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Sample records for affect recognition system

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Investigation of parameters affecting voice recognition systems in C3 Systems

    NASA Astrophysics Data System (ADS)

    Batchellor, M. P.

    1981-03-01

    This research investigates the use of a voice recognition system by military operators officer, enlisted, male and female. The application intended is the use of a discrete utterance voice recognition system in a command center environment. The system would be used by members of a watch team to execute ad hoc queries against an automated data base in support of their command center duties. The following factors were examined: the adaptability of a random sample of active duty military personnel to a voice input system; the accuracy of such a system; the effects of male versus female operators; and the effects of officer versus enlisted operators -- the advantages/disadvantages of using three, five or ten trained passes to train the voice system. Results showed no significant difference in error rates between the categories of officer and enlisted nor between male and female. Three training passes had a slightly higher error rate than five or ten passes but five and ten passes were the same.

  3. Employing Textual and Facial Emotion Recognition to Design an Affective Tutoring System

    ERIC Educational Resources Information Center

    Lin, Hao-Chiang Koong; Wang, Cheng-Hung; Chao, Ching-Ju; Chien, Ming-Kuan

    2012-01-01

    Emotional expression in Artificial Intelligence has gained lots of attention in recent years, people applied its affective computing not only in enhancing and realizing the interaction between computers and human, it also makes computer more humane. In this study, emotional expressions were applied into intelligent tutoring system, where learners'…

  4. A preliminary analysis of human factors affecting the recognition accuracy of a discrete word recognizer for C3 systems

    NASA Astrophysics Data System (ADS)

    Yellen, H. W.

    1983-03-01

    Literature pertaining to Voice Recognition abounds with information relevant to the assessment of transitory speech recognition devices. In the past, engineering requirements have dictated the path this technology followed. But, other factors do exist that influence recognition accuracy. This thesis explores the impact of Human Factors on the successful recognition of speech, principally addressing the differences or variability among users. A Threshold Technology T-600 was used for a 100 utterance vocubalary to test 44 subjects. A statistical analysis was conducted on 5 generic categories of Human Factors: Occupational, Operational, Psychological, Physiological and Personal. How the equipment is trained and the experience level of the speaker were found to be key characteristics influencing recognition accuracy. To a lesser extent computer experience, time or week, accent, vital capacity and rate of air flow, speaker cooperativeness and anxiety were found to affect overall error rates.

  5. Audio-visual affective expression recognition

    NASA Astrophysics Data System (ADS)

    Huang, Thomas S.; Zeng, Zhihong

    2007-11-01

    Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

  6. System Factors Affect the Recognition and Management of Post-Traumatic Stress Disorder by Primary Care Clinicians

    PubMed Central

    Meredith, Lisa S; Eisenman, David P; Green, Bonnie L; Basurto-Dávila, Ricardo; Cassells, Andrea; Tobin, Jonathan

    2009-01-01

    Background Post-traumatic stress disorder (PTSD) is common with an estimated prevalence of 8% in the general population and up to 17% in primary care patients. Yet, little is known about what determines primary care clinician’s (PCC) provision of PTSD care. Objective To describe PCC’s reported recognition and management of PTSD and identify how system factors affect the likelihood of performing clinical actions with regard to patients with PTSD or “PTSD treatment proclivity.” Design Linked cross-sectional surveys of medical directors and PCCs. Participants Forty-six medical directors and 154 PCCs in community health centers (CHCs) within a practice-based research network in New York and New Jersey. Measurements Two system factors (degree of integration between primary care and mental health services, and existence of linkages with other community, social, and legal services) as reported by medical directors, and PCC reports of self-confidence, perceived barriers, and PTSD treatment proclivity. Results Surveys from 47 (of 58) medical directors (81% response rate) and 154 PCCs (86% response rate). PCCs from CHCs with better mental health integration reported greater confidence, fewer barriers, and higher PTSD treatment proclivity (all p<.05). PCCs in CHCs with better community linkages reported greater confidence, fewer barriers, higher PTSD treatment proclivity, and lower proclivity to refer patients to mental health specialists or to use a “watch and wait” approach (all p<.05). Conclusion System factors play an important role in PCC PTSD management. Interventions are needed that restructure primary care practices by making mental health services more integrated and community linkages stronger. PMID:19433999

  7. Video Scene Recognition System

    NASA Astrophysics Data System (ADS)

    Wong, Robert Y.; Sallak, Rashid M.

    1983-03-01

    Microprocessors are used to show a possible implementation of a multiprocessoi system for video scene recognition operations. The system was designed in the multiple input stream and multiple data stream (MIMD) configuration. "Autonomous cooperation" among the working processors is supervised by a global operating system, the heart of which is the scheduler. The design of the scheduler and the overall operations of the system are discussed.

  8. Automatic speaker recognition system

    NASA Astrophysics Data System (ADS)

    Higgins, Alan; Naylor, Joe

    1984-07-01

    The Defense Communications Division of ITT (ITTDCD) has developed an automatic speaker recognition (ASR) system that meets the functional requirements defined in NRL's Statement of Work. This report is organized as follows. Chapter 2 is a short history of the development of the ASR system, both the algorithm and the implementation. Chapter 3 describes the methodology of system testing, and Chapter 4 summarizes test results. In Chapter 5, some additional testing performed using GFM test material is discussed. Conclusions derived from the contract work are given in Chapter 6.

  9. Can the usage of human growth hormones affect facial appearance and the accuracy of face recognition systems?

    NASA Astrophysics Data System (ADS)

    Rose, Jake; Martin, Michael; Bourlai, Thirimachos

    2014-06-01

    In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. The goal of the study is to demonstrate that steroid usage significantly affects human facial appearance and hence, the performance of commercial and academic face recognition (FR) algorithms. In this work, we evaluate the performance of state-of-the-art FR algorithms on two unique face image datasets of subjects before (gallery set) and after (probe set) steroid (or human growth hormone) usage. For the purpose of this study, datasets of 73 subjects were created from multiple sources found on the Internet, containing images of men and women before and after steroid usage. Next, we geometrically pre-processed all images of both face datasets. Then, we applied image restoration techniques on the same face datasets, and finally, we applied FR algorithms in order to match the pre-processed face images of our probe datasets against the face images of the gallery set. Experimental results demonstrate that only a specific set of FR algorithms obtain the most accurate results (in terms of the rank-1 identification rate). This is because there are several factors that influence the efficiency of face matchers including (i) the time lapse between the before and after image pre-processing and restoration face photos, (ii) the usage of different drugs (e.g. Dianabol, Winstrol, and Decabolan), (iii) the usage of different cameras to capture face images, and finally, (iv) the variability of standoff distance, illumination and other noise factors (e.g. motion noise). All of the previously mentioned complicated scenarios make clear that cross-scenario matching is a very challenging problem and, thus, further investigation is required.

  10. Facial Affect Recognition and Social Anxiety in Preschool Children

    ERIC Educational Resources Information Center

    Ale, Chelsea M.; Chorney, Daniel B.; Brice, Chad S.; Morris, Tracy L.

    2010-01-01

    Research relating anxiety and facial affect recognition has focused mostly on school-aged children and adults and has yielded mixed results. The current study sought to demonstrate an association among behavioural inhibition and parent-reported social anxiety, shyness, social withdrawal and facial affect recognition performance in 30 children,…

  11. A face recognition embedded system

    NASA Astrophysics Data System (ADS)

    Pun, Kwok Ho; Moon, Yiu Sang; Tsang, Chi Chiu; Chow, Chun Tak; Chan, Siu Man

    2005-03-01

    This paper presents an experimental study of the implementation of a face recognition system in embedded systems. To investigate the feasibility and practicality of real time face recognition on such systems, a door access control system based on face recognition is built. Due to the limited computation power of embedded device, a semi-automatic scheme for face detection and eye location is proposed to solve these computationally hard problems. It is found that to achieve real time performance, optimization of the core face recognition module is needed. As a result, extensive profiling is done to pinpoint the execution hotspots in the system and optimization are carried out. After careful precision analysis, all slow floating point calculations are replaced with their fixed-point versions. Experimental results show that real time performance can be achieved without significant loss in recognition accuracy.

  12. Assessing collective affect recognition via the Emotional Aperture Measure.

    PubMed

    Sanchez-Burks, Jeffrey; Bartel, Caroline A; Rees, Laura; Huy, Quy

    2016-01-01

    Curiosity about collective affect is undergoing a revival in many fields. This literature, tracing back to Le Bon's seminal work on crowd psychology, has established the veracity of collective affect and demonstrated its influence on a wide range of group dynamics. More recently, an interest in the perception of collective affect has emerged, revealing a need for a methodological approach for assessing collective emotion recognition to complement measures of individual emotion recognition. This article addresses this need by introducing the Emotional Aperture Measure (EAM). Three studies provide evidence that collective affect recognition requires a processing style distinct from individual emotion recognition and establishes the validity and reliability of the EAM. A sample of working managers further shows how the EAM provides unique insights into how individuals interact with collectives. We discuss how the EAM can advance several lines of research on collective affect. PMID:25809581

  13. Affective State Level Recognition in Naturalistic Facial and Vocal Expressions.

    PubMed

    Meng, Hongying; Bianchi-Berthouze, Nadia

    2014-03-01

    Naturalistic affective expressions change at a rate much slower than the typical rate at which video or audio is recorded. This increases the probability that consecutive recorded instants of expressions represent the same affective content. In this paper, we exploit such a relationship to improve the recognition performance of continuous naturalistic affective expressions. Using datasets of naturalistic affective expressions (AVEC 2011 audio and video dataset, PAINFUL video dataset) continuously labeled over time and over different dimensions, we analyze the transitions between levels of those dimensions (e.g., transitions in pain intensity level). We use an information theory approach to show that the transitions occur very slowly and hence suggest modeling them as first-order Markov models. The dimension levels are considered to be the hidden states in the Hidden Markov Model (HMM) framework. Their discrete transition and emission matrices are trained by using the labels provided with the training set. The recognition problem is converted into a best path-finding problem to obtain the best hidden states sequence in HMMs. This is a key difference from previous use of HMMs as classifiers. Modeling of the transitions between dimension levels is integrated in a multistage approach, where the first level performs a mapping between the affective expression features and a soft decision value (e.g., an affective dimension level), and further classification stages are modeled as HMMs that refine that mapping by taking into account the temporal relationships between the output decision labels. The experimental results for each of the unimodal datasets show overall performance to be significantly above that of a standard classification system that does not take into account temporal relationships. In particular, the results on the AVEC 2011 audio dataset outperform all other systems presented at the international competition. PMID:23757552

  14. Cognitive object recognition system (CORS)

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  15. Emotions affect the recognition of hand gestures

    PubMed Central

    Vicario, Carmelo M.; Newman, Anica

    2013-01-01

    The body is closely tied to the processing of social and emotional information. The purpose of this study was to determine whether a relationship between emotions and social attitudes conveyed through gestures exists. Thus, we tested the effect of pro-social (i.e., happy face) and anti-social (i.e., angry face) emotional primes on the ability to detect socially relevant hand postures (i.e., pictures depicting an open/closed hand). In particular, participants were required to establish, as quickly as possible, if the test stimulus (i.e., a hand posture) was the same or different, compared to the reference stimulus (i.e., a hand posture) previously displayed in the computer screen. Results show that facial primes, displayed between the reference and the test stimuli, influence the recognition of hand postures, according to the social attitude implicitly related to the stimulus. We found that perception of pro-social (i.e., happy face) primes resulted in slower RTs in detecting the open hand posture as compared to the closed hand posture. Vice-versa, perception of the anti-social (i.e., angry face) prime resulted in slower RTs in detecting the closed hand posture compared to the open hand posture. These results suggest that the social attitude implicitly conveyed by the displayed stimuli might represent the conceptual link between emotions and gestures. PMID:24421763

  16. Ear recognition: a complete system

    NASA Astrophysics Data System (ADS)

    Abaza, Ayman; Harrison, Mary Ann F.

    2013-05-01

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

  17. Affective recognition memory processing and event-related brain potentials

    PubMed Central

    Kaestner, Erik J.

    2011-01-01

    Recognition memory was examined for visual affective stimuli using behavioral and event-related brain potential (ERP) measures. Images from the International Affective Picture System (IAPS) that varied systematically in arousal level (low, high) and valence direction (unpleasant, pleasant) were first viewed passively. Then, during a response phase, the original images were intermixed with an equal number of new images and presented, and participants were instructed to press a button to indicate whether each stimulus picture was previously viewed (target) or new (foil). Participants were more sensitive to unpleasant- than to pleasant-valence stimuli and were biased to respond to high-arousal unpleasant stimuli as targets, whether the stimuli were previously viewed or new. Response times (RTs) to target stimuli were systematically affected by valence, whereas RTs to foil stimuli were influenced by arousal level. ERP component amplitudes were generally larger for high than for low arousal levels. The P300 (late positive component) amplitude was largest for high-arousal unpleasant target images. These and other amplitude effects suggest that high-arousal unpleasant stimuli engage a privileged memory-processing route during stimulus processing. Theoretical relationships between affective and memory processes are discussed. PMID:21384231

  18. The Army word recognition system

    NASA Technical Reports Server (NTRS)

    Hadden, David R.; Haratz, David

    1977-01-01

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

  19. Laptop Computer - Based Facial Recognition System Assessment

    SciTech Connect

    R. A. Cain; G. B. Singleton

    2001-03-01

    The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results. After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master operating in

  20. Pattern recognition systems and procedures

    NASA Technical Reports Server (NTRS)

    Nelson, G. D.; Serreyn, D. V.

    1972-01-01

    The objectives of the pattern recognition tasks are to develop (1) a man-machine interactive data processing system; and (2) procedures to determine effective features as a function of time for crops and soils. The signal analysis and dissemination equipment, SADE, is being developed as a man-machine interactive data processing system. SADE will provide imagery and multi-channel analog tape inputs for digitation and a color display of the data. SADE is an essential tool to aid in the investigation to determine useful features as a function of time for crops and soils. Four related studies are: (1) reliability of the multivariate Gaussian assumption; (2) usefulness of transforming features with regard to the classifier probability of error; (3) advantage of selecting quantizer parameters to minimize the classifier probability of error; and (4) advantage of using contextual data. The study of transformation of variables (features), especially those experimental studies which can be completed with the SADE system, will be done.

  1. Applying Affect Recognition in Serious Games: The PlayMancer Project

    NASA Astrophysics Data System (ADS)

    Ben Moussa, Maher; Magnenat-Thalmann, Nadia

    This paper presents an overview and the state-of-art in the applications of 'affect' recognition in serious games for the support of patients in behavioral and mental disorder treatments and chronic pain rehabilitation, within the framework of the European project PlayMancer. Three key technologies are discussed relating to facial affect recognition, fusion of different affect recognition methods, and the application of affect recognition in serious games.

  2. Assessing the Utility of a Virtual Environment for Enhancing Facial Affect Recognition in Adolescents with Autism

    ERIC Educational Resources Information Center

    Bekele, Esubalew; Crittendon, Julie; Zheng, Zhi; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

    2014-01-01

    Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e.,…

  3. Improving robustness of speech recognition systems

    NASA Astrophysics Data System (ADS)

    Mitra, Vikramjit

    2010-11-01

    Current Automatic Speech Recognition (ASR) systems fail to perform nearly as good as human speech recognition performance due to their lack of robustness against speech variability and noise contamination. The goal of this dissertation is to investigate these critical robustness issues, put forth different ways to address them and finally present an ASR architecture based upon these robustness criteria. Acoustic variations adversely affect the performance of current phone-based ASR systems, in which speech is modeled as 'beads-on-a-string', where the beads are the individual phone units. While phone units are distinctive in cognitive domain, they are varying in the physical domain and their variation occurs due to a combination of factors including speech style, speaking rate etc.; a phenomenon commonly known as 'coarticulation'. Traditional ASR systems address such coarticulatory variations by using contextualized phone-units such as triphones. Articulatory phonology accounts for coarticulatory variations by modeling speech as a constellation of constricting actions known as articulatory gestures. In such a framework, speech variations such as coarticulation and lenition are accounted for by gestural overlap in time and gestural reduction in space. To realize a gesture-based ASR system, articulatory gestures have to be inferred from the acoustic signal. At the initial stage of this research an initial study was performed using synthetically generated speech to obtain a proof-of-concept that articulatory gestures can indeed be recognized from the speech signal. It was observed that having vocal tract constriction trajectories (TVs) as intermediate representation facilitated the gesture recognition task from the speech signal. Presently no natural speech database contains articulatory gesture annotation; hence an automated iterative time-warping architecture is proposed that can annotate any natural speech database with articulatory gestures and TVs. Two natural

  4. Allocentric kin recognition is not affected by facial inversion

    PubMed Central

    Dal Martello, Maria F.; DeBruine, Lisa M.; Maloney, Laurence T.

    2015-01-01

    Typical judgments involving faces are disrupted by inversion, with the Thatcher illusion serving as a compelling example. In two experiments, we examined how inversion affects allocentric kin recognition—the ability to judge the degree of genetic relatedness of others. In the first experiment, participants judged whether pairs of photographs of children portrayed siblings or unrelated children. Half of the pairs were siblings, half were unrelated. In three experimental conditions, photographs were viewed in upright orientation, flipped around a horizontal axis, or rotated 180°. Neither rotation nor flipping had any detectable effect on allocentric kin recognition. In the second experiment, participants judged pairs of photographs of adult women. Half of the pairs were sisters, half were unrelated. We again found no significant effect of facial inversion. Unlike almost all other face judgments, judgments of kinship from facial appearance do not rely on perceptual cues disrupted by inversion, suggesting that they rely more on spatially localized cues rather than “holistic” cues. We conclude that kin recognition is not simply a byproduct of other face perception abilities. We discuss the implications for cue combination models of other facial judgments that are affected by inversion. PMID:26381836

  5. Kannada character recognition system using neural network

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  6. Arousal recognition system based on heartbeat dynamics during auditory elicitation.

    PubMed

    Nardelli, Mimma; Valenza, Gaetano; Greco, Alberto; Lanata, Antonio; Scilingo, Enzo Pasquale

    2015-08-01

    This study reports on the recognition of different arousal levels, elicited by affective sounds, performed using estimates of autonomic nervous system dynamics. Specifically, as a part of the circumplex model of affect, arousal levels were recognized by properly combining information gathered from standard and nonlinear analysis of heartbeat dynamics, which was derived from the electrocardiogram (ECG). Affective sounds were gathered from the International Affective Digitized Sound System and grouped into four different levels of arousal. A group of 27 healthy volunteers underwent such elicitation while ECG signals were continuously recorded. Results showed that a quadratic discriminant classifier, as applied implementing a leave-one-subject-out procedure, achieved a recognition accuracy of 84.26%. Moreover, this study confirms the crucial role of heartbeat nonlinear dynamics for emotion recognition, hereby estimated through lagged Poincare plots. PMID:26737686

  7. Practical automatic Arabic license plate recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

  8. Affective and contextual values modulate spatial frequency use in object recognition

    PubMed Central

    Caplette, Laurent; West, Gregory; Gomot, Marie; Gosselin, Frédéric; Wicker, Bruno

    2014-01-01

    Visual object recognition is of fundamental importance in our everyday interaction with the environment. Recent models of visual perception emphasize the role of top-down predictions facilitating object recognition via initial guesses that limit the number of object representations that need to be considered. Several results suggest that this rapid and efficient object processing relies on the early extraction and processing of low spatial frequencies (LSF). The present study aimed to investigate the SF content of visual object representations and its modulation by contextual and affective values of the perceived object during a picture-name verification task. Stimuli consisted of pictures of objects equalized in SF content and categorized as having low or high affective and contextual values. To access the SF content of stored visual representations of objects, SFs of each image were then randomly sampled on a trial-by-trial basis. Results reveal that intermediate SFs between 14 and 24 cycles per object (2.3–4 cycles per degree) are correlated with fast and accurate identification for all categories of objects. Moreover, there was a significant interaction between affective and contextual values over the SFs correlating with fast recognition. These results suggest that affective and contextual values of a visual object modulate the SF content of its internal representation, thus highlighting the flexibility of the visual recognition system. PMID:24904514

  9. Cochlear Implant Microphone Location Affects Speech Recognition in Diffuse Noise

    PubMed Central

    Kolberg, Elizabeth R.; Sheffield, Sterling W.; Davis, Timothy J.; Sunderhaus, Linsey W.; Gifford, René H.

    2015-01-01

    dB attenuation from 1500–4500 Hz for signals presented at 0° as compared with 90° (directed toward the processor). The T-Mic output was essentially equivalent for sources originating from 0 and 90°. Mic location also significantly affected sentence recognition as a function of source azimuth, with the T-Mic yielding the highest performance for speech originating from 0°. Conclusions These results have clinical implications for (1) future implant processor design with respect to mic location, (2) mic settings for implant recipients, and (3) execution of advanced speech testing in the clinic. PMID:25597460

  10. Automatic TLI recognition system, general description

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

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

  11. Catechol-O-methyltransferase val158met Polymorphism Interacts with Sex to Affect Face Recognition Ability

    PubMed Central

    Lamb, Yvette N.; McKay, Nicole S.; Singh, Shrimal S.; Waldie, Karen E.; Kirk, Ian J.

    2016-01-01

    The catechol-O-methyltransferase (COMT) val158met polymorphism affects the breakdown of synaptic dopamine. Consequently, this polymorphism has been associated with a variety of neurophysiological and behavioral outcomes. Some of the effects have been found to be sex-specific and it appears estrogen may act to down-regulate the activity of the COMT enzyme. The dopaminergic system has been implicated in face recognition, a form of cognition for which a female advantage has typically been reported. This study aimed to investigate potential joint effects of sex and COMT genotype on face recognition. A sample of 142 university students was genotyped and assessed using the Faces I subtest of the Wechsler Memory Scale – Third Edition (WMS-III). A significant two-way interaction between sex and COMT genotype on face recognition performance was found. Of the male participants, COMT val homozygotes and heterozygotes had significantly lower scores than met homozygotes. Scores did not differ between genotypes for female participants. While male val homozygotes had significantly lower scores than female val homozygotes, no sex differences were observed in the heterozygotes and met homozygotes. This study contributes to the accumulating literature documenting sex-specific effects of the COMT polymorphism by demonstrating a COMT-sex interaction for face recognition, and is consistent with a role for dopamine in face recognition. PMID:27445927

  12. Improved MFCC algorithm in speaker recognition system

    NASA Astrophysics Data System (ADS)

    Shi, Yibo; Wang, Li

    2011-10-01

    In speaker recognition systems, one of the key feature parameters is MFCC, which can be used for speaker recognition. So, how to extract MFCC parameter in speech signals more exactly and efficiently, decides the performance of the system. Theoretically, MFCC parameters are used to describe the spectrum envelope of the vocal tract characteristics and often ignore the impacts of fundamental frequency. But in practice, MFCC can be influenced by fundamental frequency which can cause palpable performance reduction. So, smoothing MFCC (SMFCC), which based on smoothing short-term spectral amplitude envelope, has been proposed to improve MFCC algorithm. Experimental results show that improved MFCC parameters---SMFCC can degrade the bad influences of fundamental frequency effectively and upgrade the performances of speaker recognition system. Especially for female speakers, who have higher fundamental frequency, the recognition rate improves more significantly.

  13. Larval memory affects adult nest-mate recognition in the ant Aphaenogaster senilis

    PubMed Central

    Signorotti, Lisa; Jaisson, Pierre; d'Ettorre, Patrizia

    2014-01-01

    Prenatal olfactory learning has been demonstrated in a wide variety of animals, where it affects development and behaviour. Young ants learn the chemical signature of their colony. This cue-learning process allows the formation of a template used for nest-mate recognition in order to distinguish alien individuals from nest-mates, thus ensuring that cooperation is directed towards group members and aliens are kept outside the colony. To date, no study has investigated the possible effect of cue learning during early developmental stages on adult nest-mate recognition. Here, we show that odour familiarization during preimaginal life affects recognition abilities of adult Aphaenogaster senilis ants, particularly when the familiarization process occurs during the first larval stages. Ants eclosed from larvae exposed to the odour of an adoptive colony showed reduced aggression towards familiar, adoptive individuals belonging to this colony compared with alien individuals (true unfamiliar), but they remained non-aggressive towards adult individuals of their natal colony. Moreover, we found that the chemical similarity between the colony of origin and the adoptive colony does not influence the degree of aggression, meaning that the observed effect is likely to be due only to preimaginal learning experience. These results help understanding the developmental processes underlying efficient recognition systems. PMID:24258719

  14. Functional significance of preserved affect recognition in schizophrenia

    PubMed Central

    Fiszdon, Joanna M.; Johannesen, Jason K.

    2009-01-01

    Affect recognition (AR) is a core component of social information processing, thus may be critical to understanding social behavior and functioning in broader aspects of daily living. Deficits in AR are well documented in schizophrenia, however, there is also evidence that many individuals with schizophrenia perform AR tasks at near-normal levels. In the current study, we sought to evaluate the functional significance of AR deficits in schizophrenia by comparing subgroups with normal-range and impaired AR performance on proxy and interviewer-rated measures of real-world functioning. Schizophrenia outpatients were classified as normal-range (N=17) and impaired (N=31) based on a logistic cut point in the sample distribution of BLERT scores, referenced to a normative sample of healthy control subjects (N=56). The derived schizophrenia subgroups were then compared on proxy (UCSD, UPSA, SSPA, MMAA) and interviewer-rated (QLS, ILSS) measures of functioning, as well as battery of neurocognitive tests. Initial analyses indicated superior MMAA and QLS performance in the near-normal AR subgroup. Covariate analyses indicated that group differences in neurocognition fully mediated the observed associations between AR and MMAA and attenuated the observed relationships between AR classification and QLS. These results support three main conclusions. First, AR, like many other domains of psychopathology studied in schizophrenia, is preserved in select subgroups. Second, there is a positive relationship between AR performance and functional outcome measures. Third, neurocognition appears to mediate the relationship between AR and measures of functioning. PMID:20202689

  15. Context affects L1 but not L2 during bilingual word recognition: an MEG study.

    PubMed

    Pellikka, Janne; Helenius, Päivi; Mäkelä, Jyrki P; Lehtonen, Minna

    2015-03-01

    How do bilinguals manage the activation levels of the two languages and prevent interference from the irrelevant language? Using magnetoencephalography, we studied the effect of context on the activation levels of languages by manipulating the composition of word lists (the probability of the languages) presented auditorily to late Finnish-English bilinguals. We first determined the upper limit time-window for semantic access, and then focused on the preceding responses during which the actual word recognition processes were assumedly ongoing. Between 300 and 500 ms in the temporal cortices (in the N400 m response) we found an asymmetric language switching effect: the responses to L1 Finnish words were affected by the presentation context unlike the responses to L2 English words. This finding suggests that the stronger language is suppressed in an L2 context, supporting models that allow auditory word recognition to be affected by contextual factors and the language system to be subject to inhibitory influence. PMID:25656318

  16. Selecting and implementing a voice recognition system.

    PubMed

    Wheeler, S; Cassimus, G C

    1999-01-01

    A single radiology department serves the three separate organizations that comprise Emory Healthcare in Atlanta--three separate hospitals, the Emory Clinic and the Emory University School of Medicine. In 1996, the chairman of Emory Healthcare issued a mandate to the radiology department to decrease its report turnaround time, provide better service and increase customer satisfaction. The area where the greatest effect could be made without involving the transcription area was the "exam complete to dictate" piece of the reporting process. A committee investigating voice recognition systems established an essential criteria for potential vendors--to be able to download patient scheduling and demographic information from the existing RIS to the new system. Second, the system had to be flexible and straightforward for doctors to learn. It must have a word processing package for easy report correction and editing, and a microphone that would rewind and correct dictation before recognition took place. To keep capital costs low for the pilot, the committee opted for server recognition rather than purchase the expensive workstations necessary for real-time recognition. A switch was made later to real-time recognition. PACS and voice recognition have proven to be highly complementary. Most importantly, the new system has had a tremendous impact on turnaround time in the "dictate to final" phase. Once in the 30-hour range, 65 percent of the reports are now turned around in less than 15 minutes, 80 percent in less than 30 minutes, and 90 percent in less than an hour. PMID:10558032

  17. Practical vision based degraded text recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published

  18. Implementation study of wearable sensors for activity recognition systems

    PubMed Central

    Ghassemian, Mona

    2015-01-01

    This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely ‘stream-based’, ‘feature-based’ and ‘threshold-based’ scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency. PMID:26609413

  19. Automatic TLI recognition system beta prototype testing

    SciTech Connect

    Lassahn, G.D.

    1996-06-01

    This report describes the beta prototype automatic target recognition system ATR3, and some performance tests done with this system. This is a fully operational system, with a high computational speed. It is useful for findings any kind of target in digitized image data, and as a general purpose image analysis tool.

  20. Speech recognition system for an automotive vehicle

    SciTech Connect

    Noso, K.; Futami, T.

    1987-01-13

    A speech recognition system is described for an automotive vehicle for activating vehicle actuators in response to predetermined spoken instructions supplied to the system via a microphone, which comprises: (a) a manually controlled record switch for deriving a record signal when activated; (b) a manually controlled recognition switch for deriving a recognition signal when activated; (c) a speech recognizer for sequentially recording reference spoken instructions whenever one reference spoken instruction is supplied to the system through the microphone while the record switch is activated, a memory having a storage area for each spoken instruction, and means for shifting access to each storage area for each spoken instruction has been recorded in the storage area provided therefore. A means is included for activating vehicle actuators sequentially whenever one recognition spoken instruction is supplied to the system via the microphone while the recognition switch is activated and when the spoken instruction to be recognized is similar to the reference spoken instruction; and (d) means for deriving skip instruction signal and for coupling the skip instruction signal to the speech recognizer to shift access from a currently accessed storage area for recording a current reference spoken instruction to a succeeding storage area for recording a succeeding reference spoken instruction even when the current reference spoken instruction is not supplied to the system through the microphone.

  1. Recognition system rapid application prototyping tool

    NASA Astrophysics Data System (ADS)

    Mills, Stuart A.; Karins, James P.; Dydyk, Robert B.

    1997-03-01

    The recognition system rapid application prototyping tool (RSRAPT) was developed to evaluate various potential configurations of miniature ruggedized optical correlator (MROC) modules and to rapidly assess the feasibility of their use within systems such as missile seekers. RSRAPT is a simulation environment for rapidly prototyping, developing, and evaluating recognition systems that incorporate MROC technology. It is designed to interface to OLE compliant Windows applications using standard OLE interfaces. The system consists of nine key functional elements: sensor, detection, segmentation, pre-processor, filter selection, correlator, post-processor, identifier, and controller. The RSRAPT is a collection of object oriented server components, a client user interface and a recognitions system image and image sensor database. The server components are implemented to encapsulate processes that are typical to any optical-correlator based pattern recognition system. All the servers are implemented as Microsoft component object model objects. In addition to the system servers there are two key 'helper servers.' The first is the image server, which encapsulates all 'images'. This includes gray scale images and even complex images. The other supporting server is the filter generation server. This server trains the system on user data by calculating filters for user selected image types. The system hosts a library of standard image processing routines such as convolution, edge operators, clustering algorithms, median filtering, morphological operators such as erosion and dilation, connected components, region growing, and adaptive thresholding. In this paper we describe the simulator and show sample results from diverse applications.

  2. Assessing the Utility of a Virtual Environment for Enhancing Facial Affect Recognition in Adolescents with Autism

    PubMed Central

    Crittendon, Julie; Zheng, Zhi; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

    2014-01-01

    Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e., accuracy, confidence ratings, response latency, and stimulus discrimination) as well as how participants used their gaze to process facial information using an eye tracker. Participants in both groups were similarly accurate at basic facial affect recognition at varied levels of intensity. Despite similar performance characteristics, ASD participants endorsed lower confidence in their responses and substantial variation in gaze patterns in absence of perceptual discrimination deficits. These results add support to the hypothesis that deficits in emotion and face recognition for individuals with ASD are related to fundamental differences in information processing. We discuss implications of this finding in a VR environment with regards to potential future applications and paradigms targeting not just enhanced performance, but enhanced social information processing within intelligent systems capable of adaptation to individual processing differences. PMID:24419871

  3. A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

    PubMed

    Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

    2014-01-01

    Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition. PMID:25380247

  4. A Survey on Automatic Speaker Recognition Systems

    NASA Astrophysics Data System (ADS)

    Saquib, Zia; Salam, Nirmala; Nair, Rekha P.; Pandey, Nipun; Joshi, Akanksha

    Human listeners are capable of identifying a speaker, over the telephone or an entryway out of sight, by listening to the voice of the speaker. Achieving this intrinsic human specific capability is a major challenge for Voice Biometrics. Like human listeners, voice biometrics uses the features of a person's voice to ascertain the speaker's identity. The best-known commercialized forms of voice Biometrics is Speaker Recognition System (SRS). Speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. This literature survey paper gives brief introduction on SRS, and then discusses general architecture of SRS, biometric standards relevant to voice/speech, typical applications of SRS, and current research in Speaker Recognition Systems. We have also surveyed various approaches for SRS.

  5. Changing facial affect recognition in schizophrenia: Effects of training on brain dynamics

    PubMed Central

    Popova, Petia; Popov, Tzvetan G.; Wienbruch, Christian; Carolus, Almut M.; Miller, Gregory A.; Rockstroh, Brigitte S.

