-the-art in scientific computing

    DEFF Research Database (Denmark)

    Madsen, Kaj; Wasniewski, Jerzy

    This meeting in the series, the PARA'04 Workshop with the title ``State of the Art in Scientific Computing'', was held in Lyngby, Denmark, June 20-23, 2004. The PARA'04 Workshop was organized by Jack Dongarra from the University of Tennessee and Oak Ridge National Laboratory, and Kaj Madsen and J...

  15. 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

  16. The Brazilian state-of-the-art of hydrolysis; Estado da arte da hidrolise no Brasil

    Energy Technology Data Exchange (ETDEWEB)

    Carioca, Jose Osvaldo Beserra; Paula, Haroldo Cesar Beserra de; Lal Arora, Harbans; Selvam, P.V. Pannir [Nucleo de Fontes Nao-Convencionais de Energia, Fortaleza, CE, (Brazil)

    1988-12-31

    This paper presents a study of the state-of-the-art of technologies developed for acid and enzymatic hydrolysis of lignin and cellulose materials in Brazil. The information collected leads us to conclude that Brazil has achieved a high level of technological development. However, the industrial projects for production of alcohol from cassava have not proved successful due mainly to lack of agricultural experience and its low productivity. (author) 26 refs., 13 figs., 2 tabs.

  17. State of the art of solid state dosimetry; Estado da arte em dosimetria do estado solido

    Energy Technology Data Exchange (ETDEWEB)

    Souza, Susana O., E-mail: sosouza@ufs.br [Universidade Federal de Sergipe (UFS), Sao Cristovao, SE (Brazil); Yamamoto, Takayoshi [Radioisotope Research Center, Osaka University (Japan); D' Errico, Francesco, E-mail: francesco.derrico@yale.edu [Yale University, School of Medicine, CT (United States)

    2014-07-01

    Passive solid-state detectors still dominate the personal dosimetry field. This article provides state of the art in this field and summarizes the most recent works presented on TL, OSL and RPL during the 17th International Conference on Solid State Dosimetry held in Recife in September 2013. The Article contains in particular the techniques Thermoluminescence (TL), Optically Stimulated Luminescence (OSL), radio photoluminescence (RPL). Thermoluminescence has the biggest advantage of the wide availability of commercial materials for dosimetry, and the nature tissue-equivalent of several of these materials. The limitation of the TL dosimetry presents fading luminance signal and the need for high temperatures to obtain the signal. The Optically Stimulated Luminescence has the advantages of high sensitivity, the possibility of multiple reading, while its limit is the need to use response compensating filters in addition to the high cost of equipment and dosimeters still restricted very few options trading . The radio photoluminescence has a reading that is completely non-destructive, but their dosimeters present lack of tissue-equivalent and a high cost. Presents the details of the techniques and the advantages and limitations of each of these will be discussed.

  18. Speech pattern recognition for forensic acoustic purposes

    OpenAIRE

    Herrera Martínez, Marcelo; Aldana Blanco, Andrea Lorena; Guzmán Palacios, Ana María

    2014-01-01

    The present paper describes the development of a software for analysis of acoustic voice parameters (APAVOIX), which can be used for forensic acoustic purposes, based on the speaker recognition and identification. This software enables to observe in a clear manner, the parameters which are sufficient and necessary when performing a comparison between two voice signals, the suspicious and the original one. These parameters are used according to the classic method, generally used by state entit...

  19. 20 CFR 408.1220 - How do we pay Federally administered State recognition payments?

    Science.gov (United States)

    2010-04-01

    ... recognition payments? 408.1220 Section 408.1220 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SPECIAL BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1220 How do we pay Federally administered State recognition payments? (a) Payment procedures. We make...

  20. ALBEDO PATTERN RECOGNITION AND TIME-SERIES ANALYSES IN MALAYSIA

    Directory of Open Access Journals (Sweden)

    S. A. Salleh

    2012-07-01

    Full Text Available Pattern recognition and time-series analyses will enable one to evaluate and generate predictions of specific phenomena. The albedo pattern and time-series analyses are very much useful especially in relation to climate condition monitoring. This study is conducted to seek for Malaysia albedo pattern changes. The pattern recognition and changes will be useful for variety of environmental and climate monitoring researches such as carbon budgeting and aerosol mapping. The 10 years (2000–2009 MODIS satellite images were used for the analyses and interpretation. These images were being processed using ERDAS Imagine remote sensing software, ArcGIS 9.3, the 6S code for atmospherical calibration and several MODIS tools (MRT, HDF2GIS, Albedo tools. There are several methods for time-series analyses were explored, this paper demonstrates trends and seasonal time-series analyses using converted HDF format MODIS MCD43A3 albedo land product. The results revealed significance changes of albedo percentages over the past 10 years and the pattern with regards to Malaysia's nebulosity index (NI and aerosol optical depth (AOD. There is noticeable trend can be identified with regards to its maximum and minimum value of the albedo. The rise and fall of the line graph show a similar trend with regards to its daily observation. The different can be identified in term of the value or percentage of rises and falls of albedo. Thus, it can be concludes that the temporal behavior of land surface albedo in Malaysia have a uniform behaviours and effects with regards to the local monsoons. However, although the average albedo shows linear trend with nebulosity index, the pattern changes of albedo with respects to the nebulosity index indicates that there are external factors that implicates the albedo values, as the sky conditions and its diffusion plotted does not have uniform trend over the years, especially when the trend of 5 years interval is examined, 2000 shows high

  1. Molecular recognition of AT-DNA sequences by the induced CD pattern of dibenzotetraaza[14]annulene (DBTAA)–adenine derivatives

    Science.gov (United States)

    Stojković, Marijana Radić; Škugor, Marko; Dudek, Łukasz; Grolik, Jarosław; Eilmes, Julita

    2014-01-01

    Summary An investigation of the interactions of two novel and several known DBTAA–adenine conjugates with double-stranded DNA and RNA has revealed the DNA/RNA groove as the dominant binding site, which is in contrast to the majority of previously studied DBTAA analogues (DNA/RNA intercalators). Only DBTAA–propyladenine conjugates revealed the molecular recognition of AT-DNA by an ICD band pattern > 300 nm, whereas significant ICD bands did not appear for other ds-DNA/RNA. A structure–activity relation for the studied series of compounds showed that the essential structural features for the ICD recognition are a) the presence of DNA-binding appendages (adenine side chain and positively charged side chain) on both DBTAA side chains, and b) the presence of a short propyl linker, which does not support intramolecular aromatic stacking between DBTAA and adenine. The observed AT-DNA-ICD pattern differs from previously reported ss-DNA (poly dT) ICD recognition by a strong negative ICD band at 350 nm, which allows for the dynamic differentiation between ss-DNA (poly dT) and coupled ds-AT-DNA. PMID:25246976

  2. Frame-Based Facial Expression Recognition Using Geometrical Features

    Directory of Open Access Journals (Sweden)

    Anwar Saeed

    2014-01-01

    Full Text Available To improve the human-computer interaction (HCI to be as good as human-human interaction, building an efficient approach for human emotion recognition is required. These emotions could be fused from several modalities such as facial expression, hand gesture, acoustic data, and biophysiological data. In this paper, we address the frame-based perception of the universal human facial expressions (happiness, surprise, anger, disgust, fear, and sadness, with the help of several geometrical features. Unlike many other geometry-based approaches, the frame-based method does not rely on prior knowledge of a person-specific neutral expression; this knowledge is gained through human intervention and not available in real scenarios. Additionally, we provide a method to investigate the performance of the geometry-based approaches under various facial point localization errors. From an evaluation on two public benchmark datasets, we have found that using eight facial points, we can achieve the state-of-the-art recognition rate. However, this state-of-the-art geometry-based approach exploits features derived from 68 facial points and requires prior knowledge of the person-specific neutral expression. The expression recognition rate using geometrical features is adversely affected by the errors in the facial point localization, especially for the expressions with subtle facial deformations.

  3. Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

    Science.gov (United States)

    Nasertdinova, A. D.; Bochkarev, V. V.

    2017-11-01

    Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

  4. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-03-01

    Full Text Available Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT, speed-up robust feature (SURF, local binary patterns (LBP, histogram of oriented gradients (HOG, and weighted HOG. Recently, the convolutional neural network (CNN method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  5. HPLC fingerprint analysis combined with chemometrics for pattern recognition of ginger.

    Science.gov (United States)

    Feng, Xu; Kong, Weijun; Wei, Jianhe; Ou-Yang, Zhen; Yang, Meihua

    2014-03-01

    Ginger, the fresh rhizome of Zingiber officinale Rosc. (Zingiberaceae), has been used worldwide; however, for a long time, there has been no standard approbated internationally for its quality control. To establish an efficacious and combinational method and pattern recognition technique for quality control of ginger. A simple, accurate and reliable method based on high-performance liquid chromatography with photodiode array (HPLC-PDA) detection was developed for establishing the chemical fingerprints of 10 batches of ginger from different markets in China. The method was validated in terms of precision, reproducibility and stability; and the relative standard deviations were all less than 1.57%. On the basis of this method, the fingerprints of 10 batches of ginger samples were obtained, which showed 16 common peaks. Coupled with similarity evaluation software, the similarities between each fingerprint of the sample and the simulative mean chromatogram were in the range of 0.998-1.000. Then, the chemometric techniques, including similarity analysis, hierarchical clustering analysis and principal component analysis were applied to classify the ginger samples. Consistent results were obtained to show that ginger samples could be successfully classified into two groups. This study revealed that HPLC-PDA method was simple, sensitive and reliable for fingerprint analysis, and moreover, for pattern recognition and quality control of ginger.

  6. Application of PSO for solving problems of pattern recognition

    Directory of Open Access Journals (Sweden)

    S. N. Chukanov

    2016-01-01

    Full Text Available The problem of estimating the norm of the distance between the two closed smooth curves for pattern recognition is considered. Diffeomorphic transformation curves based on the model of large deformation with the transformation of the starting points of domain in required is formed on the basis of which depends on time-dependent vector field of velocity is considered. The action of the translation, rotation and scaling closed curve, the invariants of the action of these groups are considered. The position of curves is normalized by centering, bringing the principal axes of the image to the axes of the coordinate system and bringing the area of a closed curve corresponding to one. For estimating of the norm of the distance between two closed curves is formed the functional corresponding normalized distance between the two curves, and the equation of evolution diffeomorphic transformations. The equation of evolution allows to move objects along trajectories which correspond to diffeomorphic transformations. The diffeomorphisms do not change the topology along the geodesic trajectories. The problem of inexact comparing the minimized functional contains a term that estimates the exactness of shooting points in the required positions. In the equation of evolution is introduced the variance of conversion error. An algorithm for solving the equation of diffeomorphic transformation is proposed, built on the basis of PSO, which can significantly reduce the number of computing operations, compared with gradient methods for solving. The developed algorithms can be used in bioinformatics and biometrics systems, classification of images and objects, machine vision systems, neuroimaging, for pattern recognition and object tracking systems. Algorithm for estimating the norm of distance between the closed curves by diffeomorphic transformation can spread to spatial objects (curves, surfaces, manifolds.

  7. Supplier selection problem: A state-of-the-art review

    Directory of Open Access Journals (Sweden)

    Nilesh R. Ware

    2012-08-01

    Full Text Available In the global competitiveness and growing market environment, “Actual competition is not between firms against firm, than supplier against supplier”. Globally in the fastest market development world gets closer and closer. Consumers prefer fast delivery, economical product, excellent service and high quality product with desired service level. For successful management of this supply chain, supplier considered as the base source for all processes. Therefore, an efficient supplier selection and evaluation process needs to be incorporate. The main purpose of this paper is to provide an extensive state-of-the-art literature review and critique of the studies related to various aspects of supplier selection problem over the past two decades. Research papers appearing in the reputed and leading international journals from 1991 to 2011 are gathered and analyzed. Primary focus is given on more than 200 published and unpublished works. It has been referred extensively to carry out state-of-the-art review for supplier selection problem. Finally, paper provides future perspective based on current research trends available in the published literature.

  8. [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.

  9. AN OPTICAL CHARACTER RECOGNITION RESEARCH AND DEMONSTRATION PROJECT.

    Science.gov (United States)

    1968

    RESEARCH AND DEVELOPMENT OF PROTOTYPE LIBRARY SYSTEMS WHICH UTILIZE OPTICAL CHARACTER RECOGNITION INPUT HAS CENTERED AROUND OPTICAL PAGE READERS AND DOCUMENT READERS. THE STATE-OF-THE-ART OF BOTH THESE OPTICAL SCANNERS IS SUCH THAT BOTH ARE ACCEPTABLE FOR LIBRARY INPUT PREPARATION. A DEMONSTRATION PROJECT UTILIZING THE TWO TYPES OF READERS, SINCE…

  10. The Complete Gabor-Fisher Classifier for Robust Face Recognition

    Directory of Open Access Journals (Sweden)

    Štruc Vitomir

    2010-01-01

    Full Text Available Abstract This paper develops a novel face recognition technique called Complete Gabor Fisher Classifier (CGFC. Different from existing techniques that use Gabor filters for deriving the Gabor face representation, the proposed approach does not rely solely on Gabor magnitude information but effectively uses features computed based on Gabor phase information as well. It represents one of the few successful attempts found in the literature of combining Gabor magnitude and phase information for robust face recognition. The novelty of the proposed CGFC technique comes from (1 the introduction of a Gabor phase-based face representation and (2 the combination of the recognition technique using the proposed representation with classical Gabor magnitude-based methods into a unified framework. The proposed face recognition framework is assessed in a series of face verification and identification experiments performed on the XM2VTS, Extended YaleB, FERET, and AR databases. The results of the assessment suggest that the proposed technique clearly outperforms state-of-the-art face recognition techniques from the literature and that its performance is almost unaffected by the presence of partial occlusions of the facial area, changes in facial expression, or severe illumination changes.