    2014-01-01

    Deficits in social cognition including facial affect recognition and their detrimental effects on functional outcome are well established in schizophrenia. Structured training can have substantial effects on social cognitive measures including facial affect recognition. Elucidating training effects on cortical mechanisms involved in facial affect recognition may identify causes of dysfunctional facial affect recognition in schizophrenia and foster remediation strategies. In the present study, 57 schizophrenia patients were randomly assigned to (a) computer-based facial affect training that focused on affect discrimination and working memory in 20 daily 1-hour sessions, (b) similarly intense, targeted cognitive training on auditory-verbal discrimination and working memory, or (c) treatment as usual. Neuromagnetic activity was measured before and after training during a dynamic facial affect recognition task (5 s videos showing human faces gradually changing from neutral to fear or to happy expressions). Effects on 10–13 Hz (alpha) power during the transition from neutral to emotional expressions were assessed via MEG based on previous findings that alpha power increase is related to facial affect recognition and is smaller in schizophrenia than in healthy subjects. Targeted affect training improved overt performance on the training tasks. Moreover, alpha power increase during the dynamic facial affect recognition task was larger after affect training than after treatment-as-usual, though similar to that after targeted perceptual–cognitive training, indicating somewhat nonspecific benefits. Alpha power modulation was unrelated to general neuropsychological test performance, which improved in all groups. Results suggest that specific neural processes supporting facial affect recognition, evident in oscillatory phenomena, are modifiable. This should be considered when developing remediation strategies targeting social cognition in schizophrenia. PMID:25379427

  6. How Aging Affects the Recognition of Emotional Speech

    ERIC Educational Resources Information Center

    Paulmann, Silke; Pell, Marc D.; Kotz, Sonja A.

    2008-01-01

    To successfully infer a speaker's emotional state, diverse sources of emotional information need to be decoded. The present study explored to what extent emotional speech recognition of "basic" emotions (anger, disgust, fear, happiness, pleasant surprise, sadness) differs between different sex (male/female) and age (young/middle-aged) groups in a…

  7. Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury.

    PubMed

    Neumann, Dawn; McDonald, Brenna C; West, John; Keiski, Michelle A; Wang, Yang

    2016-06-01

    The neurobiological mechanisms that underlie facial affect recognition deficits after traumatic brain injury (TBI) have not yet been identified. Using functional magnetic resonance imaging (fMRI), study aims were to 1) determine if there are differences in brain activation during facial affect processing in people with TBI who have facial affect recognition impairments (TBI-I) relative to people with TBI and healthy controls who do not have facial affect recognition impairments (TBI-N and HC, respectively); and 2) identify relationships between neural activity and facial affect recognition performance. A facial affect recognition screening task performed outside the scanner was used to determine group classification; TBI patients who performed greater than one standard deviation below normal performance scores were classified as TBI-I, while TBI patients with normal scores were classified as TBI-N. An fMRI facial recognition paradigm was then performed within the 3T environment. Results from 35 participants are reported (TBI-I = 11, TBI-N = 12, and HC = 12). For the fMRI task, TBI-I and TBI-N groups scored significantly lower than the HC group. Blood oxygenation level-dependent (BOLD) signals for facial affect recognition compared to a baseline condition of viewing a scrambled face, revealed lower neural activation in the right fusiform gyrus (FG) in the TBI-I group than the HC group. Right fusiform gyrus activity correlated with accuracy on the facial affect recognition tasks (both within and outside the scanner). Decreased FG activity suggests facial affect recognition deficits after TBI may be the result of impaired holistic face processing. Future directions and clinical implications are discussed. PMID:26040980

  8. Encoding Conditions Affect Recognition of Vocally Expressed Emotions Across Cultures

    PubMed Central

    Jürgens, Rebecca; Drolet, Matthis; Pirow, Ralph; Scheiner, Elisabeth; Fischer, Julia

    2013-01-01

    Although the expression of emotions in humans is considered to be largely universal, cultural effects contribute to both emotion expression and recognition. To disentangle the interplay between these factors, play-acted and authentic (non-instructed) vocal expressions of emotions were used, on the assumption that cultural effects may contribute differentially to the recognition of staged and spontaneous emotions. Speech tokens depicting four emotions (anger, sadness, joy, fear) were obtained from German radio archives and re-enacted by professional actors, and presented to 120 participants from Germany, Romania, and Indonesia. Participants in all three countries were poor at distinguishing between play-acted and spontaneous emotional utterances (58.73% correct on average with only marginal cultural differences). Nevertheless, authenticity influenced emotion recognition: across cultures, anger was recognized more accurately when play-acted (z = 15.06, p < 0.001) and sadness when authentic (z = 6.63, p < 0.001), replicating previous findings from German populations. German subjects revealed a slight advantage in recognizing emotions, indicating a moderate in-group advantage. There was no difference between Romanian and Indonesian subjects in the overall emotion recognition. Differential cultural effects became particularly apparent in terms of differential biases in emotion attribution. While all participants labeled play-acted expressions as anger more frequently than expected, German participants exhibited a further bias toward choosing anger for spontaneous stimuli. In contrast to the German sample, Romanian and Indonesian participants were biased toward choosing sadness. These results support the view that emotion recognition rests on a complex interaction of human universals and cultural specificities. Whether and in which way the observed biases are linked to cultural differences in self-construal remains an issue for further investigation. PMID

  9. A neuromorphic system for video object recognition

    PubMed Central

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  10. A neuromorphic system for video object recognition.

    PubMed

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  11. Securing iris recognition systems against masquerade attacks

    NASA Astrophysics Data System (ADS)

    Galbally, Javier; Gomez-Barrero, Marta; Ross, Arun; Fierrez, Julian; Ortega-Garcia, Javier

    2013-05-01

    A novel two-stage protection scheme for automatic iris recognition systems against masquerade attacks carried out with synthetically reconstructed iris images is presented. The method uses different characteristics of real iris images to differentiate them from the synthetic ones, thereby addressing important security flaws detected in state-of-the-art commercial systems. Experiments are carried out on the publicly available Biosecure Database and demonstrate the efficacy of the proposed security enhancing approach.

  12. Intelligent recognitive systems in nanomedicine

    PubMed Central

    Culver, Heidi; Daily, Adam; Khademhosseini, Ali

    2014-01-01

    There is a bright future in the development and utilization of nanoscale systems based on intelligent materials that can respond to external input providing a beneficial function. Specific functional groups can be incorporated into polymers to make them responsive to environmental stimuli such as pH, temperature, or varying concentrations of biomolecules. The fusion of such “intelligent” biomaterials with nanotechnology has led to the development of powerful therapeutic and diagnostic platforms. For example, targeted release of proteins and chemotherapeutic drugs has been achieved using pH-responsive nanocarriers while biosensors with ultra-trace detection limits are being made using nanoscale, molecularly imprinted polymers. The efficacy of therapeutics and the sensitivity of diagnostic platforms will continue to progress as unique combinations of responsive polymers and nanomaterials emerge. PMID:24860724

  13. Automatic TLI recognition system, user`s guide

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report describes how to use an automatic target recognition system (version 14). In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a programmer`s manual, Automatic TLI Recognition System, Programmer`s Guide.

  14. An online handwriting recognition system for Turkish

    NASA Astrophysics Data System (ADS)

    Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

    2005-01-01

    Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

  15. An online handwriting recognition system for Turkish

    NASA Astrophysics Data System (ADS)

    Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

    2004-12-01

    Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

  16. Development of a sonar-based object recognition system

    NASA Astrophysics Data System (ADS)

    Ecemis, Mustafa Ihsan

    2001-02-01

    Sonars are used extensively in mobile robotics for obstacle detection, ranging and avoidance. However, these range-finding applications do not exploit the full range of information carried in sonar echoes. In addition, mobile robots need robust object recognition systems. Therefore, a simple and robust object recognition system using ultrasonic sensors may have a wide range of applications in robotics. This dissertation develops and analyzes an object recognition system that uses ultrasonic sensors of the type commonly found on mobile robots. Three principal experiments are used to test the sonar recognition system: object recognition at various distances, object recognition during unconstrained motion, and softness discrimination. The hardware setup, consisting of an inexpensive Polaroid sonar and a data acquisition board, is described first. The software for ultrasound signal generation, echo detection, data collection, and data processing is then presented. Next, the dissertation describes two methods to extract information from the echoes, one in the frequency domain and the other in the time domain. The system uses the fuzzy ARTMAP neural network to recognize objects on the basis of the information content of their echoes. In order to demonstrate that the performance of the system does not depend on the specific classification method being used, the K- Nearest Neighbors (KNN) Algorithm is also implemented. KNN yields a test accuracy similar to fuzzy ARTMAP in all experiments. Finally, the dissertation describes a method for extracting features from the envelope function in order to reduce the dimension of the input vector used by the classifiers. Decreasing the size of the input vectors reduces the memory requirements of the system and makes it run faster. It is shown that this method does not affect the performance of the system dramatically and is more appropriate for some tasks. The results of these experiments demonstrate that sonar can be used to develop

  17. Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

    NASA Astrophysics Data System (ADS)

    Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

    2010-12-01

    This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

  18. Privacy protection schemes for fingerprint recognition systems

    NASA Astrophysics Data System (ADS)

    Marasco, Emanuela; Cukic, Bojan

    2015-05-01

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

  19. Affect Influences False Memories at Encoding: Evidence from Recognition Data

    PubMed Central

    Storbeck, Justin; Clore, Gerald L.

    2014-01-01

    Memory is susceptible to illusions in the form of false memories. Prior research found, however, that sad moods reduce false memories. The current experiment had two goals: (1) to determine whether affect influences retrieval processes, and (2) to determine whether affect influences the strength and the persistence of false memories. Happy or sad moods were induced either before or after learning word lists designed to produce false memories. Control groups did not experience a mood induction. We found that sad moods reduced false memories only when induced before learning. Signal detection analyses confirmed that sad moods induced prior to learning reduced activation of nonpresented critical lures suggesting that they came to mind less often. Affective states, however, did not influence retrieval effects. We conclude that negative affective states promote item-specific processing, which reduces false memories in a similar way as using an explicitly guided cognitive control strategy. PMID:21517165

  20. System and method for character recognition

    NASA Technical Reports Server (NTRS)

    Hong, J. P. (Inventor)

    1974-01-01

    A character recognition system is disclosed in which each character in a retina, defining a scanning raster, is scanned with random lines uniformly distributed over the retina. For each type of character to be recognized the system stores a probability density function (PDF) of the random line intersection lengths and/or a PDF of the random line number of intersections. As an unknown character is scanned, the random line intersection lengths and/or the random line number of intersections are accumulated and based on a comparison with the prestored PDFs a classification of the unknown character is performed.

  1. Directed forgetting in the list method affects recognition memory for source.

    PubMed

    Gottlob, Lawrence R; Golding, Jonathan M

    2007-11-01

    The effects of list-method directed forgetting on recognition memory were explored. In Experiment 1 (N = 40), observers were instructed to remember words and their type-cases; in Experiment 2 (N = 80), the instruction was to remember words and their colours. Two lists of 10 words were presented; after the first list, half of the observers (forget) were instructed to forget that list, and the other half (remember) were not given the forget instruction. Recognition of items (words) as well as source (encoding list + case/colour) was measured for forget and remember observers. The forget instruction affected case/colour memory more consistently than item and list memory, a multinomial analysis indicated that source information was affected by the forget instructions. The results indicated that recognition of source information may be a more sensitive indicator of forgetting than recognition of items. PMID:17853219

  2. EEG Responses to Auditory Stimuli for Automatic Affect Recognition

    PubMed Central

    Hettich, Dirk T.; Bolinger, Elaina; Matuz, Tamara; Birbaumer, Niels; Rosenstiel, Wolfgang; Spüler, Martin

    2016-01-01

    Brain state classification for communication and control has been well established in the area of brain-computer interfaces over the last decades. Recently, the passive and automatic extraction of additional information regarding the psychological state of users from neurophysiological signals has gained increased attention in the interdisciplinary field of affective computing. We investigated how well specific emotional reactions, induced by auditory stimuli, can be detected in EEG recordings. We introduce an auditory emotion induction paradigm based on the International Affective Digitized Sounds 2nd Edition (IADS-2) database also suitable for disabled individuals. Stimuli are grouped in three valence categories: unpleasant, neutral, and pleasant. Significant differences in time domain domain event-related potentials are found in the electroencephalogram (EEG) between unpleasant and neutral, as well as pleasant and neutral conditions over midline electrodes. Time domain data were classified in three binary classification problems using a linear support vector machine (SVM) classifier. We discuss three classification performance measures in the context of affective computing and outline some strategies for conducting and reporting affect classification studies. PMID:27375410

  3. EEG Responses to Auditory Stimuli for Automatic Affect Recognition.

    PubMed

    Hettich, Dirk T; Bolinger, Elaina; Matuz, Tamara; Birbaumer, Niels; Rosenstiel, Wolfgang; Spüler, Martin

    2016-01-01

    Brain state classification for communication and control has been well established in the area of brain-computer interfaces over the last decades. Recently, the passive and automatic extraction of additional information regarding the psychological state of users from neurophysiological signals has gained increased attention in the interdisciplinary field of affective computing. We investigated how well specific emotional reactions, induced by auditory stimuli, can be detected in EEG recordings. We introduce an auditory emotion induction paradigm based on the International Affective Digitized Sounds 2nd Edition (IADS-2) database also suitable for disabled individuals. Stimuli are grouped in three valence categories: unpleasant, neutral, and pleasant. Significant differences in time domain domain event-related potentials are found in the electroencephalogram (EEG) between unpleasant and neutral, as well as pleasant and neutral conditions over midline electrodes. Time domain data were classified in three binary classification problems using a linear support vector machine (SVM) classifier. We discuss three classification performance measures in the context of affective computing and outline some strategies for conducting and reporting affect classification studies. PMID:27375410

  4. Poor Facial Affect Recognition among Boys with Duchenne Muscular Dystrophy

    ERIC Educational Resources Information Center

    Hinton, V. J.; Fee, R. J.; De Vivo, D. C.; Goldstein, E.

    2007-01-01

    Children with Duchenne or Becker muscular dystrophy (MD) have delayed language and poor social skills and some meet criteria for Pervasive Developmental Disorder, yet they are identified by molecular, rather than behavioral, characteristics. To determine whether comprehension of facial affect is compromised in boys with MD, children were given a…

  5. Predicting the Accuracy of Facial Affect Recognition: The Interaction of Child Maltreatment and Intellectual Functioning

    ERIC Educational Resources Information Center

    Shenk, Chad E.; Putnam, Frank W.; Noll, Jennie G.

    2013-01-01

    Previous research demonstrates that both child maltreatment and intellectual performance contribute uniquely to the accurate identification of facial affect by children and adolescents. The purpose of this study was to extend this research by examining whether child maltreatment affects the accuracy of facial recognition differently at varying…

  6. Does humor in radio advertising affect recognition of novel product brand names?

    PubMed

    Berg, E M; Lippman, L G

    2001-04-01

    The authors proposed that item selection during shopping is based on brand name recognition rather than recall. College students rated advertisements and news stories of a simulated radio program for level of amusement (orienting activity) before participating in a surprise recognition test. Humor level of the advertisements was varied systematically, and content was controlled. According to signal detection analysis, humor did not affect the strength of recognition memory for brand names (nonsense units). However, brand names and product types were significantly more likely to be associated when appearing in humorous advertisements than in nonhumorous advertisements. The results are compared with prior findings concerning humor and recall. PMID:11506048

  7. Perceptual and affective mechanisms in facial expression recognition: An integrative review.

    PubMed

    Calvo, Manuel G; Nummenmaa, Lauri

    2016-09-01

    Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser's internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with "emotionless" computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms. PMID:26212348

  8. Edge detection techniques for iris recognition system

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  9. Positive and negative affect recognition in schizophrenia: a comparison with substance abuse and normal control subjects.

    PubMed

    Bell, M; Bryson, G; Lysaker, P

    1997-11-14

    This study had three aims: to compare a schizophrenia sample (n = 50) with a substance abuse (n = 25) and normal sample (n = 81) on affect recognition; to compare differences in their performance between positive and negative affect recognition; and to introduce a new videotape method of stimulus presentation. Subjects were asked to identify the predominant affect depicted in 21 5-10-s vignettes containing three trials of seven affect states. Results demonstrate significant group differences: normal subjects scored in the normal or mild range, substance abuse (s/a) subjects scored in the mild and moderate ranges, and the schizophrenia sample scored predominantly in the moderate to severe ranges. Accuracies were 92.3% for the normal sample, 77.2 for the s/a sample and 64.8 for the schizophrenia sample. Response dispersions were 97.6% for the schizophrenia group, 69% for the s/a sample and 38% in the normal sample. A repeated measures ANOVA revealed a group by type of affect interaction with schizophrenia subjects showing far greater differential impairment on negative affect recognition. Difficulty of item did not contribute to this difference. Test-retest reliability at 5 months for this new method was r = 0.76, and stability of categorization was very high over 5 months (weighted kappa = 0.93). These affect recognition deficits in schizophrenia are discussed as they relate to lateralization of brain function, high EE families, social skills impairment and implications for rehabilitation services. PMID:9463840

  10. Positive Mood Induction and Facial Affect Recognition among Students at Risk for Mania.

    PubMed

    Trevisani, Dante P; Johnson, Sheri L; Carver, Charles S

    2008-01-01

    Previous research has suggested that bipolar disorder is characterized by a state-dependent decrease in the ability to recognize facial affect during mania. It remains unclear, though, whether people who are only vulnerable to the disorder show these changes in facial affect recognition. It is also unclear whether minor shifts in mood affect the recognition of facial emotion. Thus, this study examined the effects of positive mood induction on the facial affect recognition of undergraduates vulnerable to mania. Fifty-two undergraduates completed the Hypomanic Personality Scale, and also completed a measure of their ability to recognize affect in pictures of faces. After receiving false success feedback on another task to induce a positive mood, they completed the facial affect recognition measure again. Although we expected to find a relationship between higher Hypomanic Personality Scale (HPS) scores and an impaired ability to recognize negative facial affect after a positive mood induction, this was not found. Rather, there was a significant interaction between HPS scores and happiness level, such that individuals with higher scores on the HPS who also reported higher levels of happiness were particularly adept at identifying subtle facial expressions of happiness. This finding expands a growing literature linking manic tendencies to sensitivity to positive stimuli and demonstrates that this sensitivity may have bearing on interpersonal interactions. PMID:20126422

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

    SciTech Connect

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

    1994-05-01

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

  12. Method and System for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  13. Recognition of error symptoms in large systems

    NASA Technical Reports Server (NTRS)

    Iyer, Ravishankar K.; Sridhar, V.

    1987-01-01

    A methodology for automatically detecting symptoms of frequently occurring errors in large computer systems is developed. The proposed symptom recognition methodology and its validation are based on probabilistic techniques. The technique is shown to work on real failure data from two CYBER systems at the University of Illinois. The methodology allows for the resolution between independent and dependent causes and, also quantifies a measure of the strength of relationship among errors. Comparison made with failure/repair information obtained from field maintenance engineers shows that in 85% of the cases, the error symptoms recognized by our approach correspond to real system problems. Further, the remaining 15% although not directly supported by field data, were confirmed as valid problems. Some of these were shown to be persistent problems which otherwise would have been considered as minor transients and hence ignored.

  14. [Development of the affect system].

    PubMed

    Moser, U; Von Zeppelin, I

    1996-01-01

    The authors show that the development of the affect system commences with affects of an exclusively communicative nature. These regulate the relationship between subject and object. On a different plane they also provide information on the feeling of self deriving from the interaction. Affect is seen throughout as a special kind of information. One section of the article is given over to intensity regulation and early affect defenses. The development of cognitive processes leads to the integration of affect systems and cognitive structures. In the pre-conceptual concretistic phase, fantasies change the object relation in such a way as to make unpleasant affects disappear. Only at a later stage do fantasies acquire the capacity to deal with affects. Ultimately, the affect system is grounded on an invariant relationship feeling. On a variety of different levels it displays the features typical of situation theory and the theory of the representational world, thus making it possible to entertain complex object relations. In this process the various planes of the affect system are retained and practised. Finally, the authors discuss the consequences of their remarks for the understanding of psychic disturbances and the therapies brought to bear on them. PMID:8584745

  15. Impairments in facial affect recognition associated with autism spectrum disorders: a meta-analysis.

    PubMed

    Lozier, Leah M; Vanmeter, John W; Marsh, Abigail A

    2014-11-01

    Autism spectrum disorders (ASDs) are characterized by social impairments, including inappropriate responses to affective stimuli and nonverbal cues, which may extend to poor face-emotion recognition. However, the results of empirical studies of face-emotion recognition in individuals with ASD have yielded inconsistent findings that occlude understanding the role of face-emotion recognition deficits in the development of ASD. The goal of this meta-analysis was to address three as-yet unanswered questions. Are ASDs associated with consistent face-emotion recognition deficits? Do deficits generalize across multiple emotional expressions or are they limited to specific emotions? Do age or cognitive intelligence affect the magnitude of identified deficits? The results indicate that ASDs are associated with face-emotion recognition deficits across multiple expressions and that the magnitude of these deficits increases with age and cannot be accounted for by intelligence. These findings suggest that, whereas neurodevelopmental processes and social experience produce improvements in general face-emotion recognition abilities over time during typical development, children with ASD may experience disruptions in these processes, which suggested distributed functional impairment in the neural architecture that subserves face-emotion processing, an effect with downstream developmental consequences. PMID:24915526

  16. Automatic TLI recognition system, programmer`s guide

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report describes the software of an automatic target recognition system (version 14), from a programmer`s point of view. The intent is to provide information that will help people who wish to modify the software. In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a user`s manual, Automatic TLI Recognition System, User`s Guide. 2 refs.

  17. Optical music recognition system which learns

    NASA Astrophysics Data System (ADS)

    Fujinaga, Ichiro

    1993-01-01

    This paper describes an optical music recognition system composed of a database and three interdependent processes: a recognizer, an editor, and a learner. Given a scanned image of a musical score, the recognizer locates, separates, and classifies symbols into musically meaningful categories. This classification is based on the k-nearest neighbor method using a subset of the database that contains features of symbols classified in previous recognition sessions. Output of the recognizer is corrected by a musically trained human operator using a music notation editor. The editor provides both visual and high-quality audio feedback of the output. Editorial corrections made by the operator are passed to the learner which then adds the newly acquired data to the database. The learner's main task, however, involves selecting a subset of the database and reweighing the importance of the features to improve accuracy and speed for subsequent sessions. Good preliminary results have been obtained with everything from professionally engraved scores to hand-written manuscripts.

  18. Mutants affecting nucleotide recognition by T7 DNA polymerase.

    PubMed

    Donlin, M J; Johnson, K A

    1994-12-13

    Analysis of two mutations affecting nucleotide selection by the DNA polymerase from bacteriophage T7 is reported here. Two conserved residues (Glu480 and Tyr530) in the polymerase active site of an exonuclease deficient (exo-) T7 DNA polymerase were mutated using site-directed mutagenesis (Glu480-Asp and Tyr530-Phe). The kinetic and equilibrium constants governing DNA binding, nucleotide incorporation, and pyrophosphorolysis were measured with the mutants E480D(exo-) and Y530F(exo-) in single-turnover experiments using rapid chemical quench-flow methods. Both mutants have slightly lower Kd values for DNA binding compared to that of wild-type(exo-). With Y530F(exo-) the ground state nucleotide binding affinity was unchanged from wild-type for dGTP and dCTP, was 2-fold lower for dATP and 8-10-fold lower for dTTP binding. With E480D(exo-), the binding constants were 5-6-fold lower for dATP, dGTP, and dCTP and 40-fold lower for dTTP binding compared to those constants for wild-type(exo-). The significance of a specific destabilization of dTTP binding by these amino acids was examined using a dGTP analog, deoxyinosine triphosphate, which mimics the placement and number of hydrogen bonds of an A:T base pair. The Kd for dCTP opposite inosine was unchanged with wild-type(exo-) (197 microM) but higher with Y530F(exo-) (454 microM) and with E480D(exo-) (1 mM). The Kd for dITP was the same with wild-type(exo-) (180 microM) and Y530F(exo-) (229 microM), but significantly higher with E480D(exo-) (3.2 mM). These data support the suggestion that E480 selectively stabilizes dTTP in the wild-type enzyme, perhaps by hydrogen bonding to the unbonded carbonyl. Data on the incorporation of dideoxynucleotide analogs were consistent with the observation of a selective stabilization of dTTP by both residues. Pyrophosphorolysis experiments revealed that neither mutation had a significant effect on the chemistry of polymerization. The fidelity of the mutants were examined in

  19. The Relation of Facial Affect Recognition and Empathy to Delinquency in Youth Offenders

    ERIC Educational Resources Information Center

    Carr, Mary B.; Lutjemeier, John A.

    2005-01-01

    Associations among facial affect recognition, empathy, and self-reported delinquency were studied in a sample of 29 male youth offenders at a probation placement facility. Youth offenders were asked to recognize facial expressions of emotions from adult faces, child faces, and cartoon faces. Youth offenders also responded to a series of statements…

  20. Elementary neurocognitive function, facial affect recognition and social-skills in schizophrenia.

    PubMed

    Meyer, Melissa B; Kurtz, Matthew M

    2009-05-01

    Social-skill deficits are pervasive in schizophrenia and negatively impact many key aspects of functioning. Prior studies have found that measures of elementary neurocognition and social cognition are related to social-skills. In the present study we selected a range of neurocognitive measures and examined their relationship with identification of happy and sad faces and performance-based social-skills. Fifty-three patients with schizophrenia or schizoaffective disorder participated. Results revealed that: 1) visual vigilance, problem-solving and affect recognition were related to social-skill; 2) links between problem-solving and social-skill, but not visual vigilance and social-skill, remained significant when estimates of verbal intelligence were controlled; 3) affect recognition deficits explained unique variance in social-skill after neurocognitive variables were controlled; and 4) affect recognition deficits partially mediated the relationship of visual vigilance and social-skill. These results support the conclusion that facial affect recognition deficits are a crucial domain of impairment in schizophrenia that both contribute unique variance to social-skill deficits and may also mediate the relationship between some aspects of neurocognition and social-skill. These findings may help guide the development and refinement of cognitive and social-cognitive remediation methods for social-skill impairment. PMID:19328653

  1. How Cross-Language Similarity and Task Demands Affect Cognate Recognition

    ERIC Educational Resources Information Center

    Dijkstra, Ton; Miwa, Koji; Brummelhuis, Bianca; Sappelli, Maya; Baayen, Harald

    2010-01-01

    This study examines how the cross-linguistic similarity of translation equivalents affects bilingual word recognition. Performing one of three tasks, Dutch-English bilinguals processed cognates with varying degrees of form overlap between their English and Dutch counterparts (e.g., "lamp-lamp" vs. "flood-vloed" vs. "song-lied"). In lexical…

  2. Orthographic Consistency Affects Spoken Word Recognition at Different Grain-Sizes

    ERIC Educational Resources Information Center

    Dich, Nadya

    2014-01-01

    A number of previous studies found that the consistency of sound-to-spelling mappings (feedback consistency) affects spoken word recognition. In auditory lexical decision experiments, words that can only be spelled one way are recognized faster than words with multiple potential spellings. Previous studies demonstrated this by manipulating…

  3. Recognition of metal cations by biological systems.

    PubMed

    Truter, M R

    1975-11-01

    Recognition of metal cations by biological systems can be compared with the geochemical criteria for isomorphous replacement. Biological systems are more highly selective and much more rapid. Methods of maintaining an optimum concentration, including storage and transfer for the essential trace elements, copper and iron, used in some organisms are in part reproducible by coordination chemists while other features have not been reporduced in models. Poisoning can result from a foreign metal taking part in a reaction irreversibly so that the recognition site or molecule is not released. For major nutrients, sodium, potassium, magnesium and calcium, there are similarities to the trace metals in selective uptake but differences qualitatively and quantitatively in biological activity. Compounds selective for potassium replace all the solvation sphere with a symmetrical arrangement of oxygen atoms; those selective for sodium give an asymmetrical environment with retention of a solvent molecule. Experiments with naturally occurring antibiotics and synthetic model compounds have shown that flexibility is an important feature of selectivity and that for transfer or carrier properties there is an optimum (as opposed to a maximum) metal-ligand stability constant. Thallium is taken up instead of potassium and will activate some enzymes; it is suggested that the poisonous characteristics arise because the thallium ion may bind more strongly than potassium to part of a site and then fail to bind additional atoms as required for the biological activity. Criteria for the design of selective complexing agents are given with indications of those which might transfer more than one metal at once. PMID:1815

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

    ERIC Educational Resources Information Center

    Li, Fuhui

    2015-01-01

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

  5. A road sign detection and recognition system for mobile devices

    NASA Astrophysics Data System (ADS)

    Xiong, Bo; Izmirli, Ozgur

    2012-01-01

    We present an automatic road sign detection and recognition service system for mobile devices. The system is based on a client-server architecture which allows mobile users to take pictures of road signs and request detection and recognition service from a centralized server for processing. The preprocessing, detection and recognition take place at the server end and consequently, the result is sent back to the mobile device. For road sign detection, we use particular color features calculated from the input image. Recognition is implemented using a neural network based on normalized color histogram features. We report on the effects of various parameters on recognition accuracy. Our results demonstrate that the system can provide an efficient framework for locale-dependent road sign recognition with multilingual support.

  6. CACNA1C risk variant affects facial emotion recognition in healthy individuals

    PubMed Central

    Nieratschker, Vanessa; Brückmann, Christof; Plewnia, Christian

    2015-01-01

    Recognition and correct interpretation of facial emotion is essential for social interaction and communication. Previous studies have shown that impairments in this cognitive domain are common features of several psychiatric disorders. Recent association studies identified CACNA1C as one of the most promising genetic risk factors for psychiatric disorders and previous evidence suggests that the most replicated risk variant in CACNA1C (rs1006737) is affecting emotion recognition and processing. However, studies investigating the influence of rs1006737 on this intermediate phenotype in healthy subjects at the behavioral level are largely missing to date. Here, we applied the “Reading the Mind in the Eyes” test, a facial emotion recognition paradigm in a cohort of 92 healthy individuals to address this question. Whereas accuracy was not affected by genotype, CACNA1C rs1006737 risk-allele carries (AA/AG) showed significantly slower mean response times compared to individuals homozygous for the G-allele, indicating that healthy risk-allele carriers require more information to correctly identify a facial emotion. Our study is the first to provide evidence for an impairing behavioral effect of the CACNA1C risk variant rs1006737 on facial emotion recognition in healthy individuals and adds to the growing number of studies pointing towards CACNA1C as affecting intermediate phenotypes of psychiatric disorders. PMID:26611642

  7. CACNA1C risk variant affects facial emotion recognition in healthy individuals.

    PubMed

    Nieratschker, Vanessa; Brückmann, Christof; Plewnia, Christian

    2015-01-01

    Recognition and correct interpretation of facial emotion is essential for social interaction and communication. Previous studies have shown that impairments in this cognitive domain are common features of several psychiatric disorders. Recent association studies identified CACNA1C as one of the most promising genetic risk factors for psychiatric disorders and previous evidence suggests that the most replicated risk variant in CACNA1C (rs1006737) is affecting emotion recognition and processing. However, studies investigating the influence of rs1006737 on this intermediate phenotype in healthy subjects at the behavioral level are largely missing to date. Here, we applied the "Reading the Mind in the Eyes" test, a facial emotion recognition paradigm in a cohort of 92 healthy individuals to address this question. Whereas accuracy was not affected by genotype, CACNA1C rs1006737 risk-allele carries (AA/AG) showed significantly slower mean response times compared to individuals homozygous for the G-allele, indicating that healthy risk-allele carriers require more information to correctly identify a facial emotion. Our study is the first to provide evidence for an impairing behavioral effect of the CACNA1C risk variant rs1006737 on facial emotion recognition in healthy individuals and adds to the growing number of studies pointing towards CACNA1C as affecting intermediate phenotypes of psychiatric disorders. PMID:26611642

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

    PubMed Central

    Joongrock, Kim; Sunjin, Yu; Sangyoun, Lee

    2014-01-01

    In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation. PMID:24691101

  9. Hybrid gesture recognition system for short-range use

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  10. Facial affect recognition in early and late-stage schizophrenia patients.

    PubMed

    Romero-Ferreiro, María Verónica; Aguado, Luis; Rodriguez-Torresano, Javier; Palomo, Tomás; Rodriguez-Jimenez, Roberto; Pedreira-Massa, José Luis

    2016-04-01

    Prior studies have shown deficits in social cognition and emotion perception in first-episode psychosis (FEP) and multi-episode schizophrenia (MES) patients. These studies compared patients at different stages of the illness with only a single control group which differed in age from at least one clinical group. The present study provides new evidence of a differential pattern of deficit in facial affect recognition in FEP and MES patients using a double age-matched control design. Compared to their controls, FEP patients only showed impaired recognition of fearful faces (p=.007). In contrast to this, the MES patients showed a more generalized deficit compared to their age-matched controls, with impaired recognition of angry, sad and fearful faces (ps<.01) and an increased misattribution of emotional meaning to neutral faces. PANSS scores of FEP patients on Depressed factor correlated positively with the accuracy to recognize fearful expressions (r=.473). For the MES group fear recognition correlated positively with negative PANSS factor (r=.498) and recognition of sad and neutral expressions was inversely correlated with disorganized PANSS factor (r=-.461 and r=-.541, respectively). These results provide evidence that a generalized impairment of affect recognition is observed in advanced-stage patients and is not characteristic of the early stages of schizophrenia. Moreover, the finding that anomalous attribution of emotional meaning to neutral faces is observed only in MES patients suggests that an increased attribution of salience to social stimuli is a characteristic of social cognition in advanced stages of the disorder. PMID:26874869

  11. Automated recognition system for power quality disturbances

    NASA Astrophysics Data System (ADS)

    Abdelgalil, Tarek

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

  12. How a hat may affect 3-month-olds' recognition of a face: an eye-tracking study.

    PubMed

    Bulf, Hermann; Valenza, Eloisa; Turati, Chiara

    2013-01-01

    Recent studies have shown that infants' face recognition rests on a robust face representation that is resilient to a variety of facial transformations such as rotations in depth, motion, occlusion or deprivation of inner/outer features. Here, we investigated whether 3-month-old infants' ability to represent the invariant aspects of a face is affected by the presence of an external add-on element, i.e. a hat. Using a visual habituation task, three experiments were carried out in which face recognition was investigated by manipulating the presence/absence of a hat during face encoding (i.e. habituation phase) and face recognition (i.e. test phase). An eye-tracker system was used to record the time infants spent looking at face-relevant information compared to the hat. The results showed that infants' face recognition was not affected by the presence of the external element when the type of the hat did not vary between the habituation and test phases, and when both the novel and the familiar face wore the same hat during the test phase (Experiment 1). Infants' ability to recognize the invariant aspects of a face was preserved also when the hat was absent in the habituation phase and the same hat was shown only during the test phase (Experiment 2). Conversely, when the novel face identity competed with a novel hat, the hat triggered the infants' attention, interfering with the recognition process and preventing the infants' preference for the novel face during the test phase (Experiment 3). Findings from the current study shed light on how faces and objects are processed when they are simultaneously presented in the same visual scene, contributing to an understanding of how infants respond to the multiple and composite information available in their surrounding environment. PMID:24349378

  13. Social-Cognitive Remediation in Schizophrenia: Generalization of Effects of the Training of Affect Recognition (TAR)

    PubMed Central

    Wölwer, Wolfgang; Frommann, Nicole

    2011-01-01

    In the last decade, several social cognitive remediation programs have been developed for use in schizophrenia. Though existing evidence indicates that such programs can improve social cognition, which is essential for successful social functioning, it remains unclear whether the improvements generalize to social cognitive domains not primarily addressed by the intervention and whether the improved test performance transfers into everyday social functioning. The present study investigated whether, beyond its known effects on facial affect recognition, the Training of Affect Recognition (TAR) has effects on prosodic affect recognition, theory of mind (ToM) performance, social competence in a role-play task, and more general social and occupational functioning. Thirty-eight inpatients with a diagnosis of schizophrenia or schizoaffective disorder were randomly assigned to 6 weeks of treatment with the TAR—primarily targeted at facial affect recognition—or Cognitive Remediation Training (CRT)—primarily targeted at neurocognition. Intention-to-treat analyses found significantly larger pre–post improvements with TAR than with CRT in prosodic affect recognition, ToM, and social competence and a trend effect in global social functioning. However, the effects on ToM and social competence were no longer significant in the smaller group of patients who completed treatment according to protocol. Results suggest that TAR effects generalize to other social cognitive domains not primarily addressed. TAR may also enhance social skills and social functioning, although this has to be confirmed. Results are discussed with regard to the need to improve functional outcome in schizophrenia against the background of current evidence from other social cognitive remediation approaches. PMID:21860049

  14. Predicting the accuracy of facial affect recognition: the interaction of child maltreatment and intellectual functioning.

    PubMed

    Shenk, Chad E; Putnam, Frank W; Noll, Jennie G

    2013-02-01

    Previous research demonstrates that both child maltreatment and intellectual performance contribute uniquely to the accurate identification of facial affect by children and adolescents. The purpose of this study was to extend this research by examining whether child maltreatment affects the accuracy of facial recognition differently at varying levels of intellectual functioning. A sample of maltreated (n=50) and nonmaltreated (n=56) adolescent females, 14 to 19 years of age, was recruited to participate in this study. Participants completed demographic and study-related questionnaires and interviews to control for potential psychological and psychiatric confounds such as symptoms of posttraumatic stress disorder, negative affect, and difficulties in emotion regulation. Participants also completed an experimental paradigm that recorded responses to facial affect displays starting in a neutral expression and changing into a full expression of one of six emotions: happiness, sadness, anger, disgust, fear, or surprise. Hierarchical multiple regression assessed the incremental advantage of evaluating the interaction between child maltreatment and intellectual functioning. Results indicated that the interaction term accounted for a significant amount of additional variance in the accurate identification of facial affect after controlling for relevant covariates and main effects. Specifically, maltreated females with lower levels of intellectual functioning were least accurate in identifying facial affect displays, whereas those with higher levels of intellectual functioning performed as well as nonmaltreated females. These results suggest that maltreatment and intellectual functioning interact to predict the recognition of facial affect, with potential long-term consequences for the interpersonal functioning of maltreated females. PMID:23036371

  15. Embedded palmprint recognition system using OMAP 3530.

    PubMed

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

    2012-01-01

    We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance. PMID:22438721

  16. Embedded Palmprint Recognition System Using OMAP 3530

    PubMed Central

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

    2012-01-01

    We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance. PMID:22438721

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

    PubMed Central

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency. PMID:26346654

  18. Developmental Patterns in Affective Recognition: Implications for Affective Education (HYP/POL).

    ERIC Educational Resources Information Center

    Gordon, Neal J.

    Implications for affective education are drawn from an empirical study of 60 upper-middle socioeconomic class 6 to 15 year-olds' responses to questions asking how videotaped actors felt. Percentage frequencies of category use in tape-recorded transcripts coded by two judges revealed no differences by child's sex. Marked developmental differences…

  19. ERK Pathway Activation Bidirectionally Affects Visual Recognition Memory and Synaptic Plasticity in the Perirhinal Cortex

    PubMed Central

    Silingardi, Davide; Angelucci, Andrea; De Pasquale, Roberto; Borsotti, Marco; Squitieri, Giovanni; Brambilla, Riccardo; Putignano, Elena; Pizzorusso, Tommaso; Berardi, Nicoletta

    2011-01-01

    ERK 1,2 pathway mediates experience-dependent gene transcription in neurons and several studies have identified its pivotal role in experience-dependent synaptic plasticity and in forms of long term memory involving hippocampus, amygdala, or striatum. The perirhinal cortex (PRHC) plays an essential role in familiarity-based object recognition memory. It is still unknown whether ERK activation in PRHC is necessary for recognition memory consolidation. Most important, it is unknown whether by modulating the gain of the ERK pathway it is possible to bidirectionally affect visual recognition memory and PRHC synaptic plasticity. We have first pharmacologically blocked ERK activation in the PRHC of adult mice and found that this was sufficient to impair long term recognition memory in a familiarity-based task, the object recognition task (ORT). We have then tested performance in the ORT in Ras-GRF1 knock-out (KO) mice, which exhibit a reduced activation of ERK by neuronal activity, and in ERK1 KO mice, which have an increased activation of ERK2 and exhibit enhanced striatal plasticity and striatal mediated memory. We found that Ras-GRF1 KO mice have normal short term memory but display a long term memory deficit; memory reconsolidation is also impaired. On the contrary, ERK1 KO mice exhibit a better performance than WT mice at 72 h retention interval, suggesting a longer lasting recognition memory. In parallel with behavioral data, LTD was strongly reduced and LTP was significantly smaller in PRHC slices from Ras-GRF1 KO than in WT mice while enhanced LTP and LTD were found in PRHC slices from ERK1 KO mice. PMID:22232579

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

    ERIC Educational Resources Information Center

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

    1991-01-01

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

  1. Burkholderia cenocepacia Lipopolysaccharide Modification and Flagellin Glycosylation Affect Virulence but Not Innate Immune Recognition in Plants

    PubMed Central

    Khodai-Kalaki, Maryam; Andrade, Angel; Fathy Mohamed, Yasmine

    2015-01-01

    ABSTRACT Burkholderia cenocepacia causes opportunistic infections in plants, insects, animals, and humans, suggesting that “virulence” depends on the host and its innate susceptibility to infection. We hypothesized that modifications in key bacterial molecules recognized by the innate immune system modulate host responses to B. cenocepacia. Indeed, modification of lipopolysaccharide (LPS) with 4-amino-4-deoxy-l-arabinose and flagellin glycosylation attenuates B. cenocepacia infection in Arabidopsis thaliana and Galleria mellonella insect larvae. However, B. cenocepacia LPS and flagellin triggered rapid bursts of nitric oxide and reactive oxygen species in A. thaliana leading to activation of the PR-1 defense gene. These responses were drastically reduced in plants with fls2 (flagellin FLS2 host receptor kinase), Atnoa1 (nitric oxide-associated protein 1), and dnd1-1 (reduced production of nitric oxide) null mutations. Together, our results indicate that LPS modification and flagellin glycosylation do not affect recognition by plant receptors but are required for bacteria to establish overt infection. PMID:26045541

  2. Cellular Phone Face Recognition System Based on Optical Phase Correlation

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Sayuri; Ohta, Maiko; Kodate, Kashiko

    We propose a high security facial recognition system using a cellular phone on the mobile network. This system is composed of a face recognition engine based on optical phase correlation which uses phase information with emphasis on a Fourier domain, a control sever and the cellular phone with a compact camera for taking pictures, as a portable terminal. Compared with various correlation methods, our face recognition engine revealed the most accurate EER of less than 1%. By using the JAVA interface on this system, we implemented the stable system taking pictures, providing functions to prevent spoofing while transferring images. This recognition system was tested on 300 women students and the results proved this system effective.

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

    NASA Astrophysics Data System (ADS)

    Peng, Liangrui; Xiu, Pingping; Ding, Xiaoqing

    2003-12-01

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

  4. Remote weapon station for automatic target recognition system demand analysis

    NASA Astrophysics Data System (ADS)

    Lei, Zhang; Li, Sheng-cai; Shi, Cai

    2015-08-01

    Introduces a remote weapon station basic composition and the main advantage, analysis of target based on image automatic recognition system for remote weapon station of practical significance, the system elaborated the image based automatic target recognition system in the photoelectric stabilized technology, multi-sensor image fusion technology, integrated control target image enhancement, target behavior risk analysis technology, intelligent based on the character of the image automatic target recognition algorithm research, micro sensor technology as the key technology of the development in the field of demand.

  5. Parallel effects of processing fluency and positive affect on familiarity-based recognition decisions for faces

    PubMed Central

    Duke, Devin; Fiacconi, Chris M.; Köhler, Stefan

    2014-01-01

    According to attribution models of familiarity assessment, people can use a heuristic in recognition-memory decisions, in which they attribute the subjective ease of processing of a memory probe to a prior encounter with the stimulus in question. Research in social cognition suggests that experienced positive affect may be the proximal cue that signals fluency in various experimental contexts. In the present study, we compared the effects of positive affect and fluency on recognition-memory judgments for faces with neutral emotional expression. We predicted that if positive affect is indeed the critical cue that signals processing fluency at retrieval, then its manipulation should produce effects that closely mirror those produced by manipulations of processing fluency. In two experiments, we employed a masked-priming procedure in combination with a Remember-Know (RK) paradigm that aimed to separate familiarity- from recollection-based memory decisions. In addition, participants performed a prime-discrimination task that allowed us to take inter-individual differences in prime awareness into account. We found highly similar effects of our priming manipulations of processing fluency and of positive affect. In both cases, the critical effect was specific to familiarity-based recognition responses. Moreover, in both experiments it was reflected in a shift toward a more liberal response bias, rather than in changed discrimination. Finally, in both experiments, the effect was found to be related to prime awareness; it was present only in participants who reported a lack of such awareness on the prime-discrimination task. These findings add to a growing body of evidence that points not only to a role of fluency, but also of positive affect in familiarity assessment. As such they are consistent with the idea that fluency itself may be hedonically marked. PMID:24795678

  6. Context Effects on Facial Affect Recognition in Schizophrenia and Autism: Behavioral and Eye-Tracking Evidence.

    PubMed

    Sasson, Noah J; Pinkham, Amy E; Weittenhiller, Lauren P; Faso, Daniel J; Simpson, Claire

    2016-05-01

    Although Schizophrenia (SCZ) and Autism Spectrum Disorder (ASD) share impairments in emotion recognition, the mechanisms underlying these impairments may differ. The current study used the novel "Emotions in Context" task to examine how the interpretation and visual inspection of facial affect is modulated by congruent and incongruent emotional contexts in SCZ and ASD. Both adults with SCZ (n= 44) and those with ASD (n= 21) exhibited reduced affect recognition relative to typically-developing (TD) controls (n= 39) when faces were integrated within broader emotional scenes but not when they were presented in isolation, underscoring the importance of using stimuli that better approximate real-world contexts. Additionally, viewing faces within congruent emotional scenes improved accuracy and visual attention to the face for controls more so than the clinical groups, suggesting that individuals with SCZ and ASD may not benefit from the presence of complementary emotional information as readily as controls. Despite these similarities, important distinctions between SCZ and ASD were found. In every condition, IQ was related to emotion-recognition accuracy for the SCZ group but not for the ASD or TD groups. Further, only the ASD group failed to increase their visual attention to faces in incongruent emotional scenes, suggesting a lower reliance on facial information within ambiguous emotional contexts relative to congruent ones. Collectively, these findings highlight both shared and distinct social cognitive processes in SCZ and ASD that may contribute to their characteristic social disabilities. PMID:26645375

  7. Kanji Recognition by Second Language Learners: Exploring Effects of First Language Writing Systems and Second Language Exposure

    ERIC Educational Resources Information Center

    Matsumoto, Kazumi

    2013-01-01

    This study investigated whether learners of Japanese with different first language (L1) writing systems use different recognition strategies and whether second language (L2) exposure affects L2 kanji recognition. The study used a computerized lexical judgment task with 3 types of kanji characters to investigate these questions: (a)…

  8. Automatic TLI recognition system. Part 2: User`s guide

    SciTech Connect

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

    1994-05-01

    This report describes an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system uses image data fusion and gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. This volume is a user`s manual for an Automatic Target Recognition (ATR) system. This guide is intended to provide enough information and instruction to allow individuals to the system for their own applications.

  9. Individual differences in involvement of the visual object recognition system during visual word recognition.

    PubMed

    Laszlo, Sarah; Sacchi, Elizabeth

    2015-01-01

    Individuals with dyslexia often evince reduced activation during reading in left hemisphere (LH) language regions. This can be observed along with increased activation in the right hemisphere (RH), especially in areas associated with object recognition - a pattern referred to as RH compensation. The mechanisms of RH compensation are relatively unclear. We hypothesize that RH compensation occurs when the RH object recognition system is called upon to supplement an underperforming LH visual word form recognition system. We tested this by collecting ERPs while participants with a range of reading abilities viewed words, objects, and word/object ambiguous items (e.g., "SMILE" shaped like a smile). Less experienced readers differentiate words, objects, and ambiguous items less strongly, especially over the RH. We suggest that this lack of differentiation may have negative consequences for dyslexic individuals demonstrating RH compensation. PMID:25957504

  10. Facial Affect Recognition Training Through Telepractice: Two Case Studies of Individuals with Chronic Traumatic Brain Injury

    PubMed Central

    WILLIAMSON, JOHN; ISAKI, EMI

    2015-01-01

    The use of a modified Facial Affect Recognition (FAR) training to identify emotions was investigated with two case studies of adults with moderate to severe chronic (> five years) traumatic brain injury (TBI). The modified FAR training was administered via telepractice to target social communication skills. Therapy consisted of identifying emotions through static facial expressions, personally reflecting on those emotions, and identifying sarcasm and emotions within social stories and role-play. Pre- and post-therapy measures included static facial photos to identify emotion and the Prutting and Kirchner Pragmatic Protocol for social communication. Both participants with chronic TBI showed gains on identifying facial emotions on the static photos.

  11. A hybrid recognition system for off-line handwritten characters.

    PubMed

    Katiyar, Gauri; Mehfuz, Shabana

    2016-01-01

    Computer based pattern recognition is a process that involves several sub-processes, including pre-processing, feature extraction, feature selection, and classification. Feature extraction is the estimation of certain attributes of the target patterns. Selection of the right set of features is the most crucial and complex part of building a pattern recognition system. In this work we have combined multiple features extracted using seven different approaches. The novelty of this approach is to achieve better accuracy and reduced computational time for recognition of handwritten characters using Genetic Algorithm which optimizes the number of features along with a simple and adaptive Multi Layer Perceptron classifier. Experiments have been performed using standard database of CEDAR (Centre of Excellence for Document Analysis and Recognition) for English alphabet. The experimental results obtained on this database demonstrate the effectiveness of this system. PMID:27066370

  12. Optical Correlator for Face Recognition Using Collinear Holographic System

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Kodate, Kashiko

    2006-08-01

    We have constructed an optical correlator for fast face recognition. Recognition rate can be markedly improved, if reference images are optically recorded and can be accessed directly without converting them to digital signals. In addition, a large capacity of optical storage allows us to increase the size of the reference database. We propose a new optical correlator that integrates the optical correlation technology used in our face recognition system and collinear holography. From preliminary correlation experiments using the collinear optical set-up, we achieved excellent performance of high correlation peaks and low error rates. We expect an optical correlation of 10 μs/frame, i.e., 100,000 face/s when applied to face recognition. This system can also be applied to various image searches.

  13. Seasonal polyphenism in wing coloration affects species recognition in rubyspot damselflies (Hetaerina spp.).

    PubMed

    Drury, J P; Anderson, C N; Grether, G F

    2015-08-01

    Understanding how phenotypic plasticity evolves and in turn affects the course of evolution is a major challenge in modern biology. By definition, biological species are reproductively isolated, but many animals fail to distinguish between conspecifics and closely related heterospecifics. In some cases, phenotypic plasticity may interfere with species recognition. Here, we document a seasonal polyphenism in the degree of dark wing pigmentation in smoky rubyspot damselflies (Hetaerina titia) - a shift so pronounced that it led early researchers to classify different forms of H. titia as separate species. We further show how the seasonal colour shift impacts species recognition with the sympatric congener Hetaerina occisa. Interspecific aggression (territorial fights) and reproductive interference (mating attempts) are much more frequent early in the year, when H. titia more closely resembles H. occisa, compared to later in the year when the dark phase of H. titia predominates. Using wing colour manipulations of tethered damselflies, we show that the seasonal changes in interspecific interactions are caused not only by the seasonal colour shift but also by shifts in discriminatory behaviour in both species. We also experimentally tested and rejected the hypothesis that learning underlies the behavioural shifts in H. occisa. An alternative hypothesis, which remains to be tested, is that the seasonal polyphenism in H. titia wing coloration has resulted in the evolution of a corresponding seasonal polyphenism in species recognition in H. occisa. This study illustrates one of the many possible ways that plasticity in species recognition cues may influence the evolution of interspecific interactions. PMID:26033550

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  15. FACELOCK-Lock Control Security System Using Face Recognition-

    NASA Astrophysics Data System (ADS)

    Hirayama, Takatsugu; Iwai, Yoshio; Yachida, Masahiko

    A security system using biometric person authentication technologies is suited to various high-security situations. The technology based on face recognition has advantages such as lower user’s resistance and lower stress. However, facial appearances change according to facial pose, expression, lighting, and age. We have developed the FACELOCK security system based on our face recognition methods. Our methods are robust for various facial appearances except facial pose. Our system consists of clients and a server. The client communicates with the server through our protocol over a LAN. Users of our system do not need to be careful about their facial appearance.

  16. Effects of age and task difficulty on recognition of facial affect.

    PubMed

    Orgeta, Vasiliki

    2010-05-01

    Current evidence suggests that older adults are less accurate than young adults in their ability to identify facial expressions of emotion. In the present study, young and older adults' ability to correctly recognize facial affect representative of 6 different emotions (happiness, surprise, disgust, fear, anger, and sadness) was examined in 3 conditions varying in difficulty. Task difficulty was measured by varying the number of labels available in a forced choice recognition task to 2, 4, and 6. Results showed that age differences were present in the 2 more difficult conditions for fear and sadness. Older adults were impaired in recognizing facial expressions of surprise only in the 4-label condition. Current findings suggest that task difficulty moderates age differences in emotion labeling. The present study has contributed to previous research by illuminating the conditions under which age differences in the accuracy of labeling of facial affect are more likely to be observed. PMID:20176659

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

    NASA Technical Reports Server (NTRS)

    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.

  18. Recognition of Intensive Valence and Arousal Affective States via Facial Electromyographic Activity in Young and Senior Adults

    PubMed Central

    Li, Hang; Walter, Steffen; Hrabal, David; Rukavina, Stefanie; Limbrecht-Ecklundt, Kerstin; Hoffman, Holger; Traue, Harald C.

    2016-01-01

    Background Research suggests that interaction between humans and digital environments characterizes a form of companionship in addition to technical convenience. To this effect, humans have attempted to design computer systems able to demonstrably empathize with the human affective experience. Facial electromyography (EMG) is one such technique enabling machines to access to human affective states. Numerous studies have investigated the effects of valence emotions on facial EMG activity captured over the corrugator supercilii (frowning muscle) and zygomaticus major (smiling muscle). The arousal emotion, specifically, has not received much research attention, however. In the present study, we sought to identify intensive valence and arousal affective states via facial EMG activity. Methods Ten blocks of affective pictures were separated into five categories: neutral valence/low arousal (0VLA), positive valence/high arousal (PVHA), negative valence/high arousal (NVHA), positive valence/low arousal (PVLA), and negative valence/low arousal (NVLA), and the ability of each to elicit corresponding valence and arousal affective states was investigated at length. One hundred and thirteen participants were subjected to these stimuli and provided facial EMG. A set of 16 features based on the amplitude, frequency, predictability, and variability of signals was defined and classified using a support vector machine (SVM). Results We observed highly accurate classification rates based on the combined corrugator and zygomaticus EMG, ranging from 75.69% to 100.00% for the baseline and five affective states (0VLA, PVHA, PVLA, NVHA, and NVLA) in all individuals. There were significant differences in classification rate accuracy between senior and young adults, but there was no significant difference between female and male participants. Conclusion Our research provides robust evidences for recognition of intensive valence and arousal affective states in young and senior adults. These

  19. Molecular recognition in chemical and biological systems.

    PubMed

    Persch, Elke; Dumele, Oliver; Diederich, François

    2015-03-01

    Structure-based ligand design in medicinal chemistry and crop protection relies on the identification and quantification of weak noncovalent interactions and understanding the role of water. Small-molecule and protein structural database searches are important tools to retrieve existing knowledge. Thermodynamic profiling, combined with X-ray structural and computational studies, is the key to elucidate the energetics of the replacement of water by ligands. Biological receptor sites vary greatly in shape, conformational dynamics, and polarity, and require different ligand-design strategies, as shown for various case studies. Interactions between dipoles have become a central theme of molecular recognition. Orthogonal interactions, halogen bonding, and amide⋅⋅⋅π stacking provide new tools for innovative lead optimization. The combination of synthetic models and biological complexation studies is required to gather reliable information on weak noncovalent interactions and the role of water. PMID:25630692

  20. Toward a unified model of face and object recognition in the human visual system

    PubMed Central

    Wallis, Guy

    2013-01-01

    Our understanding of the mechanisms and neural substrates underlying visual recognition has made considerable progress over the past 30 years. During this period, accumulating evidence has led many scientists to conclude that objects and faces are recognised in fundamentally distinct ways, and in fundamentally distinct cortical areas. In the psychological literature, in particular, this dissociation has led to a palpable disconnect between theories of how we process and represent the two classes of object. This paper follows a trend in part of the recognition literature to try to reconcile what we know about these two forms of recognition by considering the effects of learning. Taking a widely accepted, self-organizing model of object recognition, this paper explains how such a system is affected by repeated exposure to specific stimulus classes. In so doing, it explains how many aspects of recognition generally regarded as unusual to faces (holistic processing, configural processing, sensitivity to inversion, the other-race effect, the prototype effect, etc.) are emergent properties of category-specific learning within such a system. Overall, the paper describes how a single model of recognition learning can and does produce the seemingly very different types of representation associated with faces and objects. PMID:23966963

  1. Neural Mechanisms and Information Processing in Recognition Systems

    PubMed Central

    Ozaki, Mamiko; Hefetz, Abraham

    2014-01-01

    Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold. PMID:26462936

  2. Neural Mechanisms and Information Processing in Recognition Systems.

    PubMed

    Ozaki, Mamiko; Hefetz, Abraham

    2014-01-01

    Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of "pre-filter mechanism", posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an "aggressive-behavior-switching center", where the response is generated if the signal is above a certain threshold. PMID:26462936

  3. Low Energy Physical Activity Recognition System on Smartphones

    PubMed Central

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

    2015-01-01

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

  4. HIV Infection Seems to Affect Nervous System

    MedlinePlus

    ... fullstory_159344.html HIV Infection Seems to Affect Nervous System But symptoms tend to subside once antiretroviral drugs ... mild, it is clear that HIV affects the nervous system within days of infection," she said in a ...

  5. Mood Swings: An Affective Interactive Art System

    NASA Astrophysics Data System (ADS)

    Bialoskorski, Leticia S. S.; Westerink, Joyce H. D. M.; van den Broek, Egon L.

    The progress in the field of affective computing enables the realization of affective consumer products, affective games, and affective art. This paper describes the affective interactive art system Mood Swings, which interprets and visualizes affect expressed by a person. Mood Swings is founded on the integration of a framework for affective movements and a color model. This enables Mood Swings to recognize affective movement characteristics as expressed by a person and display a color that matches the expressed emotion. With that, a unique interactive system is introduced, which can be considered as art, a game, or a combination of both.

  6. Working Memory Load Affects Processing Time in Spoken Word Recognition: Evidence from Eye-Movements.

    PubMed

    Hadar, Britt; Skrzypek, Joshua E; Wingfield, Arthur; Ben-David, Boaz M

    2016-01-01

    In daily life, speech perception is usually accompanied by other tasks that tap into working memory capacity. However, the role of working memory on speech processing is not clear. The goal of this study was to examine how working memory load affects the timeline for spoken word recognition in ideal listening conditions. We used the "visual world" eye-tracking paradigm. The task consisted of spoken instructions referring to one of four objects depicted on a computer monitor (e.g., "point at the candle"). Half of the trials presented a phonological competitor to the target word that either overlapped in the initial syllable (onset) or at the last syllable (offset). Eye movements captured listeners' ability to differentiate the target noun from its depicted phonological competitor (e.g., candy or sandal). We manipulated working memory load by using a digit pre-load task, where participants had to retain either one (low-load) or four (high-load) spoken digits for the duration of a spoken word recognition trial. The data show that the high-load condition delayed real-time target discrimination. Specifically, a four-digit load was sufficient to delay the point of discrimination between the spoken target word and its phonological competitor. Our results emphasize the important role working memory plays in speech perception, even when performed by young adults in ideal listening conditions. PMID:27242424

  7. Working Memory Load Affects Processing Time in Spoken Word Recognition: Evidence from Eye-Movements

    PubMed Central

    Hadar, Britt; Skrzypek, Joshua E.; Wingfield, Arthur; Ben-David, Boaz M.

    2016-01-01

    In daily life, speech perception is usually accompanied by other tasks that tap into working memory capacity. However, the role of working memory on speech processing is not clear. The goal of this study was to examine how working memory load affects the timeline for spoken word recognition in ideal listening conditions. We used the “visual world” eye-tracking paradigm. The task consisted of spoken instructions referring to one of four objects depicted on a computer monitor (e.g., “point at the candle”). Half of the trials presented a phonological competitor to the target word that either overlapped in the initial syllable (onset) or at the last syllable (offset). Eye movements captured listeners' ability to differentiate the target noun from its depicted phonological competitor (e.g., candy or sandal). We manipulated working memory load by using a digit pre-load task, where participants had to retain either one (low-load) or four (high-load) spoken digits for the duration of a spoken word recognition trial. The data show that the high-load condition delayed real-time target discrimination. Specifically, a four-digit load was sufficient to delay the point of discrimination between the spoken target word and its phonological competitor. Our results emphasize the important role working memory plays in speech perception, even when performed by young adults in ideal listening conditions. PMID:27242424

  8. Mate Recognition and Expression of Affective State in Croop Calls of Northern Bald Ibis (Geronticus eremita)

    PubMed Central

    Szipl, Georgine; Boeckle, Markus; Werner, Sinja A. B.; Kotrschal, Kurt

    2014-01-01

    Northern Bald Ibis are socially monogamous and year-round colonial birds with a moderate repertoire of calls. Their ‘croop’, for example, is used during greeting of mates, but also during agonistic encounters, and provides an ideal case to study whether calls are revealing with respect to motivational states. We recorded croop calls in a semi-tame and free-roaming flock of Northern Bald Ibis in Austria, and analysed the vocal structure to identify parameters (e.g. call duration, fundamental frequency) potentially differing between social contexts, sexes and individuals. Additionally, we conducted playback experiments to test whether mated pairs would discriminate each other by their greeting croops. Acoustic features showed highly variable temporal and structural parameters. Almost all calls could be classified correctly and assigned to the different social contexts and sexes. Classification results of greeting croops were less clear for individuality. However, incubating individuals looked up more often and longer in response to playbacks of the greeting calls of their mate than to other colony members, indicating mate recognition. We show that acoustic parameters of agonistic and greeting croops contain features that may indicate the expression of affective states, and that greeting croops encode individual differences that are sufficient for individual recognition. PMID:24505455

  9. Face Recognition Is Affected by Similarity in Spatial Frequency Range to a Greater Degree Than Within-Category Object Recognition

    ERIC Educational Resources Information Center

    Collin, Charles A.; Liu, Chang Hong; Troje, Nikolaus F.; McMullen, Patricia A.; Chaudhuri, Avi

    2004-01-01

    Previous studies have suggested that face identification is more sensitive to variations in spatial frequency content than object recognition, but none have compared how sensitive the 2 processes are to variations in spatial frequency overlap (SFO). The authors tested face and object matching accuracy under varying SFO conditions. Their results…

  10. Demonstration of the ULTOR target recognition and tracking system

    NASA Astrophysics Data System (ADS)

    Hartman, Richard L.; Farr, Keith B.

    2003-08-01

    Advanced Optical Systems has developed the world's smallest and lowest cost, fully functional target recognition and tracking system. The heart of the ULTOR target recognition and tracking system is an optical correlator. The system includes real-time preprocessing, large filter stores, filter management logic, correlation detection and thresholding, correlation tracking, and data output. It is self contained, receiving operational commands as an Internet appliance. We will present a demonstration of some of the capabilities of the system using live video signals and real target models. The ULTOR system has wide application in both military and commercial settings. The Navy is considering use of the ULTOR system in several programs, including missile systems and unmanned aerial vehicles.