  11. 20 CFR 408.1215 - How do you establish eligibility for Federally administered State recognition payments?

    Science.gov (United States)

    2010-04-01

    ... Federally administered State recognition payments? 408.1215 Section 408.1215 Employees' Benefits SOCIAL... Recognition Payments § 408.1215 How do you establish eligibility for Federally administered State recognition... deemed to have filed an application for any Federally administered State recognition payments for which...

  12. Some Aspects of the State-of-the-Arts in Biomedical Science ...

    African Journals Online (AJOL)

    Summary: In the biomedical sciences, there is need to generate solutions for Africa's health and economic problems through the impact of university research. To guide organizational transformation, the author here presents some aspects of the state-of-the-arts of biomedical science research in advanced countries using a ...

  13. Deep Learning based Super-Resolution for Improved Action Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman

    2015-01-01

    with results of a state-of- the-art deep learning-based super-resolution algorithm, through an alpha-blending approach. The experimental results obtained on down-sampled version of a large subset of Hoolywood2 benchmark database show the importance of the proposed system in increasing the recognition rate...

  14. Three dimensional pattern recognition using feature-based indexing and rule-based search

    Science.gov (United States)

    Lee, Jae-Kyu

    In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

  15. State-of-the-Art in Open Courseware Initiatives Worldwide

    Science.gov (United States)

    Vladoiu, Monica

    2011-01-01

    We survey here the state-of-the-art in open courseware initiatives worldwide. First, the MIT OpenCourseWare project is overviewed, as it has been the real starting point of the OCW movement. Usually, open courseware refers to a free and open digital publication of high quality university level educational materials that are organized as courses,…

  16. CMOS image sensors: State-of-the-art

    Science.gov (United States)

    Theuwissen, Albert J. P.

    2008-09-01

    This paper gives an overview of the state-of-the-art of CMOS image sensors. The main focus is put on the shrinkage of the pixels : what is the effect on the performance characteristics of the imagers and on the various physical parameters of the camera ? How is the CMOS pixel architecture optimized to cope with the negative performance effects of the ever-shrinking pixel size ? On the other hand, the smaller dimensions in CMOS technology allow further integration on column level and even on pixel level. This will make CMOS imagers even smarter that they are already.

  17. Multi-Lingual Deep Neural Networks for Language Recognition

    Science.gov (United States)

    2016-08-08

    system architecture 2. I-VECTOR SYSTEM Most state-of-the- art language recognition systems are based on the i-vector framework [8] depicted in Figure 1...may be possible to achieve more gains on the Arabic and Chinese cluster by adding ad- ditional ASR corpora such as Callhome Egyptian Arabic or HKUST

  18. 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.

  19. Optical pattern recognition III; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

    Science.gov (United States)

    Casasent, David P. (Editor); Chao, Tien-Hsin (Editor)

    1992-01-01

    Consideration is given to transitioning of optical processing into systems (TOPS), optical correlator hardware, phase-only optical correlation filters, optical distortion-invariant correlation filters, and optical neural networks. Particular attention is given to a test target for optical correlators, a TOPS electronic warfare channelizer program, a portable video-rate optical correlator, a joint transform correlator employing electron trapping materials, a novelty filtered optical correlator using a photorefractive crystal, a comparison of correlation performance of smart ternary phase-amplitude filters with gray-scale and binary input scenes, real-time distortion-tolerant composite filters for automatic target identification, landscaping the correlation surface, fast designing of a circular harmonic filter using simulated annealing, feature-based correlation filters for distortion invariance, automatic target recognition using a feature-based optical neural network, and a holographic inner-product processor for pattern recognition.

  20. State of the art: two-phase flow calibration techniques

    International Nuclear Information System (INIS)

    Stanley, M.L.

    1977-01-01

    The nuclear community faces a particularly difficult problem relating to the calibration of instrumentation in a two-phase flow steam/water environment. The rationale of the approach to water reactor safety questions in the United States demands that accurate measurements of mass flows in a decompressing two-phase flow be made. An accurate measurement dictates an accurate calibration. This paper addresses three questions relating to the state of the art in two-phase calibration: (1) What do we mean by calibration. (2) What is done now. (3) What should be done

  1. State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

    Directory of Open Access Journals (Sweden)

    Moritz Koplin

    2013-04-01

    Full Text Available Most state-of-the-art driver assistance systems cannot guarantee that real-time images of object states are updated within a given time interval, because the object state observations are typically sampled by uncontrolled sensors and transmitted via an indeterministic bus system such as CAN. To overcome this shortcoming, a paradigm shift toward time-triggered advanced driver assistance systems based on a deterministic bus system, such as FlexRay, is under discussion. In order to prove the feasibility of this paradigm shift, this paper develops different models of a state-of-the-art and a time-triggered advanced driver assistance system based on multi-sensor object tracking and compares them with regard to their mean performance. The results show that while the state-of-the-art model is advantageous in scenarios with low process noise, it is outmatched by the time-triggered model in the case of high process noise, i.e., in complex situations with high dynamic.

  2. Pattern recognition for cache management in distributed medical imaging environments.

    Science.gov (United States)

    Viana-Ferreira, Carlos; Ribeiro, Luís; Matos, Sérgio; Costa, Carlos

    2016-02-01

    Traditionally, medical imaging repositories have been supported by indoor infrastructures with huge operational costs. This paradigm is changing thanks to cloud outsourcing which not only brings technological advantages but also facilitates inter-institutional workflows. However, communication latency is one main problem in this kind of approaches, since we are dealing with tremendous volumes of data. To minimize the impact of this issue, cache and prefetching are commonly used. The effectiveness of these mechanisms is highly dependent on their capability of accurately selecting the objects that will be needed soon. This paper describes a pattern recognition system based on artificial neural networks with incremental learning to evaluate, from a set of usage pattern, which one fits the user behavior at a given time. The accuracy of the pattern recognition model in distinct training conditions was also evaluated. The solution was tested with a real-world dataset and a synthesized dataset, showing that incremental learning is advantageous. Even with very immature initial models, trained with just 1 week of data samples, the overall accuracy was very similar to the value obtained when using 75% of the long-term data for training the models. Preliminary results demonstrate an effective reduction in communication latency when using the proposed solution to feed a prefetching mechanism. The proposed approach is very interesting for cache replacement and prefetching policies due to the good results obtained since the first deployment moments.