  11. The relation of facial affect recognition and empathy to delinquency in youth offenders.

    PubMed

    Carr, Mary B; Lutjemeier, John A

    2005-01-01

    Associations among facial affect recognition, empathy, and self-reported delin-quency were studied in a sample of 29 male youth offenders at a probation placement facility. Youth offenders were asked to recognize facial expressions of emotions from adult faces, child faces, and cartoon faces. Youth offenders also responded to a series of statements on emotional empathy, and provided self-reported acts of delinquency. Findings revealed a moderate positive relationship between ability to recognize the expression, angry, in adult faces, and self-reported acts of delinquent behavior, which included physical violence, theft, and vandalism. Findings revealed a moderate inverse relationship between ability to recognize facial expressions of emotions in child faces and self-reported acts of physical violence. With respect to specific facial expressions of emotions in child faces, a moderate inverse relationship was found between ability to recognize the expression, fearful, and self-reported acts of physical violence. A moderate positive relationship was found between ability to recognized the expression, fearful, in child faces, and ability to empathize with the emotional experiences of others. Strong and moderate links were found between the negative expressions, fearful and sad, and angry and sad, respectively. Additionally, a strong inverse relationship was found between ability to emphathize with the emotional experiences of others and self-reported acts of delinquent behavior. Lastly, a strong positive relationship was found between covert and overt self-reported acts of delinquent behavior. Results from this exploratory investigation suggest a link between facial affect recognition, empathy, and delinquency. Findings have important implications for educators and counselors who work with youth offenders within probation placement facilities. PMID:16268136

  12. Social trait judgment and affect recognition from static faces and video vignettes in schizophrenia.

    PubMed

    McIntosh, Lindsey G; Park, Sohee

    2014-09-01

    Social impairment is a core feature of schizophrenia, present from the pre-morbid stage and predictive of outcome, but the etiology of this deficit remains poorly understood. Successful and adaptive social interactions depend on one's ability to make rapid and accurate judgments about others in real time. Our surprising ability to form accurate first impressions from brief exposures, known as "thin slices" of behavior has been studied very extensively in healthy participants. We sought to examine affect and social trait judgment from thin slices of static or video stimuli in order to investigate the ability of schizophrenic individuals to form reliable social impressions of others. 21 individuals with schizophrenia (SZ) and 20 matched healthy participants (HC) were asked to identify emotions and social traits for actors in standardized face stimuli as well as brief video clips. Sound was removed from videos to remove all verbal cues. Clinical symptoms in SZ and delusional ideation in both groups were measured. Results showed a general impairment in affect recognition for both types of stimuli in SZ. However, the two groups did not differ in the judgments of trustworthiness, approachability, attractiveness, and intelligence. Interestingly, in SZ, the severity of positive symptoms was correlated with higher ratings of attractiveness, trustworthiness, and approachability. Finally, increased delusional ideation in SZ was associated with a tendency to rate others as more trustworthy, while the opposite was true for HC. These findings suggest that complex social judgments in SZ are affected by symptomatology. PMID:25037526

  13. Social trait judgment and affect recognition from static faces and video vignettes in schizophrenia

    PubMed Central

    McIntosh, Lindsey G.; Park, Sohee

    2014-01-01

    Social impairment is a core feature of schizophrenia, present from the pre-morbid stage and predictive of outcome, but the etiology of this deficit remains poorly understood. Successful and adaptive social interactions depend on one’s ability to make rapid and accurate judgments about others in real time. Our surprising ability to form accurate first impressions from brief exposures, known as “thin slices” of behavior has been studied very extensively in healthy participants. We sought to examine affect and social trait judgment from thin slices of static or video stimuli in order to investigate the ability of schizophrenic individuals to form reliable social impressions of others. 21 individuals with schizophrenia (SZ) and 20 matched healthy participants (HC) were asked to identify emotions and social traits for actors in standardized face stimuli as well as brief video clips. Sound was removed from videos to remove all verbal cues. Clinical symptoms in SZ and delusional ideation in both groups were measured. Results showed a general impairment in affect recognition for both types of stimuli in SZ. However, the two groups did not differ in the judgments of trustworthiness, approachability, attractiveness, and intelligence. Interestingly, in SZ, the severity of positive symptoms was correlated with higher ratings of attractiveness, trustworthiness, and approachability. Finally, increased delusional ideation in SZ was associated with a tendency to rate others as more trustworthy, while the opposite was true for HC. These findings suggest that complex social judgments in SZ are affected by symptomatology. PMID:25037526

  14. Hostility and Facial Affect Recognition: Effects of a Cold Pressor Stressor on Accuracy and Cardiovascular Reactivity

    ERIC Educational Resources Information Center

    Herridge, Matt L.; Harrison, David W.; Mollet, Gina A.; Shenal, Brian V.

    2004-01-01

    The effects of hostility and a cold pressor stressor on the accuracy of facial affect perception were examined in the present experiment. A mechanism whereby physiological arousal level is mediated by systems which also mediate accuracy of an individual's interpretation of affective cues is described. Right-handed participants were classified as…

  15. Dynamic Artificial Neural Networks with Affective Systems

    PubMed Central

    Schuman, Catherine D.; Birdwell, J. Douglas

    2013-01-01

    Artificial neural networks (ANNs) are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP) and long term depression (LTD), and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance. PMID:24303015

  16. Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

    PubMed

    Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

    2016-08-01

    Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research. PMID:26761193

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

    SciTech Connect

    Beer, C.L.

    1993-07-01

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

  18. Crozier’s paradox revisited: maintenance of genetic recognition systems by disassortative mating

    PubMed Central

    2013-01-01

    Background Organisms are predicted to behave more favourably towards relatives, and kin-biased cooperation has been found in all domains of life from bacteria to vertebrates. Cooperation based on genetic recognition cues is paradoxical because it disproportionately benefits individuals with common phenotypes, which should erode the required cue polymorphism. Theoretical models suggest that many recognition loci likely have some secondary function that is subject to diversifying selection, keeping them variable. Results Here, we use individual-based simulations to investigate the hypothesis that the dual use of recognition cues to facilitate social behaviour and disassortative mating (e.g. for inbreeding avoidance) can maintain cue diversity over evolutionary time. Our model shows that when organisms mate disassortatively with respect to their recognition cues, cooperation and recognition locus diversity can persist at high values, especially when outcrossed matings produce more surviving offspring. Mating system affects cue diversity via at least four distinct mechanisms, and its effects interact with other parameters such as population structure. Also, the attrition of cue diversity is less rapid when cooperation does not require an exact cue match. Using a literature review, we show that there is abundant empirical evidence that heritable recognition cues are simultaneously used in social and sexual behaviour. Conclusions Our models show that mate choice is one possible resolution of the paradox of genetic kin recognition, and the literature review suggests that genetic recognition cues simultaneously inform assortative cooperation and disassortative mating in a large range of taxa. However, direct evidence is scant and there is substantial scope for future work. PMID:24070498

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

    NASA Astrophysics Data System (ADS)

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

    1998-07-01

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

  20. A Compact Prototype of an Optical Pattern Recognition System

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  1. New taste sensor system combined with chaotic recognition

    NASA Astrophysics Data System (ADS)

    Hu, Jie; Wang, Ping; Li, Rong

    2001-09-01

    Taste sensor as a new kind of chemical sensor has been studied by many researchers. We have developed several types of taste sensor system and some new recognition methods for taste substance. Kiyoshi Toko et al proposed a new kind of chaos taste sensor that is based on sensor chaos dynamics. In this paper, we improve the taste sensor based on chaos dynamics and proposed a new method for the pattern recognition of tastes. We use three kinds of tastes, i.e., sweetness, salty taste, and sourness. They cause the membrane oscillate in different form, and the complexity is not the same. We can detect taste based on the new method.

  2. An Overview of Hand Gestures Recognition System Techniques

    NASA Astrophysics Data System (ADS)

    Farhana Mod Ma'asum, Farah; Sulaiman, Suhana; Saparon, Azilah

    2015-11-01

    Hand gesture recognition system has evolved tremendously in the recent few years because of its ability to interact with machine efficiently. Mankind tries to incorporate human gestures into modern technology by searching and finding a replacement of multi touch technology which does not require any touching movement on screen. This paper presents an overview on several methods to realize hand gesture recognition by using three main modules: camera and segmentation module, detection module and feature extraction module. There are many methods which can be used to get the respective results depending on its advantages. Summary of previous research and results of hand gesture methods as well as comparison between gesture recognition are also given in this paper.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Liu, Ting; Li, Ailan

    2015-07-01

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

  4. Color recognition system for urine analyzer

    NASA Astrophysics Data System (ADS)

    Zhu, Lianqing; Wang, Zicai; Lin, Qian; Dong, Mingli

    2010-08-01

    In order to increase the speed of photoelectric conversion, a linear CCD is applied as the photoelectric converter instead of the traditional photodiode. A white LED is used as the light source of the system. The color information of the urine test strip is transferred into the CCD through a reflecting optical system. It is then converted to digital signals by an A/D converter. The test results of urine analysis are obtained by a data processing system. An ARM microprocessor is selected as the CPU of the system and a CPLD is employed to provide a driving timing for the CCD drive and the A/D converter. Active HDL7.2 and Verilog HDL are used to simulate the driving timing of the CPLD. Experimental results show that the correctness rate of the test results is better than 90%. The system satisfies the requirements of the color information collection of urine analyzer.

  5. Voice-Recognition System Records Inspection Data

    NASA Technical Reports Server (NTRS)

    Rochester, Larry L.

    1993-01-01

    Main Injector Voice Activated Record (MIVAR) system acts on vocal commands and processes spoken inspection data into electronic and printed inspection reports. Devised to improve acquisition and recording of data from borescope inspections of interiors of liquid-oxygen-injecting tubes on main engine of Space Shuttle. With modifications, system used in other situations to relieve inspectors of manual recording of data. Enhances flow of work and quality of data acquired by enabling inspector to remain visually focused on workpiece.

  6. Does Employee Recognition Affect Positive Psychological Functioning and Well-Being?

    PubMed

    Merino, M Dolores; Privado, Jesús

    2015-01-01

    Employee recognition is one of the typical characteristics of healthy organizations. The majority of research on recognition has studied the consequences of this variable on workers. But few investigations have focused on understanding what mechanisms mediate between recognition and its consequences. This work aims to understand whether the relationship between employee recognition and well-being, psychological resources mediate. To answer this question a sample of 1831 workers was used. The variables measured were: employee recognition, subjective well-being and positive psychological functioning (PPF), which consists of 11 psychological resources. In the analysis of data, structural equation models were applied. The results confirmed our hypothesis and showed that PPF mediate the relationship between recognition and well-being. The effect of recognition over PPF is two times greater (.39) with peer-recognition than with supervisor-recognition (.20), and, the effect of PPF over well-being is .59. This study highlights the importance of promoting employee recognition policies in organizations for the impact it has, not only on well-being, but also on the positive psychological functioning of the workers. PMID:26364645

  7. System integration of pattern recognition, adaptive aided, upper limb prostheses

    NASA Technical Reports Server (NTRS)

    Lyman, J.; Freedy, A.; Solomonow, M.

    1975-01-01

    The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.

  8. The advantages of stereo vision in a face recognition system

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng; Blasch, Erik

    2014-06-01

    Humans can recognize a face with binocular vision, while computers typically use a single face image. It is known that the performance of face recognition (by a computer) can be improved using the score fusion of multimodal images and multiple algorithms. A question is: Can we apply stereo vision to a face recognition system? We know that human binocular vision has many advantages such as stereopsis (3D vision), binocular summation, and singleness of vision including fusion of binocular images (cyclopean image). For face recognition, a 3D face or 3D facial features are typically computed from a pair of stereo images. In human visual processes, the binocular summation and singleness of vision are similar as image fusion processes. In this paper, we propose an advanced face recognition system with stereo imaging capability, which is comprised of two 2-in-1 multispectral (visible and thermal) cameras and three recognition algorithms (circular Gaussian filter, face pattern byte, and linear discriminant analysis [LDA]). Specifically, we present and compare stereo fusion at three levels (images, features, and scores) by using stereo images (from left camera and right camera). Image fusion is achieved with three methods (Laplacian pyramid, wavelet transform, average); feature fusion is done with three logical operations (AND, OR, XOR); and score fusion is implemented with four classifiers (LDA, k-nearest neighbor, support vector machine, binomial logical regression). The system performance is measured by probability of correct classification (PCC) rate (reported as accuracy rate in this paper) and false accept rate (FAR). The proposed approaches were validated with a multispectral stereo face dataset from 105 subjects. Experimental results show that any type of stereo fusion can improve the PCC, meanwhile reduce the FAR. It seems that stereo image/feature fusion is superior to stereo score fusion in terms of recognition performance. Further score fusion after image

  9. Training methodologies for dependent Speech Recognition (SR) systems

    NASA Astrophysics Data System (ADS)

    Miller, Richard L.

    1991-03-01

    An experiment was conducted to determine whether a dependent (SR) system would perform with different accuracies given different ways in which it was trained. The experiment used an SR system (Voice Navigator) which is based on Dragon Systems, Inc. (proprietary) technology. Fifteen subjects trained three different voice patterns each and conducted four tests to compile statistics about the recognition accuracy for each pattern. The experiment was successful and demonstrated that the training method used can have significant impact on the performance of a dependent SR system. This thesis discusses the research methodology, reviews and analyzes the data collected, and states conclusions drawn about the particular dependent SR system used in the experiment.

  10. Self-amplified optical pattern recognition system

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang (Inventor)

    1994-01-01

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

  11. A pattern recognition system for JPEG steganography detection

    NASA Astrophysics Data System (ADS)

    Chen, C. L. Philip; Chen, Mei-Ching; Agaian, Sos; Zhou, Yicong; Roy, Anuradha; Rodriguez, Benjamin M.

    2012-10-01

    This paper builds up a pattern recognition system to detect anomalies in JPEG images, especially steganographic content. The system consists of feature generation, feature ranking and selection, feature extraction, and pattern classification. These processes tend to capture image characteristics, reduce the problem dimensionality, eliminate the noise inferences between features, and further improve classification accuracies on clean and steganography JPEG images. Based on the discussion and analysis of six popular JPEG steganography methods, the entire recognition system results in higher classification accuracies between clean and steganography classes compared to merely using individual feature subset for JPEG steganography detection. The strength of feature combination and preprocessing has been integrated even when a small amount of information is embedded. The work demonstrated in this paper is extensible and can be improved by integrating various new and current techniques.

  12. Reaction Time of Facial Affect Recognition in Asperger's Disorder for Cartoon and Real, Static and Moving Faces

    ERIC Educational Resources Information Center

    Miyahara, Motohide; Bray, Anne; Tsujii, Masatsugu; Fujita, Chikako; Sugiyama, Toshiro

    2007-01-01

    This study used a choice reaction-time paradigm to test the perceived impairment of facial affect recognition in Asperger's disorder. Twenty teenagers with Asperger's disorder and 20 controls were compared with respect to the latency and accuracy of response to happy or disgusted facial expressions, presented in cartoon or real images and in…

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

    PubMed Central

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

    2014-01-01

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

  14. Callous-unemotional traits and empathy deficits: Mediating effects of affective perspective-taking and facial emotion recognition.

    PubMed

    Lui, Joyce H L; Barry, Christopher T; Sacco, Donald F

    2016-09-01

    Although empathy deficits are thought to be associated with callous-unemotional (CU) traits, findings remain equivocal and little is known about what specific abilities may underlie these purported deficits. Affective perspective-taking (APT) and facial emotion recognition may be implicated, given their independent associations with both empathy and CU traits. The current study examined how CU traits relate to cognitive and affective empathy and whether APT and facial emotion recognition mediate these relations. Participants were 103 adolescents (70 males) aged 16-18 attending a residential programme. CU traits were negatively associated with cognitive and affective empathy to a similar degree. The association between CU traits and affective empathy was partially mediated by APT. Results suggest that assessing mechanisms that may underlie empathic deficits, such as perspective-taking, may be important for youth with CU traits and may inform targets of intervention. PMID:26192073

  15. Speech recognition control system and method

    SciTech Connect

    Lemelson, J.H.

    1986-08-12

    This invention relates to a system and method for weighing articles and quantities of material wherein computing functions are performed to effect calculations and the control of a visual presentation means such as a display or printer or the generation of signals for use in recording a transaction. In particular, the invention relates to such a weighing and computing apparatus and method which operates or varies in response to speech signals generated by selected words of speech spoken into a microphone by an operator of the apparatus. It is known in the art to electronically detect the weight of articles and containers of material and to generate electrical signals which are indicative of such weight. It is also known to effect a computation with respect to such signals and additional signals generated by manually operating selected keys of a keyboard wherein the additional signals represent one or more additional variables which must be divided into or multiplied by the numerical representation of the weights of articles weighed by such apparatus.

  16. Cannula implantation into the lateral ventricle does not adversely affect recognition or spatial working memory.

    PubMed

    Seyer, Benjamin; Pham, Vi; Albiston, Anthony L; Chai, Siew Yeen

    2016-08-15

    Indwelling cannulas are often used to deliver pharmacological agents into the lateral ventricles of the brain to study their effects on memory and learning, yet little is known about the possible adverse effects of the cannulation itself. In this study, the effect of implanting an indwelling cannula into the right lateral ventricle was examined with respect to cognitive function and tissue damage in rats. Specifically, the cannula passed through sections of the primary motor (M1) and somatosensory hind limb (S1HL) cortices. One week following implantation, rats were impaired on the rotarod task, implying a deficit in fine motor control, likely caused by the passage of the cannula through the aforementioned cortical regions. Importantly, neither spatial working nor recognition memory was adversely affected. Histological examination showed immune cell activation only in the area immediately surrounding the cannulation site and not spreading to other brain regions. Both GFAP and CD-11b mRNA expression was elevated in the area immediately surrounding the cannulation site, but not in the contralateral hemisphere or the hippocampus. Neither of the inflammatory cytokines, TNF-α or IL-6, were upregulated in any region. These results show that cannulation into the lateral ventricle does not impair cognition and indicates that nootropic agents delivered via this method are enhancing normal memory rather than rescuing deficits caused by the surgery procedure. PMID:27345383

  17. Alteration of cuticular hydrocarbon composition affects heterospecific nestmate recognition in the carpenter ant Camponotus fellah

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nestmate recognition is a ubiquitous phenomenon in social insects as a means to prevent entry of undesired individuals aiming at exploiting the rich nest resources. The recognition cues in ants were shown in a few cases to be cuticular hydrocarbons, although there are a quite number of correlated as...

  18. Speech recognition systems on the Cell Broadband Engine

    SciTech Connect

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

    2007-04-20

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

  19. 3D Multi-Spectrum Sensor System with Face Recognition

    PubMed Central

    Kim, Joongrock; Yu, Sunjin; Kim, Ig-Jae; Lee, Sangyoun

    2013-01-01

    This paper presents a novel three-dimensional (3D) multi-spectrum sensor system, which combines a 3D depth sensor and multiple optical sensors for different wavelengths. Various image sensors, such as visible, infrared (IR) and 3D sensors, have been introduced into the commercial market. Since each sensor has its own advantages under various environmental conditions, the performance of an application depends highly on selecting the correct sensor or combination of sensors. In this paper, a sensor system, which we will refer to as a 3D multi-spectrum sensor system, which comprises three types of sensors, visible, thermal-IR and time-of-flight (ToF), is proposed. Since the proposed system integrates information from each sensor into one calibrated framework, the optimal sensor combination for an application can be easily selected, taking into account all combinations of sensors information. To demonstrate the effectiveness of the proposed system, a face recognition system with light and pose variation is designed. With the proposed sensor system, the optimal sensor combination, which provides new effectively fused features for a face recognition system, is obtained. PMID:24072025

  20. 3D multi-spectrum sensor system with face recognition.

    PubMed

    Kim, Joongrock; Yu, Sunjin; Kim, Ig-Jae; Lee, Sangyoun

    2013-01-01

    This paper presents a novel three-dimensional (3D) multi-spectrum sensor system, which combines a 3D depth sensor and multiple optical sensors for different wavelengths. Various image sensors, such as visible, infrared (IR) and 3D sensors, have been introduced into the commercial market. Since each sensor has its own advantages under various environmental conditions, the performance of an application depends highly on selecting the correct sensor or combination of sensors. In this paper, a sensor system, which we will refer to as a 3D multi-spectrum sensor system, which comprises three types of sensors, visible, thermal-IR and time-of-flight (ToF), is proposed. Since the proposed system integrates information from each sensor into one calibrated framework, the optimal sensor combination for an application can be easily selected, taking into account all combinations of sensors information. To demonstrate the effectiveness of the proposed system, a face recognition system with light and pose variation is designed. With the proposed sensor system, the optimal sensor combination, which provides new effectively fused features for a face recognition system, is obtained. PMID:24072025

  1. A Highly Accurate Face Recognition System Using Filtering Correlation

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Sayuri; Kodate, Kashiko

    2007-09-01

    The authors previously constructed a highly accurate fast face recognition optical correlator (FARCO) [E. Watanabe and K. Kodate: Opt. Rev. 12 (2005) 460], and subsequently developed an improved, super high-speed FARCO (S-FARCO), which is able to process several hundred thousand frames per second. The principal advantage of our new system is its wide applicability to any correlation scheme. Three different configurations were proposed, each depending on correlation speed. This paper describes and evaluates a software correlation filter. The face recognition function proved highly accurate, seeing that a low-resolution facial image size (64 × 64 pixels) has been successfully implemented. An operation speed of less than 10 ms was achieved using a personal computer with a central processing unit (CPU) of 3 GHz and 2 GB memory. When we applied the software correlation filter to a high-security cellular phone face recognition system, experiments on 30 female students over a period of three months yielded low error rates: 0% false acceptance rate and 2% false rejection rate. Therefore, the filtering correlation works effectively when applied to low resolution images such as web-based images or faces captured by a monitoring camera.

  2. Human activity recognition based on Evolving Fuzzy Systems.

    PubMed

    Iglesias, Jose Antonio; Angelov, Plamen; Ledezma, Agapito; Sanchis, Araceli

    2010-10-01

    Environments equipped with intelligent sensors can be of much help if they can recognize the actions or activities of their users. If this activity recognition is done automatically, it can be very useful for different tasks such as future action prediction, remote health monitoring, or interventions. Although there are several approaches for recognizing activities, most of them do not consider the changes in how a human performs a specific activity. We present an automated approach to recognize daily activities from the sensor readings of an intelligent home environment. However, as the way to perform an activity is usually not fixed but it changes and evolves, we propose an activity recognition method based on Evolving Fuzzy Systems. PMID:20945515

  3. Beyond species recognition: somatic state affects long-distance sex pheromone communication

    PubMed Central

    Chemnitz, Johanna; Jentschke, Petra C.; Ayasse, Manfred; Steiger, Sandra

    2015-01-01

    Long-range sex pheromones have been subjected to substantial research with a particular focus on their biosynthesis, peripheral perception, central processing and the resulting orientation behaviour of perceivers. Fundamental to the research on sex attractants was the assumption that they primarily coordinate species recognition. However, especially when they are produced by the less limiting sex (usually males), the evolution of heightened condition dependence might be expected and long-range sex pheromones might, therefore, also inform about a signaller's quality. Here we provide, to our knowledge, the first comprehensive study of the role of a male's long-range pheromone in mate choice that combines chemical analyses, video observations and field experiments with a multifactorial manipulation of males' condition. We show that the emission of the long-distance sex pheromone of the burying beetle, Nicrophorus vespilloides is highly condition-dependent and reliably reflects nutritional state, age, body size and parasite load—key components of an individual's somatic state. Both, the quantity and ratio of the pheromone components were affected but the time invested in pheromone emission was largely unaffected by a male's condition. Moreover, the variation in pheromone emission caused by the variation in condition had a strong effect on the attractiveness of males in the field, with males in better nutritional condition, of older age, larger body size and bearing less parasites being more attractive. That a single pheromone is influenced by so many aspects of the somatic state and causes such variation in a male's attractiveness under field conditions was hitherto unknown and highlights the need to integrate indicator models of sexual selection into pheromone research. PMID:26180067

  4. Beyond species recognition: somatic state affects long-distance sex pheromone communication.

    PubMed

    Chemnitz, Johanna; Jentschke, Petra C; Ayasse, Manfred; Steiger, Sandra

    2015-08-01

    Long-range sex pheromones have been subjected to substantial research with a particular focus on their biosynthesis, peripheral perception, central processing and the resulting orientation behaviour of perceivers. Fundamental to the research on sex attractants was the assumption that they primarily coordinate species recognition. However, especially when they are produced by the less limiting sex (usually males), the evolution of heightened condition dependence might be expected and long-range sex pheromones might, therefore, also inform about a signaller's quality. Here we provide, to our knowledge, the first comprehensive study of the role of a male's long-range pheromone in mate choice that combines chemical analyses, video observations and field experiments with a multifactorial manipulation of males' condition. We show that the emission of the long-distance sex pheromone of the burying beetle, Nicrophorus vespilloides is highly condition-dependent and reliably reflects nutritional state, age, body size and parasite load--key components of an individual's somatic state. Both, the quantity and ratio of the pheromone components were affected but the time invested in pheromone emission was largely unaffected by a male's condition. Moreover, the variation in pheromone emission caused by the variation in condition had a strong effect on the attractiveness of males in the field, with males in better nutritional condition, of older age, larger body size and bearing less parasites being more attractive. That a single pheromone is influenced by so many aspects of the somatic state and causes such variation in a male's attractiveness under field conditions was hitherto unknown and highlights the need to integrate indicator models of sexual selection into pheromone research. PMID:26180067

  5. How Does Adult Attachment Affect Human Recognition of Love-related and Sex-related Stimuli: An ERP Study.

    PubMed

    Hou, Juan; Chen, Xin; Liu, Jinqun; Yao, Fangshu; Huang, Jiani; Ndasauka, Yamikani; Ma, Ru; Zhang, Yuting; Lan, Jing; Liu, Lu; Fang, Xiaoyi

    2016-01-01

    In the present study, we investigated the relationship among three emotion-motivation systems (adult attachment, romantic love, and sex). We recorded event-related potentials in 37 healthy volunteers who had experienced romantic love while they viewed SEX, LOVE, FRIEND, SPORT, and NEUTRAL images. We also measured adult attachment styles, level of passionate love and sexual attitudes. As expected, results showed that, firstly, response to love-related image-stimuli and sex-related image-stimuli on the electrophysiological data significantly different on N1, N2, and positive slow wave (PSW) components. Secondly, the different adult attachment styles affected individuals' recognition processing in response to love-related and sex-related images, especially, to sex-related images. Further analysis showed that voltages elicited by fearful attachment style individuals were significantly lower than voltages elicited by secure and dismissing attachment style individuals on sex-related images at frontal sites, on N1 and N2 components. Thirdly, from behavior data, we found that adult attachment styles were not significantly related to any dimension of sexual attitudes but were significantly related to passionate love scale (PLS) total points. Thus, the behavior results were not in line with the electrophysiological results. The present study proved that adult attachment styles might mediate individuals' lust and attraction systems. PMID:27199830

  6. How Does Adult Attachment Affect Human Recognition of Love-related and Sex-related Stimuli: An ERP Study

    PubMed Central

    Hou, Juan; Chen, Xin; Liu, Jinqun; Yao, Fangshu; Huang, Jiani; Ndasauka, Yamikani; Ma, Ru; Zhang, Yuting; Lan, Jing; Liu, Lu; Fang, Xiaoyi

    2016-01-01

    In the present study, we investigated the relationship among three emotion-motivation systems (adult attachment, romantic love, and sex). We recorded event-related potentials in 37 healthy volunteers who had experienced romantic love while they viewed SEX, LOVE, FRIEND, SPORT, and NEUTRAL images. We also measured adult attachment styles, level of passionate love and sexual attitudes. As expected, results showed that, firstly, response to love-related image-stimuli and sex-related image-stimuli on the electrophysiological data significantly different on N1, N2, and positive slow wave (PSW) components. Secondly, the different adult attachment styles affected individuals’ recognition processing in response to love-related and sex-related images, especially, to sex-related images. Further analysis showed that voltages elicited by fearful attachment style individuals were significantly lower than voltages elicited by secure and dismissing attachment style individuals on sex-related images at frontal sites, on N1 and N2 components. Thirdly, from behavior data, we found that adult attachment styles were not significantly related to any dimension of sexual attitudes but were significantly related to passionate love scale (PLS) total points. Thus, the behavior results were not in line with the electrophysiological results. The present study proved that adult attachment styles might mediate individuals’ lust and attraction systems. PMID:27199830

  7. Experimental modulation of external microbiome affects nestmate recognition in harvester ants (Pogonomyrmex barbatus).

    PubMed

    Dosmann, Andy; Bahet, Nassim; Gordon, Deborah M

    2016-01-01

    Social insects use odors as cues for a variety of behavioral responses, including nestmate recognition. Past research on nestmate recognition indicates cuticular hydrocarbons are important nestmate discriminators for social insects, but other factors are likely to contribute to colony-specific odors. Here we experimentally tested whether external microbes contribute to nestmate recognition in red harvester ants (Pogonomyrmex barbatus). We changed the external microbiome of ants through topical application of either antibiotics or microbial cultures. We then observed behavior of nestmates when treated ants were returned to the nest. Ants whose external microbiome was augmented with microbial cultures were much more likely to be rejected than controls, but ants treated with antibiotics were not. This result is consistent with the possibility that external microbes are used for nestmate recognition. PMID:26855857

  8. Experimental modulation of external microbiome affects nestmate recognition in harvester ants (Pogonomyrmex barbatus)

    PubMed Central

    Bahet, Nassim; Gordon, Deborah M.

    2016-01-01

    Social insects use odors as cues for a variety of behavioral responses, including nestmate recognition. Past research on nestmate recognition indicates cuticular hydrocarbons are important nestmate discriminators for social insects, but other factors are likely to contribute to colony-specific odors. Here we experimentally tested whether external microbes contribute to nestmate recognition in red harvester ants (Pogonomyrmex barbatus). We changed the external microbiome of ants through topical application of either antibiotics or microbial cultures. We then observed behavior of nestmates when treated ants were returned to the nest. Ants whose external microbiome was augmented with microbial cultures were much more likely to be rejected than controls, but ants treated with antibiotics were not. This result is consistent with the possibility that external microbes are used for nestmate recognition. PMID:26855857

  9. A Spiking Neural Network System for Robust Sequence Recognition.

    PubMed

    Yu, Qiang; Yan, Rui; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

    2016-03-01

    This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software. PMID:25879976

  10. Subthalamic nucleus stimulation affects orbitofrontal cortex in facial emotion recognition: a pet study

    PubMed Central

    Le Jeune, F.; Péron, J.; Biseul, I.; Fournier, S.; Sauleau, P.; Drapier, S.; Haegelen, C.; Drapier, D.; Millet, B.; Garin, E.; Herry, J.-Y.; Malbert, C.-H.

    2008-01-01

    Deep brain stimulation (DBS) of the bilateral subthalamic nucleus (STN) in Parkinson's disease is thought to produce adverse events such as emotional disorders, and in a recent study, we found fear recognition to be impaired as a result. These changes have been attributed to disturbance of the STN's limbic territory and would appear to confirm that the negative emotion recognition network passes through the STN. In addition, it is now widely acknowledged that damage to the orbitofrontal cortex (OFC), especially the right side, can result in impaired recognition of facial emotions (RFE). In this context, we hypothesized that this reduced recognition of fear is correlated with modifications in the cerebral glucose metabolism of the right OFC. The objective of the present study was first, to reinforce our previous results by demonstrating reduced fear recognition in our Parkinson's disease patient group following STN DBS and, second, to correlate these emotional performances with glucose metabolism using 18FDG-PET. The 18FDG-PET and RFE tasks were both performed by a cohort of 13 Parkinson's disease patients 3 months before and 3 months after surgery for STN DBS. As predicted, we observed a significant reduction in fear recognition following surgery and obtained a positive correlation between these neuropsychological results and changes in glucose metabolism, especially in the right OFC. These results confirm the role of the STN as a key basal ganglia structure in limbic circuits. PMID:18490359

  11. Comparative performance between human and automated face recognition systems, using CCTV imagery, different compression levels and scene parameters

    NASA Astrophysics Data System (ADS)

    Tsifouti, A.; Triantaphillidou, S.; Larabi, M.-C.; Bilissi, E.; Psarrou, A.

    2015-01-01

    In this investigation we identify relationships between human and automated face recognition systems with respect to compression. Further, we identify the most influential scene parameters on the performance of each recognition system. The work includes testing of the systems with compressed Closed-Circuit Television (CCTV) footage, consisting of quantified scene (footage) parameters. Parameters describe the content of scenes concerning camera to subject distance, facial angle, scene brightness, and spatio-temporal busyness. These parameters have been previously shown to affect the human visibility of useful facial information, but not much work has been carried out to assess the influence they have on automated recognition systems. In this investigation, the methodology previously employed in the human investigation is adopted, to assess performance of three different automated systems: Principal Component Analysis, Linear Discriminant Analysis, and Kernel Fisher Analysis. Results show that the automated systems are more tolerant to compression than humans. In automated systems, mixed brightness scenes were the most affected and low brightness scenes were the least affected by compression. In contrast for humans, low brightness scenes were the most affected and medium brightness scenes the least affected. Findings have the potential to broaden the methods used for testing imaging systems for security applications.

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Irhebhude, Martins E.; Edirisinghe, Eran A.

    2014-06-01

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

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

    PubMed Central

    Shin, Yong-Nyuo; Kim, Jason; Lee, Yong-Jun; Shin, Woochang; Choi, Jin-Young

    2008-01-01

    Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process. PMID:18317524

  15. Detection of prosodics by using a speech recognition system

    NASA Astrophysics Data System (ADS)

    Hupp, N. A.

    1991-07-01

    The problem was to determine the ability of a speech recognizer to extract prosodic speech features, such as pitch and stress, and to examine these features for application to future voice recognition systems. The Speech Systems Incorporated (SSI) speech recognizer demonstrated that it could detect prosodic features and that these features do indicate the word and/or syllable that is stressed by the speaker. The research examined the effect of prosodics, such as pitch, amplitude, and duration, on word and syllable stress by using the SSI. Subjects read phases and sentences, using a given intonation and stress. The three sections of the experiment compared questions and answers, words stressed within a sentence, and noun/verb pairs, such as object and subject. The results were analyzed both on the syllable level and the word level. In all cases, there was a significant increase in pitch, amplitude, and duration when comparing stressed words and syllables to unstressed words and syllables. When comparing unstressed words only, it was also noted that the first word in a sentence has an increase in pitch, amplitude, and duration. The threshold could be set in recognition systems for each of these parameters. Current speech recognizers do not use acoustic data above the word level. This research shows that we have the capability of developing better speech systems by incorporating prosodics with new linguistic software.

  16. Electronic system with memristive synapses for pattern recognition

    PubMed Central

    Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-geun

    2015-01-01

    Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction. PMID:25941950

  17. Electronic system with memristive synapses for pattern recognition

    NASA Astrophysics Data System (ADS)

    Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-Geun

    2015-05-01

    Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction.

  18. Electronic system with memristive synapses for pattern recognition.

    PubMed

    Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-geun

    2015-01-01

    Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction. PMID:25941950

  19. Named entity recognition for bacterial Type IV secretion systems.

    PubMed

    Ananiadou, Sophia; Sullivan, Dan; Black, William; Levow, Gina-Anne; Gillespie, Joseph J; Mao, Chunhong; Pyysalo, Sampo; Kolluru, Balakrishna; Tsujii, Junichi; Sobral, Bruno

    2011-01-01

    Research on specialized biological systems is often hampered by a lack of consistent terminology, especially across species. In bacterial Type IV secretion systems genes within one set of orthologs may have over a dozen different names. Classifying research publications based on biological processes, cellular components, molecular functions, and microorganism species should improve the precision and recall of literature searches allowing researchers to keep up with the exponentially growing literature, through resources such as the Pathosystems Resource Integration Center (PATRIC, patricbrc.org). We developed named entity recognition (NER) tools for four entities related to Type IV secretion systems: 1) bacteria names, 2) biological processes, 3) molecular functions, and 4) cellular components. These four entities are important to pathogenesis and virulence research but have received less attention than other entities, e.g., genes and proteins. Based on an annotated corpus, large domain terminological resources, and machine learning techniques, we developed recognizers for these entities. High accuracy rates (>80%) are achieved for bacteria, biological processes, and molecular function. Contrastive experiments highlighted the effectiveness of alternate recognition strategies; results of term extraction on contrasting document sets demonstrated the utility of these classes for identifying T4SS-related documents. PMID:21468321

  20. Learning and plan refinement in a knowledge-based system for automatic speech recognition

    SciTech Connect

    De Mori, R.; Lam, L.; Gilloux, M.

    1987-03-01

    This paper shows how a semiautomatic design of a speech recognition system can be done as a planning activity. Recognition performances are used for deciding plan refinement. Inductive learning is performed for setting action preconditions. Experimental results in the recognition of connected letters spoken by 100 speakers are presented.

  1. Document Retrieval Systems; Factors Affecting Search Time.

    ERIC Educational Resources Information Center

    Montgomery, K. Leon, Ed.

    An experiment was conducted to identify some of the important parameters affecting search time, a critical cost factor in retrieval systems. Using actual computer searches of Chemical Abstracts Condensate, a comparison was made between the effectiveness of linear and inverted filing systems. Since the results indicated that it was the type and…

  2. A speech recognition system based on hybrid wavelet network including a fuzzy decision support system

    NASA Astrophysics Data System (ADS)

    Jemai, Olfa; Ejbali, Ridha; Zaied, Mourad; Ben Amar, Chokri

    2015-02-01

    This paper aims at developing a novel approach for speech recognition based on wavelet network learnt by fast wavelet transform (FWN) including a fuzzy decision support system (FDSS). Our contributions reside in, first, proposing a novel learning algorithm for speech recognition based on the fast wavelet transform (FWT) which has many advantages compared to other algorithms and in which major problems of the previous works to compute connection weights were solved. They were determined by a direct solution which requires computing matrix inversion, which may be intensive. However, the new algorithm was realized by the iterative application of FWT to compute connection weights. Second, proposing a new classification way for this speech recognition system. It operated a human reasoning mode employing a FDSS to compute similarity degrees between test and training signals. Extensive empirical experiments were conducted to compare the proposed approach with other approaches. Obtained results show that the new speech recognition system has a better performance than previously established ones.

  3. Development of the hidden Markov models based Lithuanian speech recognition system

    NASA Astrophysics Data System (ADS)

    Ringeliene, Z.; Lipeika, A.

    2010-09-01

    The paper presents a prototype of the speaker-independent Lithuanian isolated word recognition system. The system is based on the hidden Markov models, a powerful statistical method for modeling speech signals. The prototype system can be used for Lithuanian words recognition investigations and is a good starting point for the development of a more sophisticated recognition system. The system graphical user interface is easy to control. Visualization of the entire recognition process is useful for analyzing of the recognition results. Based on this recognizer, a system for Web browser control by voice was developed. The program, which implements control by voice commands, was integrated in the speech recognition system. The system performance was evaluated by using different sets of acoustic models and vocabularies.

  4. Syllables and Bigrams: Orthographic Redundancy and Syllabic Units Affect Visual Word Recognition at Different Processing Levels

    ERIC Educational Resources Information Center

    Conrad, Markus; Carreiras, Manuel; Tamm, Sascha; Jacobs, Arthur M.

    2009-01-01

    Over the last decade, there has been increasing evidence for syllabic processing during visual word recognition. If syllabic effects prove to be independent from orthographic redundancy, this would seriously challenge the ability of current computational models to account for the processing of polysyllabic words. Three experiments are presented to…

  5. How Do Professional Mutual Recognition Agreements Affect Higher Education? Examining Regional Policy in North America

    ERIC Educational Resources Information Center

    Sa, Creso; Gaviria, Patricia

    2011-01-01

    Professional mutual recognition agreements (MRAs) are one of the policy instruments employed in global and regional trade agreements to facilitate the mobility of skilled labour. While such agreements have been noted in the literature examining cross-border academic mobility, little is known about how they impact higher education. This paper…

  6. Orientation and Affective Expression Effects on Face Recognition in Williams Syndrome and Autism

    ERIC Educational Resources Information Center

    Rose, Fredric E.; Lincoln, Alan J.; Lai, Zona; Ene, Michaela; Searcy, Yvonne M.; Bellugi, Ursula

    2007-01-01

    We sought to clarify the nature of the face processing strength commonly observed in individuals with Williams syndrome (WS) by comparing the face recognition ability of persons with WS to that of persons with autism and to healthy controls under three conditions: Upright faces with neutral expressions, upright faces with varying affective…

  7. Collocation and Pattern Recognition Effects on System Failure Remediation

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.; Press, Hayes N.

    2007-01-01

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

  8. Mapping parahippocampal systems for recognition and recency memory in the absence of the rat hippocampus

    PubMed Central

    Kinnavane, L; Amin, E; Horne, M; Aggleton, J P

    2014-01-01

    The present study examined immediate-early gene expression in the perirhinal cortex of rats with hippocampal lesions. The goal was to test those models of recognition memory which assume that the perirhinal cortex can function independently of the hippocampus. The c-fos gene was targeted, as its expression in the perirhinal cortex is strongly associated with recognition memory. Four groups of rats were examined. Rats with hippocampal lesions and their surgical controls were given either a recognition memory task (novel vs. familiar objects) or a relative recency task (objects with differing degrees of familiarity). Perirhinal Fos expression in the hippocampal-lesioned groups correlated with both recognition and recency performance. The hippocampal lesions, however, had no apparent effect on overall levels of perirhinal or entorhinal cortex c-fos expression in response to novel objects, with only restricted effects being seen in the recency condition. Network analyses showed that whereas the patterns of parahippocampal interactions were differentially affected by novel or familiar objects, these correlated networks were not altered by hippocampal lesions. Additional analyses in control rats revealed two modes of correlated medial temporal activation. Novel stimuli recruited the pathway from the lateral entorhinal cortex (cortical layer II or III) to hippocampal field CA3, and thence to CA1. Familiar stimuli recruited the direct pathway from the lateral entorhinal cortex (principally layer III) to CA1. The present findings not only reveal the independence from the hippocampus of some perirhinal systems associated with recognition memory, but also show how novel stimuli engage hippocampal subfields in qualitatively different ways from familiar stimuli. PMID:25264133

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

    PubMed

    Fachinger, Uwe; Schöpke, Birte

    2014-01-01

    AAL systems require, in addition to sophisticated and reliable technology, adequate business models for their launch and sustainable establishment. This paper presents the basic features of alternative business models for a sensor-based fall recognition system which was developed within the context of the "Lower Saxony Research Network Design of Environments for Ageing" (GAL). The models were developed parallel to the R&D process with successive adaptation and concretization. An overview of the basic features (i.e. nine partial models) of the business model is given and the mutual exclusive alternatives for each partial model are presented. The partial models are interconnected and the combinations of compatible alternatives lead to consistent alternative business models. However, in the current state, only initial concepts of alternative business models can be deduced. The next step will be to gather additional information to work out more detailed models. PMID:25148563

  10. Pattern-Recognition System for Approaching a Known Target

    NASA Technical Reports Server (NTRS)

    Huntsberger, Terrance; Cheng, Yang

    2008-01-01

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

  11. Non-conscious recognition of affect in the absence of striate cortex.

    PubMed

    de Gelder, B; Vroomen, J; Pourtois, G; Weiskrantz, L

    1999-12-16

    Functional neuroimaging experiments have shown that recognition of emotional expressions does not depend on awareness of visual stimuli and that unseen fear stimuli can activate the amygdala via a colliculopulvinar pathway. Perception of emotional expressions in the absence of awareness in normal subjects has some similarities with the unconscious recognition of visual stimuli which is well documented in patients with striate cortex lesions (blindsight). Presumably in these patients residual vision engages alternative extra-striate routes such as the superior colliculus and pulvinar. Against this background, we conjectured that a blindsight subject (GY) might recognize facial expressions presented in his blind field. The present study now provides direct evidence for this claim. PMID:10716205

  12. A Diffusion Model Analysis of Decision Biases Affecting Delayed Recognition of Emotional Stimuli

    PubMed Central

    Bowen, Holly J.; Spaniol, Julia; Patel, Ronak; Voss, Andreas

    2016-01-01

    Previous empirical work suggests that emotion can influence accuracy and cognitive biases underlying recognition memory, depending on the experimental conditions. The current study examines the effects of arousal and valence on delayed recognition memory using the diffusion model, which allows the separation of two decision biases thought to underlie memory: response bias and memory bias. Memory bias has not been given much attention in the literature but can provide insight into the retrieval dynamics of emotion modulated memory. Participants viewed emotional pictorial stimuli; half were given a recognition test 1-day later and the other half 7-days later. Analyses revealed that emotional valence generally evokes liberal responding, whereas high arousal evokes liberal responding only at a short retention interval. The memory bias analyses indicated that participants experienced greater familiarity with high-arousal compared to low-arousal items and this pattern became more pronounced as study-test lag increased; positive items evoke greater familiarity compared to negative and this pattern remained stable across retention interval. The findings provide insight into the separate contributions of valence and arousal to the cognitive mechanisms underlying delayed emotion modulated memory. PMID:26784108

  13. Selective attention affects conceptual object priming and recognition: a study with young and older adults.

    PubMed

    Ballesteros, Soledad; Mayas, Julia

    2014-01-01

    In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old-new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/artificial speeded conceptual classification task with repeated attended, repeated unattended, and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classify them as natural or artificial. After the encoding phase, they performed an old-new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults. PMID:25628588

  14. Selective attention affects conceptual object priming and recognition: a study with young and older adults

    PubMed Central

    Ballesteros, Soledad; Mayas, Julia

    2015-01-01

    In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old–new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/artificial speeded conceptual classification task with repeated attended, repeated unattended, and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classify them as natural or artificial. After the encoding phase, they performed an old–new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults. PMID:25628588

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

    SciTech Connect

    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.

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

    PubMed

    Ren, Bo; Dong, Hai; Ramström, Olof

    2014-05-01

    A carbohydrate-anion recognition system in nonpolar solvents is reported, in which complexes form at the B-faces of β-D-pyranosides with H1-, H3-, and H5-cis patterns similar to carbohydrate-π interactions. The complexation effect was evaluated for a range of carbohydrate structures; it resulted in either 1:1 carbohydrate-anion complexes, or 1:2 complex formation depending on the protection pattern of the carbohydrate. The interaction was also evaluated with different anions and solvents. In both cases it resulted in significant binding differences. The results indicate that complexation originates from van der Waals interactions or weak CH⋅⋅⋅A(-) hydrogen bonds between the binding partners and is related to electron-withdrawing groups of the carbohydrates as well as increased hydrogen-bond-accepting capability of the anions. PMID:24616327

  17. A Primitive-Based 3D Object Recognition System

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.

    1988-08-01

    A knowledge-based 3D object recognition system has been developed. The system uses the hierarchical structural, geometrical and relational knowledge in matching the 3D object models to the image data through pre-defined primitives. The primitives, we have selected, to begin with, are 3D boxes, cylinders, and spheres. These primitives as viewed from different angles covering complete 3D rotation range are stored in a "Primitive-Viewing Knowledge-Base" in form of hierarchical structural and relational graphs. The knowledge-based system then hypothesizes about the viewing angle and decomposes the segmented image data into valid primitives. A rough 3D structural and relational description is made on the basis of recognized 3D primitives. This description is now used in the detailed high-level frame-based structural and relational matching. The system has several expert and knowledge-based systems working in both stand-alone and cooperative modes to provide multi-level processing. This multi-level processing utilizes both bottom-up (data-driven) and top-down (model-driven) approaches in order to acquire sufficient knowledge to accept or reject any hypothesis for matching or recognizing the objects in the given image.

  18. FaceID: A face detection and recognition system

    SciTech Connect

    Shah, M.B.; Rao, N.S.V.; Olman, V.; Uberbacher, E.C.; Mann, R.C.

    1996-12-31

    A face detection system that automatically locates faces in gray-level images is described. Also described is a system which matches a given face image with faces in a database. Face detection in an Image is performed by template matching using templates derived from a selected set of normalized faces. Instead of using original gray level images, vertical gradient images were calculated and used to make the system more robust against variations in lighting conditions and skin color. Faces of different sizes are detected by processing the image at several scales. Further, a coarse-to-fine strategy is used to speed up the processing, and a combination of whole face and face component templates are used to ensure low false detection rates. The input to the face recognition system is a normalized vertical gradient image of a face, which is compared against a database using a set of pretrained feedforward neural networks with a winner-take-all fuser. The training is performed by using an adaptation of the backpropagation algorithm. This system has been developed and tested using images from the FERET database and a set of images obtained from Rowley, et al and Sung and Poggio.

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

    NASA Technical Reports Server (NTRS)

    Houck, J. A.

    1982-01-01

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

  20. Biased Recognition of Facial Affect in Patients with Major Depressive Disorder Reflects Clinical State

    PubMed Central

    Münkler, Paula; Rothkirch, Marcus; Dalati, Yasmin; Schmack, Katharina; Sterzer, Philipp

    2015-01-01

    Cognitive theories of depression posit that perception is negatively biased in depressive disorder. Previous studies have provided empirical evidence for this notion, but left open the question whether the negative perceptual bias reflects a stable trait or the current depressive state. Here we investigated the stability of negatively biased perception over time. Emotion perception was examined in patients with major depressive disorder (MDD) and healthy control participants in two experiments. In the first experiment subjective biases in the recognition of facial emotional expressions were assessed. Participants were presented with faces that were morphed between sad and neutral and happy expressions and had to decide whether the face was sad or happy. The second experiment assessed automatic emotion processing by measuring the potency of emotional faces to gain access to awareness using interocular suppression. A follow-up investigation using the same tests was performed three months later. In the emotion recognition task, patients with major depression showed a shift in the criterion for the differentiation between sad and happy faces: In comparison to healthy controls, patients with MDD required a greater intensity of the happy expression to recognize a face as happy. After three months, this negative perceptual bias was reduced in comparison to the control group. The reduction in negative perceptual bias correlated with the reduction of depressive symptoms. In contrast to previous work, we found no evidence for preferential access to awareness of sad vs. happy faces. Taken together, our results indicate that MDD-related perceptual biases in emotion recognition reflect the current clinical state rather than a stable depressive trait. PMID:26039710

  1. Biased recognition of facial affect in patients with major depressive disorder reflects clinical state.

    PubMed

    Münkler, Paula; Rothkirch, Marcus; Dalati, Yasmin; Schmack, Katharina; Sterzer, Philipp

    2015-01-01

    Cognitive theories of depression posit that perception is negatively biased in depressive disorder. Previous studies have provided empirical evidence for this notion, but left open the question whether the negative perceptual bias reflects a stable trait or the current depressive state. Here we investigated the stability of negatively biased perception over time. Emotion perception was examined in patients with major depressive disorder (MDD) and healthy control participants in two experiments. In the first experiment subjective biases in the recognition of facial emotional expressions were assessed. Participants were presented with faces that were morphed between sad and neutral and happy expressions and had to decide whether the face was sad or happy. The second experiment assessed automatic emotion processing by measuring the potency of emotional faces to gain access to awareness using interocular suppression. A follow-up investigation using the same tests was performed three months later. In the emotion recognition task, patients with major depression showed a shift in the criterion for the differentiation between sad and happy faces: In comparison to healthy controls, patients with MDD required a greater intensity of the happy expression to recognize a face as happy. After three months, this negative perceptual bias was reduced in comparison to the control group. The reduction in negative perceptual bias correlated with the reduction of depressive symptoms. In contrast to previous work, we found no evidence for preferential access to awareness of sad vs. happy faces. Taken together, our results indicate that MDD-related perceptual biases in emotion recognition reflect the current clinical state rather than a stable depressive trait. PMID:26039710

  2. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 2 2012-10-01 2012-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES... Reimbursement Control Systems § 403.322 Termination of agreements for Medicare recognition of State systems....

  3. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 2 2013-10-01 2013-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES... Reimbursement Control Systems § 403.322 Termination of agreements for Medicare recognition of State systems....

  4. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 2 2011-10-01 2011-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES... Reimbursement Control Systems § 403.322 Termination of agreements for Medicare recognition of State systems....

  5. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Code of Federal Regulations, 2010 CFR

    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... Reimbursement Control Systems § 403.322 Termination of agreements for Medicare recognition of State systems....

  6. 42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 2 2014-10-01 2014-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES... Reimbursement Control Systems § 403.322 Termination of agreements for Medicare recognition of State systems....

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

    NASA Astrophysics Data System (ADS)

    Dux, David Lee

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

  8. Walking intrusion signal recognition method for fiber fence system

    NASA Astrophysics Data System (ADS)

    Fang, Nian; Wang, Lutang; Jia, Dongjian; Shan, Chao; Huang, Zhaoming

    2009-11-01

    A recognition method based on the gait characteristic for walking intrusion signal is presented. The gait characteristic of a normal walker in the nature state is an average gait period of 1.2s, in which a step period is about 0.6s and a foot touchdown time is about 0.2s. When a person walks fast or runs, the step period is reduced to about 0.4s and the foot touchdown time still keeps about 0.2s. It is included in the vibration signal caused by a walking intruder inevitably. So the detection system output signal caused by a human intrusion is intermittent and periodical. If a sensing system output waveform has a period of 0.3-0.75s and a duration time of 0.15-0.25s, the disturbance source can be adjudged as a human intrusion, not as an animal or other random one. The effectiveness of the proposed method is verified by the experimental results with an in-line Sagnac interferometer fiber fence system and a φ-OTDR intrusion detection system, respectively.

  9. Degenerative disease affecting the nervous system.

    PubMed

    Eadie, M J

    1974-03-01

    The term "degenerative disease" is one which is rather widely used in relation to the nervous system and yet one which is rarely formally and carefully defined. The term appears to be applied to disorders of the nervous system which often occur in later life and which are of uncertain cause. In the Shorter Oxford Dictionary the word degeneration is defined as "a change of structure by which an organism, or an organ, assumes the form of a lower type". However this is not quite the sense in which the word is applied in human neuropathology, where it is conventional to restrict the use of the word to those organic disorders which are of uncertain or poorly understood cause and in which there is a deterioration or regression in the level of functioning of the nervous system. The concept of degenerative disorder is applied to other organs as well as to the brain, and as disease elsewhere in the body may affect the nervous system, it seems reasonable to include within the topic of degenerative disorder affecting the nervous system those conditions in which the nervous system is involved as a result of primary degenerations in other parts of the body. PMID:25026144

  10. Vermont STep Ahead Recognition System: QRS Profile. The Child Care Quality Rating System (QRS) Assessment

    ERIC Educational Resources Information Center

    Child Trends, 2010

    2010-01-01

    This paper presents a profile of Vermont's STep Ahead Recognition System (STARS) prepared as part of the Child Care Quality Rating System (QRS) Assessment Study. The profile consists of several sections and their corresponding descriptions including: (1) Program Information; (2) Rating Details; (3) Quality Indicators for All Child Care Programs;…

  11. Facial affect recognition performance and event-related potentials in violent and non-violent schizophrenia patients.

    PubMed

    Frommann, Nicole; Stroth, Sanna; Brinkmeyer, Jürgen; Wölwer, Wolfgang; Luckhaus, Christian

    2013-01-01

    We investigated whether male inpatients with schizophrenia and a history of hands-on violent offences (forensic schizophrenic, FOS) are more impaired in emotion recognition than matched schizophrenia patients without any history of violence (general psychiatric schizophrenic, GPS). This should become apparent in performance in psychometry and in scalp event-related brain potentials (ERPs) evoked by pictures of facial affect. FOS and GPS (each n = 19) were matched concerning age, intelligence, comorbid addiction, medication and illness duration. FOS revealed significantly poorer affect recognition (AR) performance, especially of neutral and fear stimuli. Analysis of ERPs revealed a significant interaction of hemisphere, electrode position and group of the N250 component. Post hoc analysis of group effect showed significantly larger amplitudes in FOS at FC3. These results support the hypothesis that in FOS emotional faces are more salient and evoke higher arousal. Larger impairment in AR performance combined with higher salience and arousal may contribute to the occurrence of violent acts in schizophrenia patients. PMID:24051542

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

    PubMed Central

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

    2015-01-01

    Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands. PMID:26184214

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

    PubMed

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

    2015-01-01

    Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands. PMID:26184214

  14. Encoding strategy affects false recall and recognition: Evidence from categorical study material

    PubMed Central

    Olszewska, Justyna; Ulatowska, Joanna

    2013-01-01

    The present research investigated memory vulnerability to distortions. Different encoding strategies were used when categorized lists were studied. The authors assumed that an imagery strategy would be responsible for decreasing false memories more than a word-whispering strategy, which is consistent with the model of semantic access and previous research in the Deese-Roediger-McDermott paradigm (the DRM paradigm; Deese, 1959; Roediger & McDermott, 1995). A normative study of category lists and 4 experiments were conducted to verify the memory vulnerability to different encoding strategies (imagery, word-whispering, control). Half of subjects recalled and half recognized previously studied words. The results revealed a marked reduction in false recognition and recall after imagery encoding, relative to after word-whispering encoding. PMID:23717349

  15. Feeling backwards? How temporal order in speech affects the time course of vocal emotion recognition

    PubMed Central

    Rigoulot, Simon; Wassiliwizky, Eugen; Pell, Marc D.

    2013-01-01

    Recent studies suggest that the time course for recognizing vocal expressions of basic emotion in speech varies significantly by emotion type, implying that listeners uncover acoustic evidence about emotions at different rates in speech (e.g., fear is recognized most quickly whereas happiness and disgust are recognized relatively slowly; Pell and Kotz, 2011). To investigate whether vocal emotion recognition is largely dictated by the amount of time listeners are exposed to speech or the position of critical emotional cues in the utterance, 40 English participants judged the meaning of emotionally-inflected pseudo-utterances presented in a gating paradigm, where utterances were gated as a function of their syllable structure in segments of increasing duration from the end of the utterance (i.e., gated syllable-by-syllable from the offset rather than the onset of the stimulus). Accuracy for detecting six target emotions in each gate condition and the mean identification point for each emotion in milliseconds were analyzed and compared to results from Pell and Kotz (2011). We again found significant emotion-specific differences in the time needed to accurately recognize emotions from speech prosody, and new evidence that utterance-final syllables tended to facilitate listeners' accuracy in many conditions when compared to utterance-initial syllables. The time needed to recognize fear, anger, sadness, and neutral from speech cues was not influenced by how utterances were gated, although happiness and disgust were recognized significantly faster when listeners heard the end of utterances first. Our data provide new clues about the relative time course for recognizing vocally-expressed emotions within the 400–1200 ms time window, while highlighting that emotion recognition from prosody can be shaped by the temporal properties of speech. PMID:23805115

  16. Factors Affecting Open-Set Word Recognition in Adults with Cochlear Implants

    PubMed Central

    Holden, Laura K.; Finley, Charles C.; Firszt, Jill B.; Holden, Timothy A.; Brenner, Christine; Potts, Lisa G.; Gotter, Brenda D.; Vanderhoof, Sallie S.; Mispagel, Karen; Heydebrand, Gitry; Skinner, Margaret W.

    2012-01-01

    A monosyllabic word test was administered to 114 postlingually-deaf adult cochlear implant (CI) recipients at numerous intervals from two weeks to two years post-initial CI activation. Biographic/audiologic information, electrode position, and cognitive ability were examined to determine factors affecting CI outcomes. Results revealed that Duration of Severe-to-Profound Hearing Loss, Age at Implantation, CI Sound-field Threshold Levels, Percentage of Electrodes in Scala Vestibuli, Medio-lateral Electrode Position, Insertion Depth, and Cognition were among the factors that affected performance. Knowledge of how factors affect performance can influence counseling, device fitting, and rehabilitation for patients and may contribute to improved device design. PMID:23348845

  17. Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems

    NASA Technical Reports Server (NTRS)

    Ye, Sherry

    2015-01-01

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

  18. [Research on Anti-Camouflaged Target System Based on Spectral Detection and Image Recognition].

    PubMed

    Wang, Bo; Gao, Yu-bin; Lu, Xu-tao

    2015-05-01

    To be able to quickly and efficiently identify Enemy camouflaged maneuvering targets in the wild environment, target recognition system was designed based on spectral detection technology and video target recognition method. System was composed of the visible light image acquisition module and static interferometer module. The system used image recognition technology to obtain two dimensional video images of measurement region, and through spectrum detection technology to identify targets. Ultimately, measured target was rebuilt on the corresponding position in the image, so the visual target recognition was realized. After the theoretical derivation, identifiable target function formula of the system was obtained, and based on the functional relationship to complete the quantitative experiments for target recognition. In the experiments, maneuvering target in the battlefield environment was simulated by a car. At different distances, the background was respectively selected to detect a flat wasteland, bushes and abandoned buildings. Obvious target, coated camouflage target and covered disguises target was respectively spectrum detection. Experimental results show that spectrum detection technology can overcome the shortcomings of unrecognized the camouflaged target by traditional image target recognition method. Testing background had some influence on spectrum detection results, and the continuity of the background was conducive to target recognition. Covered disguises target was the hardest to identify in various camouflage mode. As the distance between the target and the system increases, signal to noise ratio of the system was reduced. In summary, the system can achieve effective recognition of camouflaged targets to meet the design requirements. PMID:26415476

  19. Universal and culture-specific factors in the recognition and performance of musical affect expressions.

    PubMed

    Laukka, Petri; Eerola, Tuomas; Thingujam, Nutankumar S; Yamasaki, Teruo; Beller, Grégory

    2013-06-01

    We present a cross-cultural study on the performance and perception of affective expression in music. Professional bowed-string musicians from different musical traditions (Swedish folk music, Hindustani classical music, Japanese traditional music, and Western classical music) were instructed to perform short pieces of music to convey 11 emotions and related states to listeners. All musical stimuli were judged by Swedish, Indian, and Japanese participants in a balanced design, and a variety of acoustic and musical cues were extracted. Results first showed that the musicians' expressive intentions could be recognized with accuracy above chance both within and across musical cultures, but communication was, in general, more accurate for culturally familiar versus unfamiliar music, and for basic emotions versus nonbasic affective states. We further used a lens-model approach to describe the relations between the strategies that musicians use to convey various expressions and listeners' perceptions of the affective content of the music. Many acoustic and musical cues were similarly correlated with both the musicians' expressive intentions and the listeners' affective judgments across musical cultures, but the match between musicians' and listeners' uses of cues was better in within-cultural versus cross-cultural conditions. We conclude that affective expression in music may depend on a combination of universal and culture-specific factors. PMID:23398579

  20. Estradiol differentially affects auditory recognition and learning according to photoperiodic state in the adult male songbird, European starling (Sturnus vulgaris)

    PubMed Central

    Knudsen, Daniel P.; Krause, Jesse S.; Wingfield, John C.; Gentner, Timothy Q.

    2013-01-01

    Changes in hormones can affect many types of learning in vertebrates. Adults experience fluctuations in a multitude of hormones over a temporal scale, from local, rapid action to more long-term, seasonal changes. Endocrine changes during development can affect behavioral outcomes in adulthood, but how learning is affected in adults by hormone fluctuations experienced during adulthood is less understood. Previous reports have implicated the sex steroid hormone estradiol (E2) in both male and female vertebrate cognitive functioning. Here, we examined the effects of E2 on auditory recognition and learning in male European starlings (Sturnus vulgaris). European starlings are photoperiodic, seasonally breeding songbirds that undergo different periods of reproductive activity according to annual changes in day length. We simulated these reproductive periods, specifically 1. photosensitivity, 2. photostimulation, and 3. photorefractoriness in captive birds by altering day length. During each period, we manipulated circulating E2 and examined multiple measures of learning. To manipulate circulating E2, we used subcutaneous implants containing either 17-β E2 and/or fadrozole (FAD), a highly specific aromatase inhibitor that suppresses E2 production in the body and the brain, and measured the latency for birds to learn and respond to short, male conspecific song segments (motifs). We report that photostimulated birds given E2 had higher response rates and responded with better accuracy than those given saline controls or FAD. Conversely, photosensitive, animals treated with E2 responded with less accuracy than those given FAD. These results demonstrate how circulating E2 and photoperiod can interact to shape auditory recognition and learning in adults, driving it in opposite directions in different states. PMID:24058881

  1. Subthalamic nucleus stimulation affects fear and sadness recognition in Parkinson's disease.

    PubMed

    Péron, Julie; Biseul, Isabelle; Leray, Emmanuelle; Vicente, Siobhan; Le Jeune, Florence; Drapier, Sophie; Drapier, Dominique; Sauleau, Paul; Haegelen, Claire; Vérin, Marc

    2010-01-01

    Bilateral subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) can produce emotional disorders that have been linked to disturbance of the STN's limbic territory. The aim of this study was to confirm the impairment of the recognition of facial emotions (RFE) induced by STN DBS, not only ruling out the effect of the disease's natural progression in relation to the effect of DBS, but also assessing the influence of modifications in dopamine replacement therapy (DRT) following STN DBS. RFE was investigated in 24 PD patients who underwent STN DBS and 20 PD patients treated with apomorphine. They were assessed 3 months before and after treatment. The 2 patient groups were compared with a group of 30 healthy matched controls. The results showed that RFE for negative emotions (fear and sadness) was impaired in only the STN DBS group in the posttreatment condition and was unrelated to DRT. Results confirm the selective reduction of RFE induced by STN DBS, due neither to the disease's natural progression nor to modifications in DRT. PMID:20063943

  2. Competition between conceptual relations affects compound recognition: the role of entropy.

    PubMed

    Schmidtke, Daniel; Kuperman, Victor; Gagné, Christina L; Spalding, Thomas L

    2016-04-01

    Previous research has suggested that the conceptual representation of a compound is based on a relational structure linking the compound's constituents. Existing accounts of the visual recognition of modifier-head or noun-noun compounds posit that the process involves the selection of a relational structure out of a set of competing relational structures associated with the same compound. In this article, we employ the information-theoretic metric of entropy to gauge relational competition and investigate its effect on the visual identification of established English compounds. The data from two lexical decision megastudies indicates that greater entropy (i.e., increased competition) in a set of conceptual relations associated with a compound is associated with longer lexical decision latencies. This finding indicates that there exists competition between potential meanings associated with the same complex word form. We provide empirical support for conceptual composition during compound word processing in a model that incorporates the effect of the integration of co-activated and competing relational information. PMID:26340846

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  4. Real-time hardware continuous speech recognition system

    SciTech Connect

    Peckham, J.; Green, J.; Canning, J.; Stephens, P.

    1982-01-01

    Using both parallel and pipelined processing techniques, matching up to several hundred words from a previously stored vocabulary of whole word templates is possible in real time. An efficient single pass dynamic programming algorithm is used to find the sequence of templates that best represents the input. Continuous recognition is achieved using a traceback technique on partial recognition results. The acoustic analysis contains a number of features to improve performance. In particular a novel noise compensation algorithm is briefly described. 6 references.