  3. State-of-the-art report on the theoretical modeling of interfacial area concentration

    International Nuclear Information System (INIS)

    Lee, Won Jae; Euh, Dong Jin

    1998-03-01

    Classical approaches based on experimental correlations and the mechanistic approaches based on the interfacial area concentration were reviewed. The study focuses on the state-of-the-art researches based on the mechanistic modeling of the interfacial area concentration. The investigation is performed by classifying the mechanistic modeling approaches into those using the number density transport equations supported with a simple algebraic relation for obtaining interfacial area concentration and those using the direct interfacial area transport equations. The modeling approaches are subdivided into one group and multi-group models. The state-of-the-art source terms of transport equations are also investigated for their applicability and limitations. (author). 62 refs., 6 tabs., 49 figs

  4. Neutron-gamma discrimination employing pattern recognition of the signal from liquid scintillator

    CERN Document Server

    Kamada, K; Ogawa, S

    1999-01-01

    A pattern recognition method was applied to the neutron-gamma discrimination of the pulses from the liquid scintillator, NE-213. The circuit for the discrimination is composed of A/D converter, fast SCA, memory control circuit, two digital delay lines and two buffer memories. All components are packed on a small circuit board and are installed into a personal computer. Experiments using a weak sup 2 sup 5 sup 2 Cf n-gamma source were undertaken to test the feasibility of the circuit. The circuit is of very easy adjustment and, at the same time, of very economical price when compared with usual discrimination circuits, such as the TAC system.

  5. Neutron-gamma discrimination employing pattern recognition of the signal from liquid scintillator

    International Nuclear Information System (INIS)

    Kamada, Kohji; Enokido, Uhji; Ogawa, Seiji

    1999-01-01

    A pattern recognition method was applied to the neutron-gamma discrimination of the pulses from the liquid scintillator, NE-213. The circuit for the discrimination is composed of A/D converter, fast SCA, memory control circuit, two digital delay lines and two buffer memories. All components are packed on a small circuit board and are installed into a personal computer. Experiments using a weak 252 Cf n-γ source were undertaken to test the feasibility of the circuit. The circuit is of very easy adjustment and, at the same time, of very economical price when compared with usual discrimination circuits, such as the TAC system

  6. Differentiation of tea varieties using UV-Vis spectra and pattern recognition techniques

    Science.gov (United States)

    Palacios-Morillo, Ana; Alcázar, Ángela.; de Pablos, Fernando; Jurado, José Marcos

    2013-02-01

    Tea, one of the most consumed beverages all over the world, is of great importance in the economies of a number of countries. Several methods have been developed to classify tea varieties or origins based in pattern recognition techniques applied to chemical data, such as metal profile, amino acids, catechins and volatile compounds. Some of these analytical methods become tedious and expensive to be applied in routine works. The use of UV-Vis spectral data as discriminant variables, highly influenced by the chemical composition, can be an alternative to these methods. UV-Vis spectra of methanol-water extracts of tea have been obtained in the interval 250-800 nm. Absorbances have been used as input variables. Principal component analysis was used to reduce the number of variables and several pattern recognition methods, such as linear discriminant analysis, support vector machines and artificial neural networks, have been applied in order to differentiate the most common tea varieties. A successful classification model was built by combining principal component analysis and multilayer perceptron artificial neural networks, allowing the differentiation between tea varieties. This rapid and simple methodology can be applied to solve classification problems in food industry saving economic resources.

  7. Real-Time Control of an Exoskeleton Hand Robot with Myoelectric Pattern Recognition.

    Science.gov (United States)

    Lu, Zhiyuan; Chen, Xiang; Zhang, Xu; Tong, Kay-Yu; Zhou, Ping

    2017-08-01

    Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

  8. Orphan diseases: state of the drug discovery art.

    Science.gov (United States)

    Volmar, Claude-Henry; Wahlestedt, Claes; Brothers, Shaun P

    2017-06-01

    Since 1983 more than 300 drugs have been developed and approved for orphan diseases. However, considering the development of novel diagnosis tools, the number of rare diseases vastly outpaces therapeutic discovery. Academic centers and nonprofit institutes are now at the forefront of rare disease R&D, partnering with pharmaceutical companies when academic researchers discover novel drugs or targets for specific diseases, thus reducing the failure risk and cost for pharmaceutical companies. Considerable progress has occurred in the art of orphan drug discovery, and a symbiotic relationship now exists between pharmaceutical industry, academia, and philanthropists that provides a useful framework for orphan disease therapeutic discovery. Here, the current state-of-the-art of drug discovery for orphan diseases is reviewed. Current technological approaches and challenges for drug discovery are considered, some of which can present somewhat unique challenges and opportunities in orphan diseases, including the potential for personalized medicine, gene therapy, and phenotypic screening.

  9. State of the art on the probabilistic safety assessment (P.S.A.)

    International Nuclear Information System (INIS)

    Devictor, N.; Bassi, A.; Saignes, P.; Bertrand, F.

    2008-01-01

    The use of Probabilistic Safety Assessment (PSA) is internationally increasing as a means of assessing and improving the safety of nuclear and non-nuclear facilities. To support the development of a competence on Probabilistic Safety Assessment, a set of states of the art regarding these tools and their use has been made between 2001 and 2005, in particular on the following topics: - Definition of the PSA of level 1, 2 and 3; - Use of PSA in support to design and operation of nuclear plants (risk-informed applications); - Applications to Non Reactor Nuclear Facilities. The report compiled in a single document these states of the art in order to ensure a broader use; this work has been done in the frame of the Project 'Reliability and Safety of Nuclear Facility' of the Nuclear Development and Innovation Division of the Nuclear Energy Division. As some of these states of the art have been made in support to exchanges with international partners and were written in English, a section of this document is written in English. This work is now applied concretely in support to the design of 4. Generation nuclear systems as Sodium-cooled Fast Reactors and especially Gas-cooled Fast Reactor, that have been the subject of communications during the conferences ANS (Annual Meeting 2007), PSA'08, ICCAP'08 and in the journal Science and Technology of Nuclear Installations. (authors)

  10. Finger crease pattern recognition using Legendre moments and principal component analysis

    Science.gov (United States)

    Luo, Rongfang; Lin, Tusheng

    2007-03-01

    The finger joint lines defined as finger creases and its distribution can identify a person. In this paper, we propose a new finger crease pattern recognition method based on Legendre moments and principal component analysis (PCA). After obtaining the region of interest (ROI) for each finger image in the pre-processing stage, Legendre moments under Radon transform are applied to construct a moment feature matrix from the ROI, which greatly decreases the dimensionality of ROI and can represent principal components of the finger creases quite well. Then, an approach to finger crease pattern recognition is designed based on Karhunen-Loeve (K-L) transform. The method applies PCA to a moment feature matrix rather than the original image matrix to achieve the feature vector. The proposed method has been tested on a database of 824 images from 103 individuals using the nearest neighbor classifier. The accuracy up to 98.584% has been obtained when using 4 samples per class for training. The experimental results demonstrate that our proposed approach is feasible and effective in biometrics.