  5. Visual object recognition for mobile tourist information systems

    NASA Astrophysics Data System (ADS)

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

    2005-03-01

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

  6. The use of ISPAHAN: interactive system for statistical pattern recognition and analysis.

    PubMed

    Gelsema, E S; Landeweerd, G H

    1981-09-01

    ISPAHAN, the interactive system for statistical pattern recognition and analysis, was developed at the Department of Medical Information at the Free University of Amsterdam. It has been used in many pattern recognition problems, such as white blood cell recognition, typification of wave forms in ECG analysis, segmentation of ECG signals and resonance detection in high-energy particle physics. The structure and capabilities of ISPAHAN are presented along with an example of its use in the field of white blood cell recognition. PMID:7294538

  7. Multi-Stage System for Automatic Target Recognition

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  8. Glycosylation Patterns of HIV-1 gp120 Depend on the Type of Expressing Cells and Affect Antibody Recognition*

    PubMed Central

    Raska, Milan; Takahashi, Kazuo; Czernekova, Lydie; Zachova, Katerina; Hall, Stacy; Moldoveanu, Zina; Elliott, Matt C.; Wilson, Landon; Brown, Rhubell; Jancova, Dagmar; Barnes, Stephen; Vrbkova, Jana; Tomana, Milan; Smith, Phillip D.; Mestecky, Jiri; Renfrow, Matthew B.; Novak, Jan

    2010-01-01

    Human immunodeficiency virus type 1 (HIV-1) entry is mediated by the interaction between a variably glycosylated envelope glycoprotein (gp120) and host-cell receptors. Approximately half of the molecular mass of gp120 is contributed by N-glycans, which serve as potential epitopes and may shield gp120 from immune recognition. The role of gp120 glycans in the host immune response to HIV-1 has not been comprehensively studied at the molecular level. We developed a new approach to characterize cell-specific gp120 glycosylation, the regulation of glycosylation, and the effect of variable glycosylation on antibody reactivity. A model oligomeric gp120 was expressed in different cell types, including cell lines that represent host-infected cells or cells used to produce gp120 for vaccination purposes. N-Glycosylation of gp120 varied, depending on the cell type used for its expression and the metabolic manipulation during expression. The resultant glycosylation included changes in the ratio of high-mannose to complex N-glycans, terminal decoration, and branching. Differential glycosylation of gp120 affected envelope recognition by polyclonal antibodies from the sera of HIV-1-infected subjects. These results indicate that gp120 glycans contribute to antibody reactivity and should be considered in HIV-1 vaccine design. PMID:20439465

  9. Acute stress affects free recall and recognition of pictures differently depending on age and sex.

    PubMed

    Hidalgo, Vanesa; Pulopulos, Matias M; Puig-Perez, Sara; Espin, Laura; Gomez-Amor, Jesus; Salvador, Alicia

    2015-10-01

    Little is known about age differences in the effects of stress on memory retrieval. Our aim was to perform an in-depth examination of acute psychosocial stress effects on memory retrieval, depending on age and sex. For this purpose, data from 52 older subjects (27 men and 25 women) were reanalyzed along with data from a novel group of 50 young subjects (26 men and 24 women). Participants were exposed to an acute psychosocial stress task (Trier Social Stress Test) or a control task. After the experimental manipulation, the retrieval of positive, negative and neutral pictures learned the previous day was tested. As expected, there was a significant response to the exposure to the stress task, but the older participants had a lower cortisol response to TSST than the younger ones. Stress impaired free recall of emotional (positive and negative) and neutral pictures only in the group of young men. Also in this group, correlation analyses showed a marginally significant association between cortisol and free recall. However, exploratory analyses revealed only a negative relationship between the stress-induced cortisol response and free recall of negative pictures. Moreover, stress impaired recognition memory of positive pictures in all participants, although this effect was not related to the cortisol or alpha-amylase response. These results indicate that both age and sex are critical factors in acute stress effects on specific aspects of long-term memory retrieval of emotional and neutral material. They also point out that more research is needed to better understand their specific role. PMID:26149415

  10. Speech recognition based on pattern recognition techniques

    NASA Astrophysics Data System (ADS)

    Rabiner, Lawrence R.

    1990-05-01

    Algorithms for speech recognition can be characterized broadly as pattern recognition approaches and acoustic phonetic approaches. To date, the greatest degree of success in speech recognition has been obtained using pattern recognition paradigms. The use of pattern recognition techniques were applied to the problems of isolated word (or discrete utterance) recognition, connected word recognition, and continuous speech recognition. It is shown that understanding (and consequently the resulting recognizer performance) is best to the simplest recognition tasks and is considerably less well developed for large scale recognition systems.

  11. A Limited-Vocabulary, Multi-Speaker Automatic Isolated Word Recognition System.

    ERIC Educational Resources Information Center

    Paul, James E., Jr.

    Techniques for automatic recognition of isolated words are investigated, and a computer simulation of a word recognition system is effected. Considered in detail are data acquisition and digitizing, word detection, amplitude and time normalization, short-time spectral estimation including spectral windowing, spectral envelope approximation,…

  12. Multi-font printed Mongolian document recognition system

    NASA Astrophysics Data System (ADS)

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

    2009-01-01

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

  13. Recognition as a challenging label-free optical sensing system

    NASA Astrophysics Data System (ADS)

    Gauglitz, Günter

    2013-05-01

    Optical biosensors are increasingly used in application areas of environmental analysis, healthcare and food safety. The quality of the biosensor's results depends on the interaction layer, the detection principles, and evaluation strategies, not only on the biopolymer layer but also especially on recognition elements. Using label-free optical sensing, non-specific interaction between sample and transducer has to be reduced, and the selectivity of recognition elements has to be improved. For this reason, strategies to avoid non-specific interaction even in blood and milk are discussed, a variety of upcoming recognition is given. Based on the classification of direct optical detection methods, some examples for the above mentioned applications are reviewed. Trends as well as advantages of parallel multisport detection for kinetic evaluation are also part of the lecture.

  14. Affect Recognition through Facebook for Effective Group Profiling towards Personalized Instruction

    ERIC Educational Resources Information Center

    Troussas, Christos; Espinosa, Kurt Junshean; Virvou, Maria

    2016-01-01

    Social networks are progressively being considered as an intense thought for learning. Particularly in the research area of Intelligent Tutoring Systems, they can create intuitive, versatile and customized e-learning systems which can advance the learning process by revealing the capacities and shortcomings of every learner and by customizing the…

  15. Dissecting ant recognition systems in the age of genomics.

    PubMed

    Tsutsui, Neil D

    2013-01-01

    Hamilton is probably best known for his seminal work demonstrating the role of kin selection in social evolution. His work made it clear that, for individuals to direct their altruistic behaviours towards appropriate recipients (kin), mechanisms must exist for kin recognition. In the social insects, colonies are typically comprised of kin, and colony recognition cues are used as proxies for kinship cues. Recent years have brought rapid advances in our understanding of the genetic and molecular mechanisms that are used for this process. Here, I review some of the most notable advances, particularly the contributions from recent ant genome sequences and molecular biology. PMID:24132093

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  17. Design of miniature hybrid target recognition system with combination of FPGA+DSP

    NASA Astrophysics Data System (ADS)

    Luo, Shishang; Li, Xiujian; Jia, Hui; Hu, Wenhua; Nie, Yongming; Chang, Shengli

    2010-10-01

    With advantages of flexibility, high bandwidth, high spatial resolution and high-speed parallel operation, the opto-electronic hybrid target recognition system can be applied in many civil and military areas, such as video surveillance, intelligent navigation and robot vision. A miniature opto-electronic hybrid target recognition system based on FPGA+DSP is designed, which only employs single Fourier lens and with a focal length. With the precise timing control of the FPGA and images pretreatment of the DSP, the system performs both Fourier transform and inverse Fourier transform with all optical process, which can improve recognition speed and reduce the system volume remarkably. We analyzed the system performance, and a method to achieve scale invariant pattern recognition was proposed on the basis of lots of experiments.

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

    NASA Astrophysics Data System (ADS)

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

    1984-02-01

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

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

    SciTech Connect

    Xia, Junyi Mart, Christopher; Bayouth, John

    2014-01-15

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

  20. Korean Anaphora Recognition System to Develop Healthcare Dialogue-Type Agent

    PubMed Central

    Yang, Junggi

    2014-01-01

    Objectives Anaphora recognition is a process to identify exactly which noun has been used previously and relates to a pronoun that is included in a specific sentence later. Therefore, anaphora recognition is an essential element of a dialogue agent system. In the current study, all the merits of rule-based, machine learning-based, semantic-based anaphora recognition systems were combined to design and realize a new hybrid-type anaphora recognition system with an optimum capacity. Methods Anaphora recognition rules were encoded on the basis of the internal traits of referred expressions and adjacent contexts to realize a rule-based system and to serve as a baseline. A semantic database, related to predicate instances of sentences including referred expressions, was constructed to identify semantic co-relationships between the referent candidates (to which semantic tags were attached) and the semantic information of predicates. This approach would upgrade the anaphora recognition system by reducing the number of referent candidates. Additionally, to realize a machine learning-based system, an anaphora recognition model was developed on the basis of training data, which indicated referred expressions and referents. The three methods were further combined to develop a new single hybrid-based anaphora recognition system. Results The precision rate of the rule-based systems was 54.9%. However, the precision rate of the hybrid-based system was 63.7%, proving it to be the most efficient method. Conclusions The hybrid-based method, developed by the combination of rule-based and machine learning-based methods, represents a new system with enhanced functional capabilities as compared to other pre-existing individual methods. PMID:25405063

  1. The Effect of Social Parasitism by Polyergus breviceps on the Nestmate Recognition System of Its Host, Formica altipetens

    PubMed Central

    Torres, Candice W.; Tsutsui, Neil D.

    2016-01-01

    Highly social ants, bees and wasps employ sophisticated recognition systems to identify colony members and deny foreign individuals access to their nest. For ants, cuticular hydrocarbons serve as the labels used to ascertain nest membership. Social parasites, however, are capable of breaking the recognition code so that they can thrive unopposed within the colonies of their hosts. Here we examine the influence of the socially parasitic slave-making ant, Polyergus breviceps on the nestmate recognition system of its slaves, Formica altipetens. We compared the chemical, genetic, and behavioral characteristics of colonies of enslaved and free-living F. altipetens. We found that enslaved Formica colonies were more genetically and chemically diverse than their free-living counterparts. These differences are likely caused by the hallmark of slave-making ant ecology: seasonal raids in which pupa are stolen from several adjacent host colonies. The different social environments of enslaved and free-living Formica appear to affect their recognition behaviors: enslaved Formica workers were less aggressive towards non-nestmates than were free-living Formica. Our findings indicate that parasitism by P. breviceps dramatically alters both the chemical and genetic context in which their kidnapped hosts develop, leading to changes in how they recognize nestmates. PMID:26840394

  2. The Effect of Social Parasitism by Polyergus breviceps on the Nestmate Recognition System of Its Host, Formica altipetens.

    PubMed

    Torres, Candice W; Tsutsui, Neil D

    2016-01-01

    Highly social ants, bees and wasps employ sophisticated recognition systems to identify colony members and deny foreign individuals access to their nest. For ants, cuticular hydrocarbons serve as the labels used to ascertain nest membership. Social parasites, however, are capable of breaking the recognition code so that they can thrive unopposed within the colonies of their hosts. Here we examine the influence of the socially parasitic slave-making ant, Polyergus breviceps on the nestmate recognition system of its slaves, Formica altipetens. We compared the chemical, genetic, and behavioral characteristics of colonies of enslaved and free-living F. altipetens. We found that enslaved Formica colonies were more genetically and chemically diverse than their free-living counterparts. These differences are likely caused by the hallmark of slave-making ant ecology: seasonal raids in which pupa are stolen from several adjacent host colonies. The different social environments of enslaved and free-living Formica appear to affect their recognition behaviors: enslaved Formica workers were less aggressive towards non-nestmates than were free-living Formica. Our findings indicate that parasitism by P. breviceps dramatically alters both the chemical and genetic context in which their kidnapped hosts develop, leading to changes in how they recognize nestmates. PMID:26840394

  3. How Mood and Task Complexity Affect Children's Recognition of Others’ Emotions

    PubMed Central

    Cummings, Andrew J.; Rennels, Jennifer L.

    2013-01-01

    Previous studies examined how mood affects children's accuracy in matching emotional expressions and labels (label-based tasks). This study was the first to assess how induced mood (positive, neutral, or negative) influenced 5- to 8-year-olds’ accuracy and reaction time using both context-based tasks, which required inferring a character's emotion from a vignette, and label-based tasks. Both tasks required choosing one of four facial expressions to respond. Children responded more accurately to label-based questions relative to context-based questions at 5 to 7 years of age, but showed no differences at 8 years of age, and when the emotional expression being identified was happiness, sadness, or surprise, but not disgust. For the context-based questions, children were more accurate at inferring sad and disgusted emotions compared to happy and surprised emotions. Induced positive mood facilitated 5-year-olds’ processing (decreased reaction time) in both tasks compared to induced negative and neutral moods. Results demonstrate how task type and children's mood influence children's emotion processing at different ages. PMID:24489442

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

    PubMed Central

    Xu, Xin; Tang, Jinshan; Zhang, Xiaolong; Liu, Xiaoming; Zhang, Hong; Qiu, Yimin

    2013-01-01

    With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activities, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation of the performance of human activity recognition. PMID:23353144

  5. Improving the recognition of fingerprint biometric system using enhanced image fusion

    NASA Astrophysics Data System (ADS)

    Alsharif, Salim; El-Saba, Aed; Stripathi, Reshma

    2010-04-01

    Fingerprints recognition systems have been widely used by financial institutions, law enforcement, border control, visa issuing, just to mention few. Biometric identifiers can be counterfeited, but considered more reliable and secure compared to traditional ID cards or personal passwords methods. Fingerprint pattern fusion improves the performance of a fingerprint recognition system in terms of accuracy and security. This paper presents digital enhancement and fusion approaches that improve the biometric of the fingerprint recognition system. It is a two-step approach. In the first step raw fingerprint images are enhanced using high-frequency-emphasis filtering (HFEF). The second step is a simple linear fusion process between the raw images and the HFEF ones. It is shown that the proposed approach increases the verification and identification of the fingerprint biometric recognition system, where any improvement is justified using the correlation performance metrics of the matching algorithm.

  6. Systemic Imidacloprid Affects Intraguild Parasitoids Differently

    PubMed Central

    Roe, R. Michael; Bacheler, Jack S.

    2015-01-01

    Toxoneuron nigriceps (Viereck) (Hymenoptera, Braconidae) and Campoletis sonorensis (Cameron) (Hymenoptera, Ichneumonidae) are solitary endoparasitoids of the tobacco budworm, Heliothis virescens (Fabricius) (Lepidoptera, Noctuidae). They provide biological control of H. virescens populations in Southeastern US agricultural production systems. Field and greenhouse experiments conducted from 2011–2014 compared parasitism rates of parasitoids that developed inside H. virescens larvae fed on tobacco plants treated with and without imidacloprid. The parasitoids in our study did not have a similar response. Toxoneuron nigriceps had reduced parasitism rates, but parasitism rates of C. sonorensis were unaffected. Preliminary data indicate that adult female lifespans of T. nigriceps are also reduced. ELISA was used to measure concentrations of neonicotinoids, imidacloprid and imidacloprid metabolites in H. virescens larvae that fed on imidacloprid-treated plants and in the parasitoids that fed on these larvae. Concentrations were detectable in the whole bodies of parasitized H. virescens larvae, T. nigriceps larvae and T. nigriceps adults, but not in C. sonorensis larvae and adults. These findings suggest that there are effects of imidacloprid on multiple trophic levels, and that insecticide use may differentially affect natural enemies with similar feeding niches. PMID:26658677

  7. Systemic Imidacloprid Affects Intraguild Parasitoids Differently.

    PubMed

    Taylor, Sally V; Burrack, Hannah J; Roe, R Michael; Bacheler, Jack S; Sorenson, Clyde E

    2015-01-01

    Toxoneuron nigriceps (Viereck) (Hymenoptera, Braconidae) and Campoletis sonorensis (Cameron) (Hymenoptera, Ichneumonidae) are solitary endoparasitoids of the tobacco budworm, Heliothis virescens (Fabricius) (Lepidoptera, Noctuidae). They provide biological control of H. virescens populations in Southeastern US agricultural production systems. Field and greenhouse experiments conducted from 2011-2014 compared parasitism rates of parasitoids that developed inside H. virescens larvae fed on tobacco plants treated with and without imidacloprid. The parasitoids in our study did not have a similar response. Toxoneuron nigriceps had reduced parasitism rates, but parasitism rates of C. sonorensis were unaffected. Preliminary data indicate that adult female lifespans of T. nigriceps are also reduced. ELISA was used to measure concentrations of neonicotinoids, imidacloprid and imidacloprid metabolites in H. virescens larvae that fed on imidacloprid-treated plants and in the parasitoids that fed on these larvae. Concentrations were detectable in the whole bodies of parasitized H. virescens larvae, T. nigriceps larvae and T. nigriceps adults, but not in C. sonorensis larvae and adults. These findings suggest that there are effects of imidacloprid on multiple trophic levels, and that insecticide use may differentially affect natural enemies with similar feeding niches. PMID:26658677

  8. Development of an Environment-Aware Locomotion Mode Recognition System for Powered Lower Limb Prostheses.

    PubMed

    Liu, Ming; Wang, Ding; Helen Huang, He

    2016-04-01

    This paper aimed to develop and evaluate an environment-aware locomotion mode recognition system for volitional control of powered artificial legs. A portable terrain recognition (TR) module, consisting of an inertia measurement unit and a laser distance meter, was built to identify the type of terrain in front of the wearer while walking. A decision tree was used to classify the terrain types and provide either coarse or refined information about the walking environment. Then, the obtained environmental information was modeled as a priori probability and was integrated with a neuromuscular-mechanical-fusion-based locomotion mode (LM) recognition system. The designed TR module and environmental-aware LM recognition system was evaluated separately on able-bodied subjects and a transfemoral amputee online. The results showed that the TR module provided high quality environmental information: TR accuracy is above 98% and terrain transitions are detected over 500 ms before the time required to switch the prosthesis control mode. This enabled smooth locomotion mode transitions for the wearers. The obtained environmental information further improved the performance of LM recognition system, regardless of whether coarse or refined information was used. In addition, the environment-aware LM recognition system produced reliable online performance when the TR output was relatively noisy, which indicated the potential of this system to operate in unconstructed environment. This paper demonstrated that environmental information should be considered for operating wearable lower limb robotic devices, such as prosthetics and orthotics. PMID:25879962

  9. A new accurate pill recognition system using imprint information

    NASA Astrophysics Data System (ADS)

    Chen, Zhiyuan; Kamata, Sei-ichiro

    2013-12-01

    Great achievements in modern medicine benefit human beings. Also, it has brought about an explosive growth of pharmaceuticals that current in the market. In daily life, pharmaceuticals sometimes confuse people when they are found unlabeled. In this paper, we propose an automatic pill recognition technique to solve this problem. It functions mainly based on the imprint feature of the pills, which is extracted by proposed MSWT (modified stroke width transform) and described by WSC (weighted shape context). Experiments show that our proposed pill recognition method can reach an accurate rate up to 92.03% within top 5 ranks when trying to classify more than 10 thousand query pill images into around 2000 categories.

  10. The development of the speaker independent ARM continuous speech recognition system

    NASA Astrophysics Data System (ADS)

    Russell, M. J.

    1992-01-01

    The development of a speaker dependent continuous speech recognition system based on phoneme level hidden Markov models is described. The system is part of the Airborne Reconnaissance Mission (ARM) project, that aims at reaching the accurate recognition of continuously spoken airborne reconnaissance reports using a speech recognition system and Markov models. The system is configured to recognize continuously spoken airborne reconnaissance reports, a task which involves a vocabulary of approximately 500 words. On a test set of speech from 80 male subjects, the final system achieves a word accuracy of 74.1 percent with no explicit syntactic constraints. The evolution of the speaker independent ARM system, in terms of the performance of its various versions of the evaluation set, is summarized. Comparison of the final versions of the speaker dependent and speaker independent ARM systems shows that many of the empirically derived parameters are similar on both systems.

  11. [High-speed target recognition positioning system based on multi-spectral radiation characteristics].

    PubMed

    Li, Jian-Min; Wang, Gao

    2014-11-01

    In order to achieve quick recognition and positioning of the high-speed target, using multi-spectral radiation combined with acoustic positioning technology, in the passive state, the blast wave spectral characteristics and acoustic characteristics of the measured target were rapidly obtained, thus analysis was performed to determine the type, location and other important parameters. Multi-spectral radiation detection target recognition formula was deduced. The accuracy of the optical path length and the logical integration time was calculated by shock acoustic positioning method. Experiments used 5.56 mm NATO bullets, 7.62 mm 56-rifle bullets, 12.7 mm 54 type machine-gun bullets as a target identified projectile. Interference fringes were collected by the static Fourier transform interferometer system and ICX387AL type CCD, and the peak of sound pressure was collected using 2209 pulse sound pressure meter made by B & K Company from Denmark Experimental results show that for the 5.56 mm NATO bullets, the three characteristic wavelengths position amplitudes are close to each other, with the maximum amplitude at 966 nm; For the 7.62 mm 56-rifle bullets, 935 nm is the maximum amplitude position, while for 966 and 997 nm position the magnitudes are sunukar; For 12.7 mm 54 type machine-gun bullets, the three wavelengths show a ladder-like distribution. With the increase in the detection distance spectral radiation energy decreased. Meanwhile, with the decrease in the total radiation spectrum, the spectrum of target was affected strongly by background noise, and the SNR of system was decreased. But the spectral characteristics of different target still exist, the target species can be identified by the system with the ratio algorithm of characteristic peaks. Through spectral calibration and characteristic wavelengths extraction, the target can successfully identify the type of projectile and target position, and it meets the design requirements. PMID:25752076

  12. Development of an auditory emotion recognition function using psychoacoustic parameters based on the International Affective Digitized Sounds.

    PubMed

    Choi, Youngimm; Lee, Sungjun; Jung, SungSoo; Choi, In-Mook; Park, Yon-Kyu; Kim, Chobok

    2015-12-01

    The purpose of this study was to develop an auditory emotion recognition function that could determine the emotion caused by sounds coming from the environment in our daily life. For this purpose, sound stimuli from the International Affective Digitized Sounds (IADS-2), a standardized database of sounds intended to evoke emotion, were selected, and four psychoacoustic parameters (i.e., loudness, sharpness, roughness, and fluctuation strength) were extracted from the sounds. Also, by using an emotion adjective scale, 140 college students were tested to measure three basic emotions (happiness, sadness, and negativity). From this discriminant analysis to predict basic emotions from the psychoacoustic parameters of sound, a discriminant function with overall discriminant accuracy of 88.9% was produced from training data. In order to validate the discriminant function, the same four psychoacoustic parameters were extracted from 46 sound stimuli collected from another database and substituted into the discriminant function. The results showed that an overall discriminant accuracy of 63.04% was confirmed. Our findings provide the possibility that daily-life sounds, beyond voice and music, can be used in a human-machine interface. PMID:25319038

  13. Accuracy, security, and processing time comparisons of biometric fingerprint recognition system using digital and optical enhancements

    NASA Astrophysics Data System (ADS)

    Alsharif, Salim; El-Saba, Aed; Jagapathi, Rajendarreddy

    2011-06-01

    Fingerprint recognition is one of the most commonly used forms of biometrics and has been widely used in daily life due to its feasibility, distinctiveness, permanence, accuracy, reliability, and acceptability. Besides cost, issues related to accuracy, security, and processing time in practical biometric recognition systems represent the most critical factors that makes these systems widely acceptable. Accurate and secure biometric systems often require sophisticated enhancement and encoding techniques that burdens the overall processing time of the system. In this paper we present a comparison between common digital and optical enhancementencoding techniques with respect to their accuracy, security and processing time, when applied to biometric fingerprint systems.

  14. Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems

    PubMed Central

    Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

    2015-01-01

    The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other. PMID:26213932

  15. Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems.

    PubMed

    Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

    2015-01-01

    The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other. PMID:26213932

  16. Metacognitive deficits predict future levels of negative symptoms in schizophrenia controlling for neurocognition, affect recognition, and self-expectation of goal attainment.

    PubMed

    Lysaker, Paul H; Kukla, Marina; Dubreucq, Julien; Gumley, Andrew; McLeod, Hamish; Vohs, Jenifer L; Buck, Kelly D; Minor, Kyle S; Luther, Lauren; Leonhardt, Bethany L; Belanger, Elizabeth A; Popolo, Raffaele; Dimaggio, Giancarlo

    2015-10-01

    The recalcitrance of negative symptoms in the face of pharmacologic treatment has spurred interest in understanding the psychological factors that contribute to their formation and persistence. Accordingly, this study investigated whether deficits in metacognition, or the ability to form integrated ideas about oneself, others, and the world, prospectively predicted levels of negative symptoms independent of deficits in neurocognition, affect recognition and defeatist beliefs. Participants were 53 adults with a schizophrenia spectrum disorder. Prior to entry into a rehabilitation program, all participants completed concurrent assessments of metacognition with the Metacognitive Assessment Scale-Abbreviated, negative symptoms with the Positive and Negative Syndrome Scale, neurocognition with the MATRICS battery, affect recognition with the Bell Lysaker Emotion Recognition Task, and one form of defeatist beliefs with the Recovery Assessment Scale. Negative symptoms were then reassessed one week, 9weeks, and 17weeks after entry into the program. A mixed effects regression model revealed that after controlling for baseline negative symptoms, a general index of neurocognition, defeatist beliefs and capacity for affect recognition, lower levels of metacognition predicted higher levels of negative symptoms across all subsequent time points. Poorer metacognition was able to predict later levels of elevated negative symptoms even after controlling for initial levels of negative symptoms. Results may suggest that metacognitive deficits are a risk factor for elevated levels of negative symptoms in the future. Clinical implications are also discussed. PMID:26164820

  17. Concept Recognition in an Automatic Text-Processing System for the Life Sciences.

    ERIC Educational Resources Information Center

    Vleduts-Stokolov, Natasha

    1987-01-01

    Describes a system developed for the automatic recognition of biological concepts in titles of scientific articles; reports results of several pilot experiments which tested the system's performance; analyzes typical ambiguity problems encountered by the system; describes a disambiguation technique that was developed; and discusses future plans…

  18. Tillage system affects microbiological properties of soil

    NASA Astrophysics Data System (ADS)

    Delgado, A.; de Santiago, A.; Avilés, M.; Perea, F.

    2012-04-01

    Soil tillage significantly affects organic carbon accumulation, microbial biomass, and subsequently enzymatic activity in surface soil. Microbial activity in soil is a crucial parameter contributing to soil functioning, and thus a basic quality factor for soil. Since enzymes remain soil after excretion by living or disintegrating cells, shifts in their activities reflect long-term fluctuations in microbial biomass. In order to study the effects of no-till on biochemical and microbiological properties in comparison to conventional tillage in a representative soil from South Spain, an experiment was conducted since 1982 on the experimental farm of the Institute of Agriculture and Fisheries Research of Andalusia (IFAPA) in Carmona, SW Spain (37o24'07''N, 5o35'10''W). The soil at the experimental site was a very fine, montomorillonitic, thermic Chromic Haploxerert (Soil Survey Staff, 2010). A randomized complete block design involving three replications and the following two tillage treatments was performed: (i) Conventional tillage, which involved mouldboard plowing to a depth of 50 cm in the summer (once every three years), followed by field cultivation to a depth of 15 cm before sowing; crop residues being burnt, (ii) No tillage, which involved controlling weeds before sowing by spraying glyphosate and sowing directly into the crop residue from the previous year by using a planter with double-disk openers. For all tillage treatments, the crop rotation (annual crops) consisted of winter wheat, sunflower, and legumes (pea, chickpea, or faba bean, depending on the year), which were grown under rainfed conditions. Enzymatic activities (ß-glucosidase, dehydrogenase, aryl-sulphatase, acid phosphatase, and urease), soil microbial biomass by total viable cells number by acridine orange direct count, the density of cultivable groups of bacteria and fungi by dilution plating on semi-selective media, the physiological profiles of the microbial communities by BiologR, and the

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

    PubMed Central

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

    2013-01-01

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

  20. Construction of Multi-Mode Affective Learning System: Taking Affective Design as an Example

    ERIC Educational Resources Information Center

    Lin, Hao-Chiang Koong; Su, Sheng-Hsiung; Chao, Ching-Ju; Hsieh, Cheng-Yen; Tsai, Shang-Chin

    2016-01-01

    This study aims to design a non-simultaneous distance instruction system with affective computing, which integrates interactive agent technology with the curricular instruction of affective design. The research subjects were 78 students, and prototype assessment and final assessment were adopted to assess the interface and usability of the system.…

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

    PubMed Central

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

    2015-01-01

    This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and may lead to inaccuracies due to noise disturbances. The recognition accuracy and speed of current systems cannot meet the requirements of Φ-OTDR online vibration monitoring systems. In the method proposed in this paper, the time-space domain signal is used for feature extraction instead of the time domain signal. Feature vectors are obtained from morphologic features of time-space domain signals. A scatter matrix is calculated for the feature selection. Experiments show that the feature extraction method proposed in this paper can greatly improve recognition accuracies, with a lower computation time than traditional methods, i.e., a recognition accuracy of 97.8% can be achieved with a recognition time of below 1 s, making it is very suitable for Φ-OTDR system online vibration monitoring. PMID:26131671

  2. [Research on Barrier-free Home Environment System Based on Speech Recognition].

    PubMed

    Zhu, Husheng; Yu, Hongliu; Shi, Ping; Fang, Youfang; Jian, Zhuo

    2015-10-01

    The number of people with physical disabilities is increasing year by year, and the trend of population aging is more and more serious. In order to improve the quality of the life, a control system of accessible home environment for the patients with serious disabilities was developed to control the home electrical devices with the voice of the patients. The control system includes a central control platform, a speech recognition module, a terminal operation module, etc. The system combines the speech recognition control technology and wireless information transmission technology with the embedded mobile computing technology, and interconnects the lamp, electronic locks, alarms, TV and other electrical devices in the home environment as a whole system through a wireless network node. The experimental results showed that speech recognition success rate was more than 84% in the home environment. PMID:26964305

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

    PubMed

    Brandl, Paul; Weiss, Alexander; Zimmermann, Horst

    2014-07-01

    In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate <10⁻⁹) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s. PMID:24978803

  4. The role of asymmetric transfer in the evaluation of voice generation and recognition systems

    NASA Astrophysics Data System (ADS)

    Damos, D. L.

    1987-02-01

    The results of five experiments examining the effect of voice generation and recognition systems on dual task performance are presented. The extent to which asymmetric transfer biased the data in three of these experiments is determined by using statistical techniques and by comparing the data to the results of between subjects experiments. Generally, subjects performed task combinations better when stimuli for one of the tasks was presented auditorily using a voice generation system rather than visually on a display screen. In contrast, the use of a voice recognition system did not result in better dual task performance than the use of more conventional input devices.

  5. A computerized recognition system for the home-based physiotherapy exercises using an RGBD camera.

    PubMed

    Ar, Ilktan; Akgul, Yusuf Sinan

    2014-11-01

    Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained. PMID:24860037

  6. Drosophila GRAIL: An intelligent system for gene recognition in Drosophila DNA sequences

    SciTech Connect

    Xu, Ying; Einstein, J.R.; Uberbacher, E.C.; Helt, G.; Rubin, G.

    1995-06-01

    An AI-based system for gene recognition in Drosophila DNA sequences was designed and implemented. The system consists of two main modules, one for coding exon recognition and one for single gene model construction. The exon recognition module finds a coding exon by recognition of its splice junctions (or translation start) and coding potential. The core of this module is a set of neural networks which evaluate an exon candidate for the possibility of being a true coding exon using the ``recognized`` splice junction (or translation start) and coding signals. The recognition process consists of four steps: generation of an exon candidate pool, elimination of improbable candidates using heuristic rules, candidate evaluation by trained neural networks, and candidate cluster resolution and final exon prediction. The gene model construction module takes as input the clustered exon candidates and builds a ``best`` possible single gene model using an efficient dynamic programming algorithm. 129 Drosophila sequences consisting of 441 coding exons including 216358 coding bases were extructed from GenBank and used to build statistical matrices and to train the neural networks. On this training set the system recognized 97% of the coding messages and predicted only 5% false messages. Among the ``correctly`` predicted exons, 68% match the actual exon exactly and 96% have at least one edge predicted correctly. On an independent test set consisting of 30 Drosophila sequences, the system recognized 96% of the coding messages and predicted 7% false messages.

  7. Political and institutional factors affecting systems engineering

    NASA Technical Reports Server (NTRS)

    Yardley, John F.

    1993-01-01

    External groups have a significant impact on NASA's programs. Ten groups affecting NASA are identified, and examples are given for some of the them. Methods of dealing with these external inputs are discussed, the most important being good and open two way communications and an objective attitude on the part of the NASA participants. The importance of planning ahead, of developing rapport with these groups, and of effective use of NASA contractors is covered. The need for an overall strategic plan for the U.S. space program is stressed.

  8. Compatibility Issues Affecting Information Systems and Services.

    ERIC Educational Resources Information Center

    Lancaster, F. Wilfrid; Smith, Linda C.

    This UNISIST publication discusses issues related to the compatibility and standardization of bibliograpic records, index languages, software, hardware, and other information systems and services. Following an executive summary, definitions of terms, and other introductory material, existing information systems with common standards are briefly…

  9. Low-cost speech recognition system for small vocabulary and independent speaker

    NASA Astrophysics Data System (ADS)

    Teh, Chih Chiang; Jong, Ching C.; Siek, Liter

    2000-10-01

    In this paper an ASIC implementation of a low cost speech recognition system for small vocabulary, 15 isolated word, speaker independent is presented. The IC is a digital block that receives a 12 bit sample with a sampling rate of 11.025 kHz as its input. The IC is running at 10 MHz system clock and targeted at 0.35 micrometers CMOS process. The whole chip, which includes the speech recognition system core, RAM and ROM contains about 61000 gates. The die size is 1.5 mm by 3 mm. The current design had been coded in VHDL for hardware implementation and its functionality is identical with the Matlab simulation. The average speech recognition rate for this IC is 89 percent for 15 isolated words.

  10. Bioacoustic systems: insights for acoustical imaging and pattern recognition (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Altes, Richard A.