  11. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  12. Pattern recognition applied to infrared images for early alerts in fog

    Science.gov (United States)

    Boucher, Vincent; Marchetti, Mario; Dumoulin, Jean; Cord, Aurélien

    2014-09-01

    Fog conditions are the cause of severe car accidents in western countries because of the poor induced visibility. Its forecast and intensity are still very difficult to predict by weather services. Infrared cameras allow to detect and to identify objects in fog while visibility is too low for eye detection. Over the past years, the implementation of cost effective infrared cameras on some vehicles has enabled such detection. On the other hand pattern recognition algorithms based on Canny filters and Hough transformation are a common tool applied to images. Based on these facts, a joint research program between IFSTTAR and Cerema has been developed to study the benefit of infrared images obtained in a fog tunnel during its natural dissipation. Pattern recognition algorithms have been applied, specifically on road signs which shape is usually associated to a specific meaning (circular for a speed limit, triangle for an alert, …). It has been shown that road signs were detected early enough in images, with respect to images in the visible spectrum, to trigger useful alerts for Advanced Driver Assistance Systems.

  13. Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

    Science.gov (United States)

    Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

    2017-11-01

    Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

  14. Fault diagnosis and performance monitoring for pumps by means of vibration measurement and pattern recognition

    International Nuclear Information System (INIS)

    Grabner, A.; Weiss, F.P.

    1984-12-01

    In recent years the early detection of malfunctions with noise and vibration analysis techniques has become a more and more important method for increasing availability and safety of various components in technical plants. The possibility of pattern recognition assisted vibration monitoring and its practical realization are demonstrated by failure diagnosis and trend analysis of the condition of large centrifugal pumps in hydraulic circuits. Some problems as, e.g., the finding of dynamic failure models, signal analysis, feature extraction and statistical pattern recognition, which helps automatically to decide whether the pump works normally or not, are discussed in more detail. In the paper it is shown that for various types of machines the chance of success of condition based maintenance can be enhanced by such an automatic vibration monitoring. (author)

  15. Simulation of pollutants transfer in soils - State-of-the-art. State-of-the-art of the simulation of pollutants transfer in soils - Final report

    International Nuclear Information System (INIS)

    Bourgois, J.; Vaillant, Herve; Moszkowicz, P.; Alimi Ichola, Ibrahim; Foret, Suzanne

    1997-02-01

    Industrial companies use and produce numerous substances which can induce a pollution of our environment and especially of soil and groundwater. Thus, it's necessary to estimate the risk of an environmental impact from an accidental or chronic, real or potential pollution. Modelling, which allow the simulation of pollutant migration, can be used as a decision support system, either for the pollution control and prevention of the resource, or for the monitoring of the remediation of polluted sites. In the first part of this study, we established a state of the art on modelling of pollutant migration in soils. In the second part, we focused on the main simulation tools currently available on the market, and on the main agencies or laboratories working on this subject, especially in France. At the end of this study, we drew some conclusions concerning modelling of pollutant migration in soils and the main points which will form the subject of further studies: - sensitivity analysis of model to input parameters and ranking of the main parameters, - achievement of a database on the state of the art of the results on modelling realized on case studies, - development of a mobility indicator of pollutant in soil, - application field and relevance of the models. (authors)

  16. A Review on Video-Based Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Shian-Ru Ke

    2013-06-01

    Full Text Available This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.

  17. Evaluating structural pattern recognition for handwritten math via primitive label graphs

    Science.gov (United States)

    Zanibbi, Richard; Mouchère, Harold; Viard-Gaudin, Christian

    2013-01-01

    Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures (i.e. ground truth) using recognition rates, recall and precision for object segmentation, classification and relationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multiple primitives (e.g. connected components, or strokes for online handwritten data), but current metrics do not characterize errors at the primitive level, from which object-level structure is obtained. Primitive label graphs are directed graphs defined over primitives and primitive pairs. We define new metrics obtained by Hamming distances over label graphs, which allow classification, segmentation and parsing errors to be characterized separately, or using a single measure. Recall and precision for detected objects may also be computed directly from label graphs. We illustrate the new metrics by comparing a new primitive-level evaluation to the symbol-level evaluation performed for the CROHME 2012 handwritten math recognition competition. A Python-based set of utilities for evaluating, visualizing and translating label graphs is publicly available.

  18. Investigation of CoPd alloys by XPS and EPES using the pattern recognition method

    Czech Academy of Sciences Publication Activity Database

    Lesiak, B.; Zemek, Josef; Jiříček, Petr; Jozwik, A.

    2007-01-01

    Roč. 428, - (2007), s. 190-196 ISSN 0925-8388 R&D Projects: GA ČR GA202/06/0459 Institutional research plan: CEZ:AV0Z10100521 Keywords : CoPd alloys * x-ray photoelectron spectroscopy (XPS) * elastic peak electron spectroscopy (EPES) * pattern recognition method * fuzzy k-nearest neighbour rule (fkNN) * quantitative analysis * surface segregation Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.455, year: 2007

  19. Activation and regulation of the pattern recognition receptors in obesity-induced adipose tissue inflammation and insulin resistance.

    Science.gov (United States)

    Watanabe, Yasuharu; Nagai, Yoshinori; Takatsu, Kiyoshi

    2013-09-23

    Obesity-associated chronic tissue inflammation is a key contributing factor to type 2 diabetes mellitus, and a number of studies have clearly demonstrated that the immune system and metabolism are highly integrated. Recent advances in deciphering the various immune cells and signaling networks that link the immune and metabolic systems have contributed to our understanding of the pathogenesis of obesity-associated inflammation. Other recent studies have suggested that pattern recognition receptors in the innate immune system recognize various kinds of endogenous and exogenous ligands, and have a crucial role in initiating or promoting obesity-associated chronic inflammation. Importantly, these mediators act on insulin target cells or on insulin-producing cells impairing insulin sensitivity and its secretion. Here, we discuss how various pattern recognition receptors in the immune system underlie the etiology of obesity-associated inflammation and insulin resistance, with a particular focus on the TLR (Toll-like receptor) family protein Radioprotective 105 (RP105)/myeloid differentiation protein-1 (MD-1).

  20. Activation and Regulation of the Pattern Recognition Receptors in Obesity-Induced Adipose Tissue Inflammation and Insulin Resistance

    Directory of Open Access Journals (Sweden)

    Kiyoshi Takatsu

    2013-09-01

    Full Text Available Obesity-associated chronic tissue inflammation is a key contributing factor to type 2 diabetes mellitus, and a number of studies have clearly demonstrated that the immune system and metabolism are highly integrated. Recent advances in deciphering the various immune cells and signaling networks that link the immune and metabolic systems have contributed to our understanding of the pathogenesis of obesity-associated inflammation. Other recent studies have suggested that pattern recognition receptors in the innate immune system recognize various kinds of endogenous and exogenous ligands, and have a crucial role in initiating or promoting obesity-associated chronic inflammation. Importantly, these mediators act on insulin target cells or on insulin-producing cells impairing insulin sensitivity and its secretion. Here, we discuss how various pattern recognition receptors in the immune system underlie the etiology of obesity-associated inflammation and insulin resistance, with a particular focus on the TLR (Toll-like receptor family protein Radioprotective 105 (RP105/myeloid differentiation protein-1 (MD-1.

  1. Digital astrophotography the state of the art

    CERN Document Server

    Ratledge, David

    2005-01-01

    The CCD (Charge-Coupled Device) has revolutionised optical astronomy during the past 20 years, and specialised astronomical CCD cameras are now even more affordable, colour is standard, and they provide spectacular results. "Digital Astrophotography: The State of the Art", provides some examples of the best images, and gives readers hints and tips about how to get the best out of this extraordinary technology. Experts in CCD astronomy from North America and Europe have contributed to this book, illustrating their help and advice with many beautiful colour images - the book is in full colour throughout. Techniques range from using simple webcams to highly technical aspects such as supernovae patrolling. Computer processing, stacking and image-enhancement are detailed, along with many hints and tips from the experts.

  2. Augmented Reality and Mobile Learning: The State of the Art

    Science.gov (United States)

    FitzGerald, Elizabeth; Ferguson, Rebecca; Adams, Anne; Gaved, Mark; Mor, Yishay; Thomas, Rhodri

    2013-01-01

    In this paper, the authors examine the state of the art in augmented reality (AR) for mobile learning. Previous work in the field of mobile learning has included AR as a component of a wider toolkit but little has been done to discuss the phenomenon in detail or to examine in a balanced fashion its potential for learning, identifying both positive…

  3. Application of Pattern Recognition Techniques to the Classification of Full-Term and Preterm Infant Cry.

    Science.gov (United States)

    Orlandi, Silvia; Reyes Garcia, Carlos Alberto; Bandini, Andrea; Donzelli, Gianpaolo; Manfredi, Claudia

    2016-11-01

    Scientific and clinical advances in perinatology and neonatology have enhanced the chances of survival of preterm and very low weight neonates. Infant cry analysis is a suitable noninvasive complementary tool to assess the neurologic state of infants particularly important in the case of preterm neonates. This article aims at exploiting differences between full-term and preterm infant cry with robust automatic acoustical analysis and data mining techniques. Twenty-two acoustical parameters are estimated in more than 3000 cry units from cry recordings of 28 full-term and 10 preterm newborns. Feature extraction is performed through the BioVoice dedicated software tool, developed at the Biomedical Engineering Lab, University of Firenze, Italy. Classification and pattern recognition is based on genetic algorithms for the selection of the best attributes. Training is performed comparing four classifiers: Logistic Curve, Multilayer Perceptron, Support Vector Machine, and Random Forest and three different testing options: full training set, 10-fold cross-validation, and 66% split. Results show that the best feature set is made up by 10 parameters capable to assess differences between preterm and full-term newborns with about 87% of accuracy. Best results are obtained with the Random Forest method (receiver operating characteristic area, 0.94). These 10 cry features might convey important additional information to assist the clinical specialist in the diagnosis and follow-up of possible delays or disorders in the neurologic development due to premature birth in this extremely vulnerable population of patients. The proposed approach is a first step toward an automatic infant cry recognition system for fast and proper identification of risk in preterm babies. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  4. Pattern recognition in menstrual bleeding diaries by statistical cluster analysis

    Directory of Open Access Journals (Sweden)

    Wessel Jens

    2009-07-01

    Full Text Available Abstract Background The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs. Methods We used the four cluster analysis methods single, average and complete linkage as well as the method of Ward for the pattern recognition in menstrual bleeding diaries. The optimal number of clusters was determined using the semi-partial R2, the cubic cluster criterion, the pseudo-F- and the pseudo-t2-statistic. Finally, the interpretability of the results from a gynecological point of view was assessed. Results The method of Ward yielded distinct clusters of the bleeding diaries. The other methods successively chained the observations into one cluster. The optimal number of distinctive bleeding patterns was six. We found two desirable and four undesirable bleeding patterns. Cyclic and non cyclic bleeding patterns were well separated. Conclusion Using this cluster analysis with the method of Ward medications and devices having an impact on bleeding can be easily compared and categorized.

  5. Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

    Science.gov (United States)

    Schafer, Phillip B; Jin, Dezhe Z

    2014-03-01

    Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

  6. Electron beam melting state-of-the-art 1984

    International Nuclear Information System (INIS)

    Bakish, R.

    1984-01-01

    In 1984 electron beam melting and refining appear poised for an important new growth phase. The driving force for this phase is improved production economics made possible by technological advances. There is also a new and exciting growth application for electron beam melting: its use for surface properties beneficiation. This article is based in part on the content of the Conference on Electron Beam Melting and Refining, The State-of-the-Art 1983, held in November 1983 in Reno, Nevada

  7. Can superconductivity be predicted with the aid of pattern recognition techniques

    International Nuclear Information System (INIS)

    Pijpers, F.W.

    1982-01-01

    Pattern recognition techniques were employed in order to investigate the possibility to find features of the elements of the periodic system that may be relevant for the description of their behaviour with respect to superconductivity. Learning machines were constructed using those elements of the periodic system whose superconducting properties have been well studied. Relevant features appear to be the electronic work function and the number of valence electrons as given by Miedema, the specific heat, the heat of melting, the heat of sublimation, the melting point and the atomic radius. The learning machines have a predicting capability of the order of 90%. The predictive power of these machines concerning the superconducting behaviour of the alkali and alkaline-earth metals belonging to a given test set, however, appears to be less convincing

  8. Digital Breast Tomosynthesis: State of the Art

    Science.gov (United States)

    Vedantham, Srinivasan; Vijayaraghavan, Gopal R.; Kopans, Daniel B.