    1987-09-01

    Standard performance measures and statistical tests must be altered for research on animal sonar. The narrowband range-Doppler ambiguity function must be redefined to analyze wideband signals. A new range, cross-range ambiguity function is needed to represent angle estimation and spatial resolution properties of animal sonar systems. Echoes are transformed into time-frequency (spectrogram-like) representations by the peripheral auditory system. Detection, estimation, and pattern recognition capabilities of animals should thus be analyzed in terms of operations on spectrograms. The methods developed for bioacoustic research yield new insights into the design of man-made imaging and pattern recognition systems. The range, cross-range ambiguity function can be used to improve imaging performance. Important features for echo pattern recognition are illustrated by time-frequency plots showing (i) principal components for spectrograms and (ii) templates for optimum discrimination between data classes.

  11. Preliminary results on the use of linear discriminant analysis in the ARM continuous speech recognition system

    NASA Astrophysics Data System (ADS)

    Peeling, S. M.; Ponting, K. M.

    1991-12-01

    Linear discriminant analysis is used to generate speech data transformations. This transformed data is then used within the Airborne Reconnaissance Mission (ARM) continuous speech recognition system. The aim of the ARM project is accurate recognition of continuously spoken airborne reconnaissance reports using a speech recognition system based on phoneme level hidden Markov models. A fuller description of a linear discriminant analysis, which is applied to speaker dependent data in the ARM system, is given. Preliminary results are presented from experiments using transformed data alone and also in conjunction with one, or both, of the word transition penalties and variable frame rate analysis. Speaker dependent results are reported which are significantly better then the best obtained previously.

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

    ERIC Educational Resources Information Center

    Little, Glenn A.; And Others

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

  13. PATTERN RECOGNITION/EXPERT SYSTEM FOR IDENTIFICATION OF TOXIC COMPOUNDS FROM LOW RESOLUTION MASS SPECTRA

    EPA Science Inventory

    An empirical rule-based pattern recognition/expert system for classifying, estimating molecular weights and identifying low resolution mass spectra of toxic and other organic compounds has been developed and evaluated. he system was designed to accommodate low concentration spect...

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

    ERIC Educational Resources Information Center

    Kameny, Iris; Ritea, H.

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

  15. How phototherapy affects the immune system

    NASA Astrophysics Data System (ADS)

    Dyson, Mary

    2008-03-01

    The immune system is a complex group of cells, tissues and organs that recognize and attack foreign substances, pathogenic organisms and cancer cells. It also responds to injury by producing inflammation. The immune system has peripheral components that include skin-associated lymphoid tissues (SALT) and mucosa-associated lymphoid tissues (MALT), located where pathogens and other harmful substances gain access to the body. Phototherapy, delivered at appropriate treatment parameters, exerts direct actions on the cellular elements of the peripheral part of the immune system since it is readily accessible to photons.

  16. Recognition of Specified RNA Modifications by the Innate Immune System.

    PubMed

    Eigenbrod, Tatjana; Keller, Patrick; Kaiser, Steffen; Rimbach, Katharina; Dalpke, Alexander H; Helm, Mark

    2015-01-01

    Microbial nucleic acids have been described as important activators of human innate immune responses by triggering so-called pattern recognition receptors (PRRs) that are expressed on innate immune cells, including plasmacytoid dendritic cells and monocytes. Although host and microbial nucleic acids share pronounced chemical and structural similarities, they significantly differ in their posttranscriptional modification profile, allowing the host to discriminate between self and nonself. In this regard, ribose 2'-O-methylation has been discovered as suppressor of RNA-induced PRR activation. Although 2'-O-methylation occurs with higher frequencies in eukaryotic than in prokaryotic RNA, the immunosuppressive properties of 2'-O-methylated nucleotides may be misused by certain bacteria as immune evasion mechanism. In the course of identifying inhibitory RNA modifications, our groups have synthesized and comparatively analyzed a series of differentially modified RNAs, so-called modivariants, for their immune stimulatory capacities. In this chapter, we will detail the protocols for the design and synthesis of RNA modivariants by molecular cut-and-paste techniques (referred to as molecular surgery) and describe testing of their immune stimulatory properties upon transfection into peripheral blood mononuclear cells. PMID:26253966

  17. Flexibility and molecular recognition in the immune system

    PubMed Central

    Jimenez, Ralph; Salazar, Georgina; Baldridge, Kim K.; Romesberg, Floyd E.

    2003-01-01

    Photon echo spectroscopy has been used to measure the response of three antibody-binding sites to perturbation from electronic excitation of a bound antigen, fluorescein. The three antibodies show motions that range in time scale from tens of femtoseconds to nanoseconds. Relative to the others, one antibody, 4-4-20, possesses a rigid binding site that likely results from a short and inflexible heavy chain complementarity-determining region 3 (HCDR3) loop and a critical Tyr that acts as a “molecular splint,” rigidifying the antigen across its most flexible internal degree of freedom. The remaining two antibodies, 34F10 and 40G4, despite being generated against the same antigen, possess binding sites that are considerably more flexible. The more flexible combining sites likely result from longer HCDR3 loops and a deletion in the light chain complementarity-determining region 1 (LCDR1) that removes the critical Tyr residue. The binding site flexibilities may result in varying mechanisms of antigen recognition including lock-and-key, induced-fit, and conformational selection. PMID:12518056

  18. A Gesture Recognition System for Detecting Behavioral Patterns of ADHD.

    PubMed

    Bautista, Miguel Ángel; Hernández-Vela, Antonio; Escalera, Sergio; Igual, Laura; Pujol, Oriol; Moya, Josep; Violant, Verónica; Anguera, María T

    2016-01-01

    We present an application of gesture recognition using an extension of dynamic time warping (DTW) to recognize behavioral patterns of attention deficit hyperactivity disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the set of gesture samples of a certain gesture category using either Gaussian mixture models or an approximation of convex hulls. Thus, we add a theoretical contribution to classical warping path in DTW by including local modeling of intraclass gesture variability. This methodology is applied in a clinical context, detecting a group of ADHD behavioral patterns defined by experts in psychology/psychiatry, to provide support to clinicians in the diagnose procedure. The proposed methodology is tested on a novel multimodal dataset (RGB plus depth) of ADHD children recordings with behavioral patterns. We obtain satisfying results when compared to standard state-of-the-art approaches in the DTW context. PMID:26684256

  19. Pattern recognition receptors and central nervous system repair

    PubMed Central

    Kigerl, Kristina A.; de Rivero Vaccari, Juan Pablo; Dietrich, W. Dalton

    2016-01-01

    Pattern recognition receptors (PRRs) are part of the innate immune response and were originally discovered for their role in recognizing pathogens by ligating specific pathogen associated molecular patterns (PAMPs) expressed by microbes. Now the role of PRRs in sterile inflammation is also appreciated, responding to endogenous stimuli referred to as “damage associated molecular patterns” (DAMPs) instead of PAMPs. The main families of PRRs include Toll-like receptors (TLRs), Nod-like receptors (NLRs), RIG-like receptors (RLRs), AIM2-like receptors (ALRs), and C-type lectin receptors. Broad expression of these PRRs in the CNS and the release of DAMPs in and around sites of injury suggest an important role for these receptor families in mediating post-injury inflammation. Considerable data now show that PRRs are among the first responders to CNS injury and activation of these receptors on microglia, neurons, and astrocytes triggers an innate immune response in the brain and spinal cord. Here we discuss how the various PRR families are activated and can influence injury and repair processes following CNS injury. PMID:25017883

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

    PubMed

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

    2014-08-13

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. PMID:25122896

  1. A Single-System Model Predicts Recognition Memory and Repetition Priming in Amnesia

    PubMed Central

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

    2014-01-01

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. PMID:25122896

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  3. The design and implementation of effective face detection and recognition system

    NASA Astrophysics Data System (ADS)

    Sun, Yigui

    2011-06-01

    In the paper, a face detection and recognition system (FDRS) based on video sequences and still image is proposed. It uses the AdaBoost algorithm to detect human face in the image or frame, adopts Discrete Cosine Transforms (DCT) for feature extraction and recognition in face image. The related technologies are firstly outlined. Then, the system requirements and UML use case diagram are described. In addition, the paper mainly introduces the design solution and key procedures. The FDRS's source-code is built in VC++, Standard Template Library (STL) and Intel Open Source Computer Vision Library (OpenCV).

  4. BioTagger-GM: A Gene/Protein Name Recognition System

    PubMed Central

    Torii, Manabu; Hu, Zhangzhi; Wu, Cathy H.; Liu, Hongfang

    2009-01-01

    Objectives Biomedical named entity recognition (BNER) is a critical component in automated systems that mine biomedical knowledge in free text. Among different types of entities in the domain, gene/protein would be the most studied one for BNER. Our goal is to develop a gene/protein name recognition system BioTagger-GM that exploits rich information in terminology sources using powerful machine learning frameworks and system combination. Design BioTagger-GM consists of four main components: (1) dictionary lookup—gene/protein names in BioThesaurus and biomedical terms in UMLS Metathesaurus are tagged in text, (2) machine learning—machine learning systems are trained using dictionary lookup results as one type of feature, (3) post-processing—heuristic rules are used to correct recognition errors, and (4) system combination—a voting scheme is used to combine recognition results from multiple systems. Measurements The BioCreAtIvE II Gene Mention (GM) corpus was used to evaluate the proposed method. To test its general applicability, the method was also evaluated on the JNLPBA corpus modified for gene/protein name recognition. The performance of the systems was evaluated through cross-validation tests and measured using precision, recall, and F-Measure. Results BioTagger-GM achieved an F-Measure of 0.8887 on the BioCreAtIvE II GM corpus, which is higher than that of the first-place system in the BioCreAtIvE II challenge. The applicability of the method was also confirmed on the modified JNLPBA corpus. Conclusion The results suggest that terminology sources, powerful machine learning frameworks, and system combination can be integrated to build an effective BNER system. PMID:19074302

  5. Can color changes alter the neural correlates of recognition memory? Manipulation of processing affects an electrophysiological indicator of conceptual implicit memory.

    PubMed

    Cui, Xiaoyu; Gao, Chuanji; Zhou, Jianshe; Guo, Chunyan

    2016-09-28

    It has been widely shown that recognition memory includes two distinct retrieval processes: familiarity and recollection. Many studies have shown that recognition memory can be facilitated when there is a perceptual match between the studied and the tested items. Most event-related potential studies have explored the perceptual match effect on familiarity on the basis of the hypothesis that the specific event-related potential component associated with familiarity is the FN400 (300-500 ms mid-frontal effect). However, it is currently unclear whether the FN400 indexes familiarity or conceptual implicit memory. In addition, on the basis of the findings of a previous study, the so-called perceptual manipulations in previous studies may also involve some conceptual alterations. Therefore, we sought to determine the influence of perceptual manipulation by color changes on recognition memory when the perceptual or the conceptual processes were emphasized. Specifically, different instructions (perceptually or conceptually oriented) were provided to the participants. The results showed that color changes may significantly affect overall recognition memory behaviorally and that congruent items were recognized with a higher accuracy rate than incongruent items in both tasks, but no corresponding neural changes were found. Despite the evident familiarity shown in the two tasks (the behavioral performance of recognition memory was much higher than at the chance level), the FN400 effect was found in conceptually oriented tasks, but not perceptually oriented tasks. It is thus highly interesting that the FN400 effect was not induced, although color manipulation of recognition memory was behaviorally shown, as seen in previous studies. Our findings of the FN400 effect for the conceptual but not perceptual condition support the explanation that the FN400 effect indexes conceptual implicit memory. PMID:27489100

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

    NASA Astrophysics Data System (ADS)

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

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

  7. A recognition method in holographic data storage system by using structural similarity

    NASA Astrophysics Data System (ADS)

    Chen, Yu-Ta; Ou-Yang, Mang; Lee, Cheng-Chung

    2013-09-01

    The holographic data storage system (HDSS) is a page-oriented storage system with advantages of great capacity and high speed. The page-oriented recording breaks the tradition of the optical storage of one-point recording. As the signal image is retrieved from the storage material in the HDSS, various noises influences the image and then the data retrieve will be difficultly from the image by using the thresholding method. For progressing on the thresholding method, a recognition method, based on the structural similarity, is proposed to replace the thresholding method in the HDSS. The recognition method is implemented that the image comparison between the receive image and reference image is performed by the structural similarity method to find the most similar reference image to the received image. In the experiment, by using recognition method, the bit error rate (BER) results in 26% decrease less than using the thresholding method in the HDSS. Owing to some strong effects, such as non-uniform intensity and strong speckle, still influencing on the received image, the recognition method is seemed to be slightly better than thresholding method. In the future, the strong effects would be reduced to improve the quality of the receive image and then the result of using the recognition method may be vastly better than the thresholding method.

  8. Design of no blind area perimeter intrusion recognition system based on fisheye lens

    NASA Astrophysics Data System (ADS)

    Dai, Jun-jian; Han, Wen-bo

    2013-08-01

    The Perimeter intrusion recognition technology has slowly become an indispensable function in the intelligent video surveillance system. The existed always use the multiple video acquisition nodes to respectively control a monitoring area and each node alarm independently. However, the existed solutions are difficult to avoid the existence of monitoring blind area, and can't suitable for the perimeter environment with irregular outline, and at the same time, because of the too many nodes, it inevitably decreased the overall accuracy of intrusion recognition system and increased the cost of system. To avoid the above defects, this paper mainly talks about the following three aspects. Firstly, we used the fisheye lens as the optical system of video acquisition node, and it evidently enhances each node's information acquisition ability. And in this way, we just need to decorate a small amount of video acquisition node to get no blind area environmental information of the perimeter when against a larger monitoring situation. Secondly, due to the inexistence of blind area, the system will have enough video image information to generate the 360 degree panoramic image for monitoring environment, and finally the system server collected the wide-angle image information to splice into the panoramic video image. Finally, the system will use the panoramic image to complete the intrusion behavior recognition, thus we can effectively avoid the parallel computation in many nodes independently invasion of recognition, and this can greatly reduces the dependence for the multiple CPU operation platform and enhances the reliability of the system. The field test results show that, with the help of this paper's solution, the perimeter of the invasion of recognition system can effectively avoids the recognition of blind area. In the same recognition algorithm and same level delay premise, it greatly reduces the monitoring system server configuration requirements, especially for the

  9. Real-time optical multiple object recognition and tracking system and method

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin (Inventor); Liu, Hua-Kuang (Inventor)

    1990-01-01

    System for optically recognizing and tracking a plurality of objects within a field of vision. Laser (46) produces a coherent beam (48). Beam splitter (24) splits the beam into object (26) and reference (28) beams. Beam expanders (50) and collimators (52) transform the beams (26, 28) into coherent collimated light beams (26', 28'). A two-dimensional SLM (54), disposed in the object beam (26'), modulates the object beam with optical information as a function of signals from a first camera (16) which develops X and Y signals reflecting the contents of its field of vision. A hololens (38), positioned in the object beam (26') subsequent to the modulator (54), focuses the object beam at a plurality of focal points (42). A planar transparency-forming film (32), disposed with the focal points on an exposable surface, forms a multiple position interference filter (62) upon exposure of the surface and development processing of the film (32). A reflector (53) directing the reference beam (28') onto the film (32), exposes the surface, with images focused by the hololens (38), to form interference patterns on the surface. There is apparatus (16', 64) for sensing and indicating light passage through respective ones of the positions of the filter (62), whereby recognition of objects corresponding to respective ones of the positions of the filter (62) is affected. For tracking, apparatus (64) focuses light passing through the filter (62) onto a matrix of CCD's in a second camera (16') to form a two-dimensional display of the recognized objects.

  10. Recognition intent and visual word recognition.

    PubMed

    Wang, Man-Ying; Ching, Chi-Le

    2009-03-01

    This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed. PMID:19036609

  11. Voice recognition.

    PubMed

    Mehta, Amit; McLoud, Theresa C

    2003-07-01

    Voice recognition represents one of the new technologies that are changing the practice of radiology. Thirty percent of radiology practices are either currently or plan to have voice recognition (VR) systems. VR software encompasses 4 core processes: spoken recognition of human speech, synthesis of human readable characters into speech, speaker identification and verification, and comprehension. Many software packages are available offering VR. All these packages should contain an interface with the radiology information system. The benefits include decreased turnaround time and cost savings. Its advantages include the transfer of secretarial duties to the radiologist with a result in decreased productivity. PMID:12867815

  12. Recognition of Sound Environment by a Bathroom Monitoring System

    NASA Astrophysics Data System (ADS)

    Komoguchi, Naoyuki; Yamane, Kenji; Tanaka, Shogo

    Developing a monitoring system for a bathroom is important to prevent aged persons from accidents. The authors previously developed a bathroom monitoring system using an acoustic sensor which measured the water level of a bathtub and the temperature and also recognized the sound environment. The sound environment was however occasionally mis-recognized with the system. The present paper proposes a new method which recognizes the sound environment in the bathroom more accurately. Experiments demonstrate the effectiveness of the method.

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

    ERIC Educational Resources Information Center

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

    2016-01-01

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

  14. LARGE SCALE EVALUATION OF A PATTERN RECOGNITION/EXPERT SYSTEM FOR MASS SPECTRAL MOLECULAR WEIGHT ESTIMATION

    EPA Science Inventory

    A fast, personal-computer based method of estimating molecular weights of organic compounds from low resolution mass I spectra has been thoroughly evaluated. he method is based on a rule-based pattern,recognition/expert system approach which uses empirical linear corrections whic...

  15. SIFT-based error compensation for ear feature matching and recognition system

    NASA Astrophysics Data System (ADS)

    Jiang, Jingying; Zhang, Qi; Ma, Congcong; Lu, Junsheng; Xu, Kexin

    2015-03-01

    The current ear feature matching and recognition system, based on Scale Invariant Feature Transform (SIFT) image matching algorithm, can realize the human ear feature matching and detect the displacement of the human ear so as to reproduce the human ear position and posture. However, due to the influence of image acquisition equipment performance and lighting conditions, too dark or too bright background could bring the locally underexposed or overexposed image. This could result in the loss of some image details so as to make it impossible to identity the image and the recognition rate would be reduced. In this talk, the application of image gray level normalization processing can reduce the sensitivity of imaging to light intensity. Accordingly, it will greatly improve the recognition rate of human ears. Furthermore, it has been found that even if the object is stationary, the image matching results still have certain fluctuation changes, which could be caused by the system error. In order to reduce the error, the Background-based Compensation Model (BCM) has been established based on the investigation of the system error brought by the working environment changes. The results show that, BCM can be used to compensate the system errors of ear recognition matching and further improve the matching accuracy of human ear.

  16. Does Perceived Race Affect Discrimination and Recognition of Ambiguous-Race Faces? A Test of the Sociocognitive Hypothesis

    ERIC Educational Resources Information Center

    Rhodes, Gillian; Lie, Hanne C.; Ewing, Louise; Evangelista, Emma; Tanaka, James W.

    2010-01-01

    Discrimination and recognition are often poorer for other-race than own-race faces. These other-race effects (OREs) have traditionally been attributed to reduced perceptual expertise, resulting from more limited experience, with other-race faces. However, recent findings suggest that sociocognitive factors, such as reduced motivation to…

  17. A Novel Word Based Arabic Handwritten Recognition System Using SVM Classifier

    NASA Astrophysics Data System (ADS)

    Khalifa, Mahmoud; Bingru, Yang

    Every language script has its structure, characteristic, and feature. Character based word recognition depends on the feature available to be extracted from character. Word based script recognition overcome the problem of character segmenting and can be applied for several languages (Arabic, Urdu, Farsi... est.). In this paper Arabic handwritten is classified as word based system. Firstly, words segmented and normalized in size to fit the DCT input. Then extract feature characteristic by computing the Euclidean distance between pairs of objects in n-by-m data matrix X. Based on the point's operator of extrema, feature was extracted. Then apply one to one-Class Support Vector Machines (SVMs) as a discriminative framework in order to address feature classification. The approach was tested with several public databases and we get high efficiency rate recognition.

  18. Multiple ANN Recognizers for Adaptive Recognition of the Speech of Dysarthric Patients in AAL Systems.

    PubMed

    Nagy, Gabriella; Kutor, Laszlo

    2015-01-01

    People suffering from neuromuscular disorders are one of the main target groups of speech-controlled Ambient Assisted Living systems. However, the speech of these patients is often distorted because of the dysarthric symptoms of the disease. The dysarthria is known to become worse as the disease progresses. We propose a framework for an adaptive speech recognition system that may be able to follow the slow deterioration of speech quality without risking the accuracy of the system from incorrect data. PMID:26294603

  19. Data management in pattern recognition and image processing systems

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

  20. Neuro-parity pattern recognition system and method

    SciTech Connect

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

    2000-01-01

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

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

    PubMed

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

    2013-06-01

    This article presents the viability analysis and the development of heart disease identification embedded system. It offers a time reduction on electrocardiogram - ECG signal processing by reducing the amount of data samples, without any significant loss. The goal of the developed system is the analysis of heart signals. The ECG signals are applied into the system that performs an initial filtering, and then uses a Gustafson-Kessel fuzzy clustering algorithm for the signal classification and correlation. The classification indicated common heart diseases such as angina, myocardial infarction and coronary artery diseases. The system uses the European electrocardiogram ST-T Database (EDB) as a reference for tests and evaluation. The results prove the system can perform the heart disease detection on a data set reduced from 213 to just 20 samples, thus providing a reduction to just 9.4% of the original set, while maintaining the same effectiveness. This system is validated in a Xilinx Spartan(®)-3A FPGA. The field programmable gate array (FPGA) implemented a Xilinx Microblaze(®) Soft-Core Processor running at a 50MHz clock rate. PMID:23394802

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

    NASA Astrophysics Data System (ADS)

    Mohd Zin, Zalhan; Ibrahim, Ratnawati

    2011-06-01

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

  3. A region finding method to remove the noise from the images of the human hand gesture recognition system

    NASA Astrophysics Data System (ADS)

    Khan, Muhammad Jibran; Mahmood, Waqas

    2015-12-01

    The performance of the human hand gesture recognition systems depends on the quality of the images presented to the system. Since these systems work in real time environment the images may be corrupted by some environmental noise. By removing the noise the performance of the system can be enhanced. So far different noise removal methods have been presented in many researches to eliminate the noise but all have its own limitations. We have presented a region finding method to deal with the environmental noise that gives better results and enhances the performance of the human hand gesture recognition systems so that the recognition rate of the system can be improved.

  4. Enhancement of Prediction for Manufacturing System Using Bayesian Decision Recognition

    NASA Astrophysics Data System (ADS)

    Jianhua, Yang; Fujimoto, Yasutaka

    A decision model stemmed from Bayesian theorem is proposed to describe the process of decision making for job sequence in manufacturing system. The construction of feature vector is firstly discussed with respect to the manufacturing system’s characteristic. Then a non-parametric model is employed to deal with general distribution for decision acquisition, where a binary division methodology is developed to limit the size of non-parametric model, including elimination of irrelevant features. At last, a PCB manufacturing system is given to demonstrate the efficiency of the model.

  5. Bimusicalism: The Implicit Dual Enculturation of Cognitive and Affective Systems.

    PubMed

    Wong, Patrick C M; Roy, Anil K; Margulis, Elizabeth Hellmuth

    2009-12-01

    One prominent example of globalization and mass cultural exchange is bilingualism, whereby world citizens learn to understand and speak multiple languages. Music, similar to language, is a human universal, and subject to the effects of globalization. In two experiments, we asked whether bimusicalism exists as a phenomenon, and whether it can occur even without explicit formal training and extensive music-making. Everyday music listeners who had significant exposure to music of both Indian (South Asian) and Westerners traditions (IW listeners) and listeners who had experience with only Indian or Western culture (I or W listeners) participated in recognition memory and tension judgment experiments where they listened to Western and Indian music. We found that while I and W listeners showed an in-culture bias, IW listeners showed equal responses to music from both cultures, suggesting that dual mental and affective sensitivities can be extended to a nonlinguistic domain. PMID:20657798

  6. Bimusicalism: The Implicit Dual Enculturation of Cognitive and Affective Systems

    PubMed Central

    Wong, Patrick C. M.; Roy, Anil K.; Margulis, Elizabeth Hellmuth

    2010-01-01

    One prominent example of globalization and mass cultural exchange is bilingualism, whereby world citizens learn to understand and speak multiple languages. Music, similar to language, is a human universal, and subject to the effects of globalization. In two experiments, we asked whether bimusicalism exists as a phenomenon, and whether it can occur even without explicit formal training and extensive music-making. Everyday music listeners who had significant exposure to music of both Indian (South Asian) and Westerners traditions (IW listeners) and listeners who had experience with only Indian or Western culture (I or W listeners) participated in recognition memory and tension judgment experiments where they listened to Western and Indian music. We found that while I and W listeners showed an in-culture bias, IW listeners showed equal responses to music from both cultures, suggesting that dual mental and affective sensitivities can be extended to a nonlinguistic domain. PMID:20657798

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  8. The research on pattern recognition in distributed fiber vibrant sensor system

    NASA Astrophysics Data System (ADS)

    Wu, Hongyan; Zhao, Dong; Xu, Haiyan

    2011-09-01

    Distributed Fiber Vibrant Sensor System is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring vibration and sound signals. Position determination analysis toward this system is popular in previous papers, but pattern recognition of the output signals of the sensor has been missed for a long time. This function turns to critical especially when it is used for real security project in which quick response to intrusion is a must. After pre-processing the output signal of the system, a MFCC-based approach is provided in this paper to extract features of the sensing signals, which could be used for pattern recognition in real project, and the approach is proved by large practical experiments and projects.

  9. Systematic Approach for Validation of X-Ray Automatic Defect Recognition Systems

    SciTech Connect

    Navalgund, Megha; Venkatachalam, Rajashekar; Asati, Mahesh; Venugopal, Manoharan

    2007-03-21

    With the advent of digital radiography, there has been a gradual shift from operators viewing images to find defects to totally automated defect recognition (ADR) systems. This has resulted in reduced operator subjectivity, reduced operator fatigue, and increased productivity. These automated defect recognition solutions are based on reference or non-reference based approaches or a combination of both. There exists some amount of uncertainty or reluctance to accept automated systems in view of no systematic quantified metrics available on performance of these ADR systems in comparison to human operators. This paper describes the metrics that one could follow to quantify the performance of ADR systems such as detectability for different defect types and sizes, accuracy, false call rate, robustness to various noise levels etc., As it might be difficult to have images with defects of various sizes, shapes, contrast and noise levels, a methodology to generate images with simulated defects with variability's in parameters such as size, shape, contrast to noise ratio etc., is demonstrated. This can be used to generate probability of detection estimates for different defect types and geometries. This will result in establishing confidence limits for ADR systems and can be used to judge if it would meet specific customer requirement. This would facilitate increase in the acceptability of ADR systems over current manual defect recognition systems for applications in various industries such as Castings, Oil and Gas, Aviation etc.

  10. Learning task affects ERP-correlates of the own-race bias, but not recognition memory performance.

    PubMed

    Stahl, Johanna; Wiese, Holger; Schweinberger, Stefan R

    2010-06-01

    People are generally better in recognizing faces from their own ethnic group as opposed to faces from another ethnic group, a finding which has been interpreted in the context of two opposing theories. Whereas perceptual expertise theories stress the role of long-term experience with one's own ethnic group, race feature theories assume that the processing of an other-race-defining feature triggers inferior coding and recognition of faces. The present study tested these hypotheses by manipulating the learning task in a recognition memory test. At learning, one group of participants categorized faces according to ethnicity, whereas another group rated facial attractiveness. Subsequent recognition tests indicated clear and similar own-race biases for both groups. However, ERPs from learning and test phases demonstrated an influence of learning task on neurophysiological processing of own- and other-race faces. While both groups exhibited larger N170 responses to Asian as compared to Caucasian faces, task-dependent differences were seen in a subsequent P2 ERP component. Whereas the P2 was more pronounced for Caucasian faces in the categorization group, this difference was absent in the attractiveness rating group. The learning task thus influences early face encoding. Moreover, comparison with recent research suggests that this attractiveness rating task influences the processes reflected in the P2 in a similar manner as perceptual expertise for other-race faces does. By contrast, the behavioural own-race bias suggests that long-term expertise is required to increase other-race face recognition and hence attenuate the own-race bias. PMID:20362599

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

    SciTech Connect

    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.

  12. Automated inspection of micro-defect recognition system for color filter

    NASA Astrophysics Data System (ADS)

    Jeffrey Kuo, Chung-Feng; Peng, Kai-Ching; Wu, Han-Cheng; Wang, Ching-Chin

    2015-07-01

    This study focused on micro-defect recognition and classification in color filters. First, six types of defects were examined, namely grain, black matrix hole (BMH), indium tin oxide (ITO) defect, missing edge and shape (MES), highlights, and particle. Orthogonal projection was applied to locate each pixel in a test image. Then, an image comparison was performed to mark similar blocks on the test image. The block that best resembled the template was chosen as the new template (or matching adaptive template). Afterwards, image subtraction was applied to subtract the pixels at the same location in each block of the test image from the matching adaptive template. The control limit law employed logic operation to separate the defect from the background region. The complete defect structure was obtained by the morphology method. Next, feature values, including defect gray value, red, green, and blue (RGB) color components, and aspect ratio were obtained as the classifier input. The experimental results showed that defect recognition could be completed as fast as 0.154 s using the proposed recognition system and software. In micro-defect classification, back-propagation neural network (BPNN) and minimum distance classifier (MDC) served as the defect classification decision theories for the five acquired feature values. To validate the proposed system, this study used 41 defects as training samples, and treated the feature values of 307 test samples as the BPNN classifier inputs. The total recognition rate was 93.7%. When an MDC was used, the total recognition rate was 96.8%, indicating that the MDC method is feasible in applying automatic optical inspection technology to classify micro-defects of color filters. The proposed system is proven to successfully improve the production yield and lower costs.

  13. Assessing Affective Learning Using a Student Response System

    ERIC Educational Resources Information Center

    Rimland, Emily

    2013-01-01

    Affective learning relates to students' attitudes, emotions, and feelings. This study focuses on measuring affective learning during library instruction by using a student response system. Participants were undergraduate students who received course-related library instruction for a research assignment. Students rated their confidence levels…

  14. Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System

    NASA Astrophysics Data System (ADS)

    Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki

    In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

  15. A history-taking system that uses continuous speech recognition.

    PubMed Central

    Johnson, K.; Poon, A.; Shiffman, S.; Lin, R.; Fagan, L.

    1992-01-01

    Q-MED is an automated history-taking system that uses speaker-independent continuous speech as its main interface modality. Q-MED is designed to allow a patient to enter her basic symptoms by engaging in a dialog with the program. Error-recovery mechanisms help to eliminate findings resulting from misrecognitions or incorrect parses. An evaluation of the natural language parser that Q-MED uses to map user utterances to findings showed an overall semantic accuracy of 87 percent; Q-MED asks more specific questions to capture findings that were not volunteered, or that were unable to be parsed in their initial, open-ended form. PMID:1482973

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

    NASA Astrophysics Data System (ADS)

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

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

  17. RAPTOR: radar plus thermal observation and recognition system

    NASA Astrophysics Data System (ADS)

    Charlesworth, Peter D.

    1995-09-01

    Typical targets to be detected in ground surveillance scenarios have two common properties that are physically distinct, motion and radiation. This applies to pedestrians, vehicles, trucks and light aircraft. Infrared sensors can be used for the detection of radiating bodies through the application of image processing techniques and Doppler radar is an excellent detector of radial body motion. RAPTOR is a system whose aim is to produce a ground surveillance device with higher detection performance and lower false and nuisance alarm rates than possible with either or both sensor types operating alone. RAPTOR combines two complementary sensors, an infrared imager and a pulsed Doppler radar, which automatically detect targets using different physical phenomena and then uses data fusion techniques to enhance the automatic target detection performance. The fusion process includes alignment, correlation, association, target data processing and multisensor management. RAPTOR uses the two sensors in parallel, bore sighted on a single rotational platform. Both sensors concurrently scan the spatial volume and the individual target detection results, 'soft-targets,' are combined using data fusion algorithms to generate a confirmed set of targets, 'hard-targets.'

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

    PubMed Central

    Gasparrini, Samuele

    2016-01-01

    The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed. PMID:27069469

  19. A survey on acoustic signature recognition and classification techniques for persistent surveillance systems

    NASA Astrophysics Data System (ADS)

    Shirkhodaie, Amir; Alkilani, Amjad

    2012-06-01

    Application of acoustic sensors in Persistent Surveillance Systems (PSS) has received considerable attention over the last two decades because they can be rapidly deployed and have low cost. Conventional utilization of acoustic sensors in PSS spans a wide range of applications including: vehicle classification, target tracking, activity understanding, speech recognition, shooter detection, etc. This paper presents a current survey of physics-based acoustic signature classification techniques for outdoor sounds recognition and understanding. Particularly, this paper focuses on taxonomy and ontology of acoustic signatures resulted from group activities. The taxonomy and supportive ontology considered include: humanvehicle, human-objects, and human-human interactions. This paper, in particular, exploits applicability of several spectral analysis techniques as a means to maximize likelihood of correct acoustic source detection, recognition, and discrimination. Spectral analysis techniques based on Fast Fourier Transform, Discrete Wavelet Transform, and Short Time Fourier Transform are considered for extraction of features from acoustic sources. In addition, comprehensive overviews of most current research activities related to scope of this work are presented with their applications. Furthermore, future potential direction of research in this area is discussed for improvement of acoustic signature recognition and classification technology suitable for PSS applications.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  1. Reliable emotion recognition system based on dynamic adaptive fusion of forehead biopotentials and physiological signals.