    2015-01-01

    This topical review on digital breast tomosynthesis (DBT) is provided with the intent of describing the state of the art in terms of technology, results from recent clinical studies, advanced applications, and ongoing efforts to develop multimodality imaging systems that include DBT. Particular emphasis is placed on clinical studies. The observations of increase in cancer detection rates, particularly for invasive cancers, and the reduction in false-positive rates with DBT in prospective trials indicate its benefit for breast cancer screening. Retrospective multireader multicase studies show either noninferiority or superiority of DBT compared with mammography. Methods to curtail radiation dose are of importance. © RSNA, 2015 PMID:26599926

  9. State of the art-hydraulic yaw systems for wind turbines

    DEFF Research Database (Denmark)

    Stubkier, Søren; Pedersen, Henrik C.; Andersen, Torben Ole

    2011-01-01

    This paper addresses the yawing systems of Horizontal Axis Wind Turbines (HAWT’s). HAWT’s represents close to all of the commercial large wind turbines sold today and must be considered state-of-the art within wind turbine technology. Two choices exists when considering components for the active ...

  10. Intracytoplasmic sperm injection: state of the art in humans.

    Science.gov (United States)

    Palermo, G D; O'Neill, C L; Chow, S; Cheung, S; Parrella, A; Pereira, N; Rosenwaks, Z

    2017-12-01

    Among infertile couples, 25% involve both male and female factors, while male factor alone accounts for another 25% due to oligo-, astheno-, teratozoospermia, a combination of the three, or even a complete absence of sperm cells in the ejaculate and can lead to a poor prognosis even with the help of assisted reproductive technology (ART). Intracytoplasmic sperm injection (ICSI) has been with us now for a quarter of a century and in spite of the controversy generated since its inception, it remains in the forefront of the techniques utilized in ART. The development of ICSI in 1992 has drastically decreased the impact of male factor, resulting in millions of pregnancies worldwide for couples who, without ICSI, would have had little chance of having their own biological child. This review focuses on the state of the art of ICSI regarding utility of bioassays that evaluate male factor infertility beyond the standard semen analysis and describes the current application and advances in regard to ICSI, particularly the genetic and epigenetic characteristics of spermatozoa and their impact on reproductive outcome. © 2017 Society for Reproduction and Fertility.

  11. 20 CFR 408.1235 - How does the State transfer funds to SSA to administer its recognition payment program?

    Science.gov (United States)

    2010-04-01

    ... administer its recognition payment program? 408.1235 Section 408.1235 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SPECIAL BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1235 How does the State transfer funds to SSA to administer its recognition payment program...

  12. Pattern recognition trigger electronics for an imaging atmospheric Cherenkov telescope

    International Nuclear Information System (INIS)

    Bradbury, S.M.; Rose, H.J.

    2002-01-01

    For imaging atmospheric Cherenkov telescopes, which aim to detect electromagnetic air showers with cameras consisting of several hundred photomultiplier pixels, the single pixel trigger rate is dominated by fluctuations in night sky brightness and by ion feedback in the photomultipliers. Pattern recognition trigger electronics may be used to reject night sky background images, thus reducing the data rate to a manageable level. The trigger system described here detects patterns of 2, 3 or 4 adjacent pixel signals within a 331 pixel camera and gives a positive trigger decision in 65 ns. The candidate pixel pattern is compared with the contents of a pre-programmed memory. With the trigger decision timing controlled by a fixed delay the time-jitter inherent in the use of programmable gate arrays is avoided. This system is now in routine operation at the Whipple 10 m Telescope

  13. Playing tag with ANN: boosted top identification with pattern recognition

    International Nuclear Information System (INIS)

    Almeida, Leandro G.; Backović, Mihailo; Cliche, Mathieu; Lee, Seung J.; Perelstein, Maxim

    2015-01-01

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image" of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p T in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

  14. Playing tag with ANN: boosted top identification with pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Almeida, Leandro G. [Institut de Biologie de l’École Normale Supérieure (IBENS), Inserm 1024- CNRS 8197,46 rue d’Ulm, 75005 Paris (France); Backović, Mihailo [Center for Cosmology, Particle Physics and Phenomenology - CP3,Universite Catholique de Louvain,Louvain-la-neuve (Belgium); Cliche, Mathieu [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States); Lee, Seung J. [Department of Physics, Korea Advanced Institute of Science and Technology,335 Gwahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); School of Physics, Korea Institute for Advanced Study,Seoul 130-722 (Korea, Republic of); Perelstein, Maxim [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States)

    2015-07-17

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image' of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p{sub T} in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

  15. Setting ART initiation targets in response to changing guidelines: The importance of addressing both steady-state and backlog.

    Science.gov (United States)

    Martin, Catherine; Naidoo, Nicolette P; Venter, W D Francois; Jaffer, Ambereen; Barker, Pierre M

    2014-05-12

    Target setting is useful in planning, assessing and improving antiretroviral treatment (ART) programmes. In the past 4 years, the ART initiation environment has been transformed due to the change in eligibility criteria (starting ART at a CD4+ count ART. To describe and illustrate the use of a target-setting model for estimating district-based targets in the era of an expanding ART programme and changing CD4+ count thresholds for ART initiation. Using previously described models and data for annual new HIV infections, we estimated both steady-state need for ART initiation and backlog in a North West Province district, accounting for the shift in eligibility. Comparison of actual v. targeted ART initiations was undertaken. The change in CD4+ count threshold adds a once-off group of newly eligible patients to the pool requiring ART - the backlog. The steady-state remains unchanged as it is determined by the annual rate of new HIV infections in previous years. The steady-state need for the district was 639 initiations/month, and the backlog was ~15,388 patients. After the shift in eligibility in September 2011, the steady-state target was exceeded over several months with some backlog addressed. Of the total backlog for this district, 72% remains to be cleared. South Africa has two pools of patients who need ART: the steady-state of HIV-infected patients entering the programme each year, determined by historical infection rates; and the backlog created by the shift in eligibility. The healthcare system needs to build long- term capacity to meet the steady-state need for ART and additional capacity to address the backlog.

  16. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

    Science.gov (United States)

    Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

    2017-01-01

    Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

  17. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Qi Huang

    2017-06-01

    Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

  18. Patterns of HIV-1 Drug Resistance After First-Line Antiretroviral Therapy (ART) Failure in 6 Sub-Saharan African Countries: Implications for Second-Line ART Strategies

    NARCIS (Netherlands)

    Hamers, Raph L.; Sigaloff, Kim C. E.; Wensing, Annemarie M.; Wallis, Carole L.; Kityo, Cissy; Siwale, Margaret; Mandaliya, Kishor; Ive, Prudence; Botes, Mariette E.; Wellington, Maureen; Osibogun, Akin; Stevens, Wendy S.; Rinke de Wit, Tobias F.; Schuurman, Rob; Siwale, M.; Njovu, C.; Labib, M.; Menke, J.; Botes, M. E.; Conradie, F.; Ive, P.; Sanne, I.; Wallis, C. L.; Letsoalo, E.; Stevens, W. S.; Hardman, M.; Wellington, M.; Luthy, R.; Mandaliya, K.; Abdallah, S.; Jao, I.; Dolan, M.; Namayanja, G.; Nakatudde, L.; Nankya, I.; Kiconco, M.; Abwola, M.; Mugyenyi, P.; Osibogun, A.; Akanmu, S.; Schuurman, R.; Wensing, A. M.; Straatsma, E.; Wit, F. W.; Dekker, J.; van Vugt, M.; Lange, J. M.

    2012-01-01

    Background. Human immunodeficiency virus type 1 (HIV-1) drug resistance may limit the benefits of antiretroviral therapy (ART). This cohort study examined patterns of drug-resistance mutations (DRMs) in individuals with virological failure on first-line ART at 13 clinical sites in 6 African

  19. Pattern recognition in cyclic and discrete skills performance from inertial measurement units

    NARCIS (Netherlands)

    Seifert, Ludovic; L'Hermette, Maxime; Komar, John; Orth, Dominic; Mell, Florian; Merriaux, Pierre; Grenet, Pierre; Caritu, Yanis; Hérault, Romain; Dovgalecs, Vladislavs; Davids, Keith

    2014-01-01

    The aim of this study is to compare and validate an Inertial Measurement Unit (IMU) relative to an optic system, and to propose methods for pattern recognition to capture behavioural dynamics during sport performance. IMU validation was conducted by comparing the motions of the two arms of a

  20. Making sense of design patterns

    NARCIS (Netherlands)

    Hoekstra, R.; Breuker, J.

    2010-01-01

    This paper discusses the way in which design patterns may improve the current practice of ontology engineering. It presents five requirements that go beyond the current state of the art of collecting and curating design patterns. We build on the thesis outlined in [17] that design patterns should be

  1. STATE-OF-THE-ART TASKS AND ACHIEVEMENTS OF PARALINGUISTIC SPEECH ANALYSIS SYSTEMS

    Directory of Open Access Journals (Sweden)

    A. A. Karpov

    2016-07-01

    Full Text Available We present analytical survey of state-of-the-art actual tasks in the area of computational paralinguistics, as well as the recent achievements of automatic systems for paralinguistic analysis of conversational speech. Paralinguistics studies non-verbal aspects of human communication and speech such as: natural emotions, accents, psycho-physiological states, pronunciation features, speaker’s voice parameters, etc. We describe architecture of a baseline computer system for acoustical paralinguistic analysis, its main components and useful speech processing methods. We present some information on an International contest called Computational Paralinguistics Challenge (ComParE, which is held each year since 2009 in the framework of the International conference INTERSPEECH organized by the International Speech Communication Association. We present sub-challenges (tasks that were proposed at the ComParE Challenges in 2009-2016, and analyze winning computer systems for each sub-challenge and obtained results. The last completed ComParE-2015 Challenge was organized in September 2015 in Germany and proposed 3 sub-challenges: 1 Degree of Nativeness (DN sub-challenge, determination of nativeness degree of speakers based on acoustics; 2 Parkinson's Condition (PC sub-challenge, recognition of a degree of Parkinson’s condition based on speech analysis; 3 Eating Condition (EC sub-challenge, determination of the eating condition state during speaking or a dialogue, and classification of consumed food type (one of seven classes of food by the speaker. In the last sub-challenge (EC, the winner was a joint Turkish-Russian team consisting of the authors of the given paper. We have developed the most efficient computer-based system for detection and classification of the corresponding (EC acoustical paralinguistic events. The paper deals with the architecture of this system, its main modules and methods, as well as the description of used training and evaluation

  2. Visual Localization by Place Recognition Based on Multifeature (D-λLBP++HOG

    Directory of Open Access Journals (Sweden)

    Yongliang Qiao

    2017-01-01

    Full Text Available Visual localization is widely used in the autonomous navigation system and Advanced Driver Assistance Systems (ADAS. This paper presents a visual localization method based on multifeature fusion and disparity information using stereo images. We integrate disparity information into complete center-symmetric local binary patterns (CSLBP to obtain a robust global image description (D-CSLBP. In order to represent the scene in depth, multifeature fusion of D-CSLBP and HOG features provides valuable information and permits decreasing the effect of some typical problems in place recognition such as perceptual aliasing. It improves visual recognition performance by taking advantage of depth, texture, and shape information. In addition, for real-time visual localization, local sensitive hashing method (LSH was used to compress the high-dimensional multifeature into binary vectors. It can thus speed up the process of image matching. To show its effectiveness, the proposed method is tested and evaluated using real datasets acquired in outdoor environments. Given the obtained results, our approach allows more effective visual localization compared with the state-of-the-art method FAB-MAP.

  3. A new kernel discriminant analysis framework for electronic nose recognition

    International Nuclear Information System (INIS)

    Zhang, Lei; Tian, Feng-Chun

    2014-01-01

    Graphical abstract: - Highlights: • This paper proposes a new discriminant analysis framework for feature extraction and recognition. • The principle of the proposed NDA is derived mathematically. • The NDA framework is coupled with kernel PCA for classification. • The proposed KNDA is compared with state of the art e-Nose recognition methods. • The proposed KNDA shows the best performance in e-Nose experiments. - Abstract: Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter. In terms of the linear separability in high dimensional kernel mapping space and the dimension reduction of principal component analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components by an e-Nose. The NDA framework is derived in this paper as well as the specific implementations of the proposed KNDA method in training and recognition process. The KNDA is examined on the e-Nose datasets of six kinds of gas components, and compared with state of the art e-Nose classification methods. Experimental results demonstrate that the proposed KNDA method shows the best performance with average recognition rate and total recognition rate as 94.14% and 95.06% which leads to a promising feature extraction and multi-class recognition in e-Nose

  4. Scene text recognition in mobile applications by character descriptor and structure configuration.

    Science.gov (United States)

    Yi, Chucai; Tian, Yingli

    2014-07-01

    Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

  5. REMOVAL OF SPECTRO-POLARIMETRIC FRINGES BY TWO-DIMENSIONAL PATTERN RECOGNITION