    PubMed

    Khezri, Mahdi; Firoozabadi, Mohammad; Sharafat, Ahmad Reza

    2015-11-01

    In this study, we proposed a new adaptive method for fusing multiple emotional modalities to improve the performance of the emotion recognition system. Three-channel forehead biosignals along with peripheral physiological measurements (blood volume pressure, skin conductance, and interbeat intervals) were utilized as emotional modalities. Six basic emotions, i.e., anger, sadness, fear, disgust, happiness, and surprise were elicited by displaying preselected video clips for each of the 25 participants in the experiment; the physiological signals were collected simultaneously. In our multimodal emotion recognition system, recorded signals with the formation of several classification units identified the emotions independently. Then the results were fused using the adaptive weighted linear model to produce the final result. Each classification unit is assigned a weight that is determined dynamically by considering the performance of the units during the testing phase and the training phase results. This dynamic weighting scheme enables the emotion recognition system to adapt itself to each new user. The results showed that the suggested method outperformed conventional fusion of the features and classification units using the majority voting method. In addition, a considerable improvement, compared to the systems that used the static weighting schemes for fusing classification units, was also shown. Using support vector machine (SVM) and k-nearest neighbors (KNN) classifiers, the overall classification accuracies of 84.7% and 80% were obtained in identifying the emotions, respectively. In addition, applying the forehead or physiological signals in the proposed scheme indicates that designing a reliable emotion recognition system is feasible without the need for additional emotional modalities. PMID:26253158

  2. Surface acoustic wave sensor array system for trace organic vapor detection using pattern recognition analysis

    NASA Astrophysics Data System (ADS)

    Rose-Pehrsson, Susan L.; Grate, Jay W.; Klusty, Mark

    1993-03-01

    A sensor system using surface acoustic wave (SAW) vapor sensors has been fabricated and tested against hazardous organic vapors, simulants of these vapors, and potential background vapors. The vapor tests included two- and three-component mixtures, and covered a wide relative humidity range. The sensor system was compared of four SAW devices coated with different sorbent materials with different vapor selectivities. Preconcentrators were included to improve sensitivity. The vapor experiments were organized into a large data set analyzed using pattern recognition techniques. Pattern recognition algorithms were developed to identify two different classes of hazards. The algorithms were verified against a second data set not included in the training. Excellent sensitivity was achieved by the sensor coatings, and the pattern recognition analysis, and was also examined by the preconcentrators. The system can detect hazardous vapors of interest in the ppb range even in varying relative humidity and in the presence of background vapors. The system does not false alarm to a variety of other vapors including gasoline, jet fuel, diesel fuel and cigarette smoke.

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

    NASA Astrophysics Data System (ADS)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

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

  4. Face Recognition System for Set-Top Box-Based Intelligent TV

    PubMed Central

    Lee, Won Oh; Kim, Yeong Gon; Hong, Hyung Gil; Park, Kang Ryoung

    2014-01-01

    Despite the prevalence of smart TVs, many consumers continue to use conventional TVs with supplementary set-top boxes (STBs) because of the high cost of smart TVs. However, because the processing power of a STB is quite low, the smart TV functionalities that can be implemented in a STB are very limited. Because of this, negligible research has been conducted regarding face recognition for conventional TVs with supplementary STBs, even though many such studies have been conducted with smart TVs. In terms of camera sensors, previous face recognition systems have used high-resolution cameras, cameras with high magnification zoom lenses, or camera systems with panning and tilting devices that can be used for face recognition from various positions. However, these cameras and devices cannot be used in intelligent TV environments because of limitations related to size and cost, and only small, low cost web-cameras can be used. The resulting face recognition performance is degraded because of the limited resolution and quality levels of the images. Therefore, we propose a new face recognition system for intelligent TVs in order to overcome the limitations associated with low resource set-top box and low cost web-cameras. We implement the face recognition system using a software algorithm that does not require special devices or cameras. Our research has the following four novelties: first, the candidate regions in a viewer's face are detected in an image captured by a camera connected to the STB via low processing background subtraction and face color filtering; second, the detected candidate regions of face are transmitted to a server that has high processing power in order to detect face regions accurately; third, in-plane rotations of the face regions are compensated based on similarities between the left and right half sub-regions of the face regions; fourth, various poses of the viewer's face region are identified using five templates obtained during the initial user

  5. Affective Neuronal Selection: The Nature of the Primordial Emotion Systems

    PubMed Central

    Toronchuk, Judith A.; Ellis, George F. R.

    2013-01-01

    Based on studies in affective neuroscience and evolutionary psychiatry, a tentative new proposal is made here as to the nature and identification of primordial emotional systems. Our model stresses phylogenetic origins of emotional systems, which we believe is necessary for a full understanding of the functions of emotions and additionally suggests that emotional organizing systems play a role in sculpting the brain during ontogeny. Nascent emotional systems thus affect cognitive development. A second proposal concerns two additions to the affective systems identified by Panksepp. We suggest there is substantial evidence for a primary emotional organizing program dealing with power, rank, dominance, and subordination which instantiates competitive and territorial behavior and is an evolutionary contributor to self-esteem in humans. A program underlying disgust reactions which originally functioned in ancient vertebrates to protect against infection and toxins is also suggested. PMID:23316177

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  7. Classification of fragments of objects by the Fourier masks pattern recognition system

    NASA Astrophysics Data System (ADS)

    Barajas-García, Carolina; Solorza-Calderón, Selene; Álvarez-Borrego, Josué

    2016-05-01

    The automation process of the pattern recognition for fragments of objects is a challenge to humanity. For humans it is relatively easy to classify the fragment of some object even if it is isolated and perhaps this identification could be more complicated if it is partially overlapped by other object. However, the emulation of the functions of the human eye and brain by a computer is not a trivial issue. This paper presents a pattern recognition digital system based on Fourier binary rings masks in order to classify fragments of objects. The system is invariant to position, scale and rotation, and it is robust in the classification of images that have noise. Moreover, it classifies images that present an occlusion or elimination of approximately 50% of the area of the object.

  8. Ageing affects event-related potentials and brain oscillations: a behavioral and electrophysiological study using a haptic recognition memory task.

    PubMed

    Sebastián, Manuel; Reales, José M; Ballesteros, Soledad

    2011-12-01

    In this electrophysiological study, we investigated the effects of ageing on recognition memory for three-dimensional (3D) familiar objects presented to touch in a continuous paradigm. To examine changes in event-related potentials (ERPs) and brain oscillations, we recorded the EEGs of healthy groups of young (n=14; mean age=32.3 years) and older adults (n=14; mean age=65.1). Both age groups exhibited similar accuracy and exploration times when making old-new judgments. Young and older participants showed a marginally significant ERP old/new effect widely distributed over the scalp between 550-750 ms. In addition, the elders showed lower amplitude than younger participants within 1200-1500 ms. There were age-related differences in brain oscillations as measured by event-related spectral perturbation (ERSP). Older adults showed greater alpha and beta power reductions than young participants, suggesting the recruitment of additional neural resources. In contrast, the two age groups showed a reliable old/new effect in the theta band that temporarily overlapped the ERP old/new effect. The present results suggest that despite similar behavioral performance, the young and older adults recruited different neural resources to perform a haptic recognition task. PMID:22027172

  9. Human action recognition using meta-cognitive neuro-fuzzy inference system.

    PubMed

    Subramanian, K; Suresh, S

    2012-12-01

    We propose a sequential Meta-Cognitive learning algorithm for Neuro-Fuzzy Inference System (McFIS) to efficiently recognize human actions from video sequence. Optical flow information between two consecutive image planes can represent actions hierarchically from local pixel level to global object level, and hence are used to describe the human action in McFIS classifier. McFIS classifier and its sequential learning algorithm is developed based on the principles of self-regulation observed in human meta-cognition. McFIS decides on what-to-learn, when-to-learn and how-to-learn based on the knowledge stored in the classifier and the information contained in the new training samples. The sequential learning algorithm of McFIS is controlled and monitored by the meta-cognitive components which uses class-specific, knowledge based criteria along with self-regulatory thresholds to decide on one of the following strategies: (i) Sample deletion (ii) Sample learning and (iii) Sample reserve. Performance of proposed McFIS based human action recognition system is evaluated using benchmark Weizmann and KTH video sequences. The simulation results are compared with well known SVM classifier and also with state-of-the-art action recognition results reported in the literature. The results clearly indicates McFIS action recognition system achieves better performances with minimal computational effort. PMID:23186277

  10. Content-addressable holographic data storage system for invariant pattern recognition of gray-scale images.

    PubMed

    Joseph, Joby; Bhagatji, Alpana; Singh, Kehar

    2010-01-20

    Conventionally a holographic data storage system uses binary digital data as the input pages. We propose and demonstrate the use of a holographic data storage system for the purpose of invariant pattern recognition of gray-scale images. To improve the correlation accuracy for gray-scale images, we present a coding technique, phase Fourier transform (phase-FT) coding, to code a gray-scale image into a random and balanced digital binary image. In addition to the fact that a digital data page is obtained for incorporation into a holographic data storage system, this phase-FT coded image produces dc-free homogenized Fourier spectrum. This coded image can also be treated as an image for further processing, such as synthesis of distortion-invariant filters for invariant pattern recognition. A space-domain synthetic discriminant function (SDF) filter has been synthesized using these phase-FT coded images for rotation-invariant pattern recognition. Both simulation and experimental results are presented. The results show good correlation accuracy in comparison to correlation results obtained for SDF filter synthesized using the original gray-scale images themselves. PMID:20090813

  11. Real-time color/shape-based traffic signs acquisition and recognition system

    NASA Astrophysics Data System (ADS)

    Saponara, Sergio

    2013-02-01

    A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.

  12. Toward Computer-Aided Affective Learning Systems: A Literature Review

    ERIC Educational Resources Information Center

    Moridis, C. N.; Economides, A. A.

    2008-01-01

    The aim of this survey is to provide an overview of the various components of "computer aided affective learning systems." The research is classified into 3 main scientific areas that are integral parts of the development of these kinds of systems. The three main scientific areas are: i) emotions and their connection to learning; ii) affect…

  13. CULTURAL SYSTEM AFFECTS FRUIT QUALITY AND ANTIOXIDANT CAPACITY IN STRAWBERRIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cultural system [hill plasticulture (HC) vs. matted row (MR)] and genotypes interactions affected strawberry fruit quality. In general, fruit soluble content, total sugar, fructose, glucose, ascorbic acid, titratable acid and citric acid content were increased in the HC system. Fruit from HC also ...

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

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

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

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

    PubMed

    Freeh, M; Dewey, M; Brigham, L

    2001-06-01

    The Department of Radiology at the University of Utah Health Sciences Center has been in the process of transitioning from the traditional film-based department to a digital imaging department for the past 2 years. The department is now transitioning from the traditional method of dictating reports (dictation by radiologist to transcription to review and signing by radiologist) to a voice recognition system. The transition to digital operations will not be complete until we have the ability to directly interface the dictation process with the image review process. Voice recognition technology has advanced to the level where it can and should be an integral part of the new way of working in radiology and is an integral part of an efficient digital imaging department. The transition to voice recognition requires the task of identifying the product and the company that will best meet a department's needs. This report introduces the methods we used to evaluate the vendors and the products available as we made our purchasing decision. We discuss our evaluation method and provide a checklist that can be used by other departments to assist with their evaluation process. The criteria used in the evaluation process fall into the following major categories: user operations, technical infrastructure, medical dictionary, system interfaces, service support, cost, and company strength. Conclusions drawn from our evaluation process will be detailed, with the intention being to shorten the process for others as they embark on a similar venture. As more and more organizations investigate the many products and services that are now being offered to enhance the operations of a radiology department, it becomes increasingly important that solid methods are used to most effectively evaluate the new products. This report should help others complete the task of evaluating a voice recognition system and may be adaptable to other products as well. PMID:11442123

  16. Emotion Recognition with Eigen Features of Frequency Band Activities Embedded in Induced Brain Oscillations Mediated by Affective Pictures.

    PubMed

    Aydin, Serap; Demirtaş, Serdar; Ateş, Kahraman; Tunga, M Alper

    2016-05-01

    In this study, singular spectrum analysis (SSA) has been used for the first time in order to extract emotional features from well-defined electroencephalography (EEG) frequency band activities (BAs) so-called delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-16 Hz), beta (16-32 Hz), gamma (32-64 Hz). These five BAs were estimated by applying sixth-level multi-resolution wavelet decomposition (MRWD) with Daubechies wavelets (db-8) to single channel nonaveraged emotional EEG oscillations of 6 s for each scalp location over 16 recording sites (Fp1, Fp2, F3, F4, F7, F8, C3, C4, P3, P4, T3, T4, T5, T6, O1, O2). Every trial was mediated by different emotional stimuli which were selected from international affective picture system (IAPS) to induce emotional states such as pleasant (P), neutral (N), and unpleasant (UP). Largest principal components (PCs) of BAs were considered as emotional features and data mining approaches were used for the first time in order to classify both three different (P, N, UP) and two contrasting (P and UP) emotional states for 30 healthy controls. Emotional features extracted from gamma BAs (GBAs) for 16 recording sites provided the high classification accuracies of 87.1% and 100% for classification of three emotional states and two contrasting emotional states, respectively. In conclusion, we found the followings: (1) Eigenspectra of high frequency BAs in EEG are highly sensitive to emotional hemispheric activations, (2) emotional states are mostly mediated by GBA, (3) pleasant pictures induce the higher cortical activation in contrast to unpleasant pictures, (4) contrasting emotions induce opposite cortical activations, (5) cognitive activities are necessary for an emotion to occur. PMID:26971786

  17. Efficient live face detection to counter spoof attack in face recognition systems

    NASA Astrophysics Data System (ADS)

    Biswas, Bikram Kumar; Alam, Mohammad S.

    2015-03-01

    Face recognition is a critical tool used in almost all major biometrics based security systems. But recognition, authentication and liveness detection of the face of an actual user is a major challenge because an imposter or a non-live face of the actual user can be used to spoof the security system. In this research, a robust technique is proposed which detects liveness of faces in order to counter spoof attacks. The proposed technique uses a three-dimensional (3D) fast Fourier transform to compare spectral energies of a live face and a fake face in a mathematically selective manner. The mathematical model involves evaluation of energies of selective high frequency bands of average power spectra of both live and non-live faces. It also carries out proper recognition and authentication of the face of the actual user using the fringe-adjusted joint transform correlation technique, which has been found to yield the highest correlation output for a match. Experimental tests show that the proposed technique yields excellent results for identifying live faces.

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

    PubMed Central

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

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance. PMID:22438704

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

    NASA Astrophysics Data System (ADS)

    Hui, Zeng; Qiang, Li; Yu, Gu

    2016-02-01

    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 (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) 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. Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

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

    PubMed

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

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance. PMID:22438704

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

    PubMed

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

    2014-01-01

    For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system. PMID:24693243

  3. Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion

    PubMed Central

    2014-01-01

    For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system. PMID:24693243

  4. Spectral pattern recognition of controlled substances in street samples using artificial neural network system

    NASA Astrophysics Data System (ADS)

    Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

    2011-04-01

    The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

  5. Social hackers: integration in the host chemical recognition system by a paper wasp social parasite.

    PubMed

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

    2000-04-01

    Obligate social parasites in the social insects have lost the worker caste and the ability to establish nests. As a result, parasites must usurp a host nest, overcome the host recognition system, and depend on the host workers to rear their offspring. We analysed cuticular hydrocarbon profiles of live parasite females of the paper wasp social parasite Polistes sulcifer before and after usurpation of host nests, using the non-destructive technique of solid-phase micro-extraction. Our results reveal that hydrocarbon profiles of parasites change after usurpation of host nests to match the cuticular profile of the host species. Chemical evidence further shows that the parasite queen changes the odour of the nest by the addition of a parasite-specific hydrocarbon. We discuss the possible role of this in the recognition and acceptance of the parasite and its offspring in the host colony. PMID:10840803

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

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  8. Assessment of visual space recognition of patients with unilateral spatial neglect and visual field defects using a head mounted display system

    PubMed Central

    Sugihara, Shunichi; Tanaka, Toshiaki; Miyasaka, Tomoya; Izumi, Takashi; Shimizu, Koichi

    2016-01-01

    [Purpose] The purpose of this study was the development of a method for presenting diverse visual information and assessing visual space recognition using a new head mounted display (HMD) system. [Subjects] Eight patients: four with unilateral spatial neglect (USN) and four with visual field defects (VFD). [Methods] A test sheet was placed on a desk, and its image was projected on the display of the HMD. Then, space recognition assessment was conducted using a cancellation test and motion analysis of the eyeballs and head under four conditions with images reduced in size and shifted. [Results] Leftward visual search was dominant in VFD patients, while rightward visual search was dominant in USN patients. The angular velocity of leftward eye movement during visual search of the right sheet decreased in both patient types. Motion analysis revealed a tendency of VFD patients to rotate the head in the affected direction under the left reduction condition, whereas USN patients rotated it in the opposite direction of the neglect. [Conclusion] A new HMD system was developed for presenting diverse visual information and assessing visual space recognition which identified the differences in the disturbance of visual space recognition of VFD and USN patients were indicated. PMID:27065515

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

    NASA Astrophysics Data System (ADS)

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

    2005-10-01

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

  10. Unravelling glucan recognition systems by glycome microarrays using the designer approach and mass spectrometry.

    PubMed

    Palma, Angelina S; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S; Ciocchini, Andres E; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M G A; Mulloy, Barbara; Childs, Robert A; Feizi, Ten; Chai, Wengang

    2015-04-01

    Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure-function studies and their exploitation. We describe construction of a "glucome" microarray, the first sequence-defined glycome-scale microarray, using a "designer" approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear "homo" and "hetero" and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

  11. Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry*

    PubMed Central

    Palma, Angelina S.; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V.; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S.; Ciocchini, Andres E.; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M. G. A.; Mulloy, Barbara; Childs, Robert A.; Feizi, Ten; Chai, Wengang

    2015-01-01

    Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

  12. A bio-inspired system for spatio-temporal recognition in static and video imagery

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

    2007-04-01

    This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

  13. Multiview human activity recognition system based on spatiotemporal template for video surveillance system

    NASA Astrophysics Data System (ADS)

    Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

    2015-09-01

    An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

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

    PubMed Central

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

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What’s more, the improved algorithm can enhance the accuracy of blind recognition obviously. PMID:26154439

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

    NASA Astrophysics Data System (ADS)

    Caranica, Alexandru; Burileanu, Corneliu

    2015-02-01

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

  16. Real-time optical multiple object recognition and tracking system and method

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin (Inventor); Liu, Hua Kuang (Inventor)

    1987-01-01

    The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

  17. Design of a hand-shape acquisition and recognition system based on DSP

    NASA Astrophysics Data System (ADS)

    Li, Wenwen; Liu, Fu; Gao, Lei

    2013-10-01

    In this paper, we design a hand-shape image acquisition and processing system based on DSP for solving the problem of hand-shape recognition. Acquisition configuration was designed, and the key parts (encoder, decoder, memory chip etc.) are selected. And a new method for hand-shape recognition based on wavelet moment is presented to overcome some shortage in present method for hand shape recognition. Firstly, image processing including binary processing and segment of hand silhouette are used, and then translation and scale normalization algorithms is implemented on the palms and fingers image. After that the wavelet moment characteristics of image are extracted. At last, support vector is achieved by training 100 images data in images database, 10 testing images were selected randomly to verify validity and feasibility of algorithms. Experimental results indicate that the 10 testing images are all classified correctly. The new method of extracting hand shape wavelet moment as characteristic matrix is easy to realize with characteristic of high utility and accuracy, and solve the problem of translation, rotation and scaling during the image acquisition process without positioning aids.

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

    NASA Astrophysics Data System (ADS)

    Zuo, Fei; de With, Peter H.

    2003-06-01

    In a home environment, video surveillance employing face detection and recognition is attractive for new applications. Facial feature (e.g. eyes and mouth) localization in the face is an essential task for face recognition because it constitutes an indispensable step for face geometry normalization. This paper presents a new and efficient feature localization approach for real-time personal surveillance applications with low-quality images. The proposed approach consists of three major steps: (1) self-adaptive iris tracing, which is preceded by a trace-point selection process with multiple initializations to overcome the local convergence problem, (2) eye structure verification using an eye template with limited deformation freedom, and (3) eye-pair selection based on a combination of metrics. We have tested our facial feature localization method on about 100 randomly selected face images from the AR database and 30 face images downloaded from the Internet. The results show that our approach achieves a correct detection rate of 96%. Since our eye-selection technique does not involve time-consuming deformation processes, it yields relatively fast processing. The proposed algorithm has been successfully applied to a real-time home video surveillance system and proven to be an effective and computationally efficient face normalization method preceding the face recognition.

  19. Study on pattern recognition method based on fiber optic perimeter system

    NASA Astrophysics Data System (ADS)

    Xu, Haiyan; Zhang, Xuewu; Zhang, Zhuo; Li, Min

    2015-10-01

    All-fiber interferometer sensor system is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring and inspection. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, the universal steps in triggering pattern recognition is introduced, which includes signal characteristics extracting by accurate endpoint detecting, templates establishing by training, and pattern matching. By training the samples acquired in the laboratory, this paper uses the wavelet transformation to decompose the detection signals of the intrusion activities into sub-signals in different frequency bands with multi-resolution analysis. Then extracts the features of the above mentioned intrusions signals by frequency band energy and wavelet information entropy and the system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises such as windy and walk effectively. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

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

    PubMed

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%. PMID:9228583

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

    NASA Astrophysics Data System (ADS)

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

    1992-11-01

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

  2. An E-learning System based on Affective Computing

    NASA Astrophysics Data System (ADS)

    Duo, Sun; Song, Lu Xue

    In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

  3. Agent Based Affective Tutoring Systems: A Pilot Study

    ERIC Educational Resources Information Center

    Mao, Xia; Li, Zheng

    2010-01-01

    An important trend in the development of Intelligent tutoring systems (ITSs) has been that providing the student with a more personalized and friendly environment for learning. Many researchers now feel strongly that the ITSs would significantly improve performance if they could adapt to the affective state of the learner. This idea has spawned…

  4. Carelessness and Affect in an Intelligent Tutoring System for Mathematics

    ERIC Educational Resources Information Center

    San Pedro, Maria Ofelia Z.; de Baker, Ryan S. J.; Rodrigo, Ma. Mercedes T.

    2014-01-01

    We investigate the relationship between students' affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student's answer is wrong despite knowing the skill required to provide the correct answer. We…

  5. Factors Affecting Educational Innovation with in Class Electronic Response Systems

    ERIC Educational Resources Information Center

    Freeman, Mark; Bell, Amani; Comerton-Forde, Carole; Pickering, Joanne; Blayney, Paul

    2007-01-01

    This paper reports the use of Rogers' diffusion of innovation perspective to understand the factors affecting educational innovation decisions, specifically in regard to in class electronic response systems. Despite decreasing costs and four decades of research showing strong student support, academic adoption is limited. Using data collected from…

  6. Measurement of reach envelopes with a four-camera Selective Spot Recognition (SELSPOT) system

    NASA Technical Reports Server (NTRS)

    Stramler, J. H., Jr.; Woolford, B. J.

    1983-01-01

    The basic Selective Spot Recognition (SELSPOT) system is essentially a system which uses infrared LEDs and a 'camera' with an infrared-sensitive photodetector, a focusing lens, and some A/D electronics to produce a digital output representing an X and Y coordinate for each LED for each camera. When the data are synthesized across all cameras with appropriate calibrations, an XYZ set of coordinates is obtained for each LED at a given point in time. Attention is given to the operating modes, a system checkout, and reach envelopes and software. The Video Recording Adapter (VRA) represents the main addition to the basic SELSPOT system. The VRA contains a microprocessor and other electronics which permit user selection of several options and some interaction with the system.

  7. Receptor affinity and extracellular domain modifications affect tumor recognition by ROR1-specific chimeric antigen receptor T-cells

    PubMed Central

    Hudecek, Michael; Lupo-Stanghellini, Maria-Teresa; Kosasih, Paula L.; Sommermeyer, Daniel; Jensen, Michael C.; Rader, Christoph; Riddell, Stanley R.

    2013-01-01

    Purpose The adoptive transfer of T-cells modified to express a chimeric antigen receptor (CAR) comprised of an extracellular single chain antibody (scFV) fragment specific for a tumor cell surface molecule, and linked to an intracellular signaling module has activity in advanced malignancies. ROR1 is a tumor-associated molecule expressed on prevalent B-lymphoid and epithelial cancers, and is absent on normal mature B-cells and vital tissues, making it a candidate for CAR T-cell therapy. Experimental Design We constructed ROR1-CARs from scFVs with different affinities and containing extracellular IgG4-Fc spacer domains of different lengths, and evaluated the ability of T-cells expressing each CAR to recognize ROR1+ hematopoietic and epithelial tumors in vitro, and to eliminate human mantle cell lymphoma engrafted into immunodeficient mice. Results ROR1-CARs containing a short ‘Hinge-only’ extracellular spacer conferred superior lysis of ROR1+ tumor cells and induction of T-cell effector functions compared to CARs with long ‘Hinge-CH2-CH3’ spacers. CARs derived from a higher affinity scFV conferred maximum T-cell effector function against primary CLL and ROR1+ epithelial cancer lines in vitro without inducing activation induced T-cell death. T-cells modified with an optimal ROR1-CAR were equivalently effective as CD19-CAR modified T-cells in mediating regression of JeKo-1 mantle cell lymphoma in immunodeficient mice. Conclusions Our results demonstrate that customizing spacer design and increasing affinity of ROR1-CARs enhances T-cell effector function and recognition of ROR1+ tumors. T-cells modified with an optimized ROR1-CAR have significant anti-tumor efficacy in a preclinical model in vivo, suggesting they may be useful to treat ROR1+ tumors in clinical applications. PMID:23620405

  8. Illumination analysis of the digital pattern recognition system by Bessel masks and one-dimensional signatures

    NASA Astrophysics Data System (ADS)

    Solorza, S.; Álvarez-Borrego, J.

    2013-11-01

    The effects of illumination variations in digital images are a trend topic of the pattern recognition field. The luminance information of the objects help to classify them, however the environment illumination could cause a lot of problem if the system is not illumination invariant. Some applications of this topic include image and video quality, biometrics classification, etc. In this work an illumination analysis for a digital system invariant to position and rotation based on Fourier transform, Bessel masks, one-dimensional signatures and linear correlations are presented. The digital system was tested using a reference database of 21 fossil diatoms images of gray-scale and 307 x 307 pixels. The digital system has shown an excellent performance in the classification of 60,480 problem images which have different non-homogeneous illumination.

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

    NASA Astrophysics Data System (ADS)

    Dehnavi, Mohammad; Eshghi, Mohammad

    2012-12-01

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

  10. Recognition of maximum flooding events in mixed siliciclastic-carbonate systems: Key to global chronostratigraphic correlation

    USGS Publications Warehouse

    Mancini, E.A.; Tew, B.H.

    1997-01-01

    The maximum flooding event within a depositional sequence is an important datum for correlation because it represents a virtually synchronous horizon. This event is typically recognized by a distinctive physical surface and/or a significant change in microfossil assemblages (relative fossil abundance peaks) in siliciclastic deposits from shoreline to continental slope environments in a passive margin setting. Recognition of maximum flooding events in mixed siliciclastic-carbonate sediments is more complicated because the entire section usually represents deposition in continental shelf environments with varying rates of biologic and carbonate productivity versus siliciclastic influx. Hence, this event cannot be consistently identified simply by relative fossil abundance peaks. Factors such as siliciclastic input, carbonate productivity, sediment accumulation rates, and paleoenvironmental conditions dramatically affect the relative abundances of microfossils. Failure to recognize these complications can lead to a sequence stratigraphic interpretation that substantially overestimates the number of depositional sequences of 1 to 10 m.y. duration.

  11. Factors affecting the level of success of community information systems.

    PubMed

    Coombs, C R; Doherty, N F; Loan-Clarke, J

    1999-01-01

    The factors that influence the ultimate level of success or failure of systems development projects have received considerable attention in the academic literature. However, previous research has rarely targeted different instances of a common type of system within a homogeneous organisational sector. This paper presents the results of a survey of IM&T managers within Community Trusts to gain insights into the factors affecting the success of Community Information Systems. The results demonstrate that the most successful operational systems were thoroughly tested prior to implementation and enjoyed high levels of user and senior management commitment. Furthermore, it has been shown that there is a relationship between the level of organisational impact and systems success, with the most successful systems engendering changes to the host organisation's culture, level of empowerment and clinical working practices. In addition to being of academic interest, this research provides many important insights for practising IM&T managers. PMID:10747445

  12. Severe Traumatic Head Injury Affects Systemic Cytokine Expression

    PubMed Central

    LaPar, Damien J; Rosenberger, Laura H; Walters, Dustin M; Hedrick, Traci L; Swenson, Brian R; Young, Jeffrey S; Dossett, Lesly A; May, Addison K; Sawyer, Robert G

    2012-01-01

    Background The neuroimmunologic effect of traumatic head injury remains ill-defined. This study aimed to characterize systemic cytokine profiles among traumatically injured patients to assess the effect of traumatic head injury on the systemic inflammatory response. Study Design Over five years, 1,022 patients were evaluated from a multi-institutional trauma immunomodulatory database (TIMD). Patients were stratified by presence of severe head injury (SHI, Head ISS ≥ 4, n=335) versus non-severe head injury (NHI, Head ISS ≤ 3, n=687). Systemic cytokine expression was quantified by ELISA within 72 hours of admission. Patient factors, outcomes, and cytokine profiles were compared by univariate analyses. Results SHI patients were more severely injured with higher mortality despite similar ICU infection and ventilator associated pneumonia (VAP) rates. Expression of early pro-inflammatory cytokines, IL-6 (p<0.001) and tumor necrosis factor (TNF)-α (p=0.02), were higher among NHI patients, while expression of immunomodulatory cytokines, interferon-γ (p=0.01) and IL-12 (p=0.003), was higher in SHI patients. High TNF-α levels in NHI patients were associated with mortality (p=0.01), increased mechanical ventilation (p=0.02), and development of VAP (p=0.01). Alternatively, among SHI patients, high IL-2 levels were associated with survival, decreased mechanical ventilation, and absence of VAP. Conclusions The presence of severe traumatic head injury significantly alters systemic cytokine expression and exerts an immunomodulatory effect. Early recognition of these profiles may allow for targeted intervention to reduce patient morbidity and mortality. PMID:22342787

  13. Proposed study to determine potential flight applications and human factors design guidelines of voice recognition/synthesis systems

    NASA Technical Reports Server (NTRS)

    Bergeron, H. P.

    1983-01-01

    An effort to evaluate the human factors aspects and potential of voice recognition/synthesis techniques and the application of present and near-future (5 years) voice recognition/synthesis systems as a pilot/aircraft cockpit interface capability in an operational environment is discussed. The analysis will emphasize applications for single pilot instrument flight rules operations but will also include applications for other categories of aircraft with various levels of complexity.

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

    PubMed

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

    2014-07-01

    Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the bag-of-features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset. PMID:25014934

  15. Toward Design of an Environment-Aware Adaptive Locomotion-Mode-Recognition System

    PubMed Central

    Du, Lin; Zhang, Fan; Liu, Ming

    2013-01-01

    In this study, we aimed to improve the performance of a locomotion-mode-recognition system based on neuromuscular-mechanical fusion by introducing additional information about the walking environment. Linear-discriminant-analysis-based classifiers were first designed to identify a lower limb prosthesis user’s locomotion mode based on electromyographic signals recorded from residual leg muscles and ground reaction forces measured from the prosthetic pylon. Nine transfemoral amputees who wore a passive hydraulic knee or powered prosthetic knee participated in this study. Information about the walking terrain was simulated and modeled as prior probability based on the principle of maximum entropy and integrated into the discriminant functions of the classifier. When the correct prior knowledge of walking terrain was simulated, the classification accuracy for each locomotion mode significantly increased and no task transitions were missed. In addition, simulated incorrect prior knowledge did not significantly reduce system performance, indicating that our design is robust against noisy and imperfect prior information. Furthermore, these observations were independent of the type of prosthesis applied. The promising results in this study may assist the further development of an environment-aware adaptive system for locomotion-mode recognition for powered lower limb prostheses or orthoses. PMID:22996721

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

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

    PubMed Central

    Peternel, Klemen; Pogačnik, Matevž; Tavčar, Rudi; Kos, Andrej

    2012-01-01

    Stressors encountered in daily life may play an important role in personal well-being. Chronic stress can have a serious long-term impact on our physical as well as our psychological health, due to ongoing increased levels of the chemicals released in the ‘fight or flight’ response. The currently available stress assessment methods are usually not suitable for daily chronic stress measurement. The paper presents a context-aware chronic stress recognition system that addresses this problem. The proposed system obtains contextual data from various mobile sensors and other external sources in order to calculate the impact of ongoing stress. By identifying and visualizing ongoing stress situations of an individual user, he/she is able to modify his/her behavior in order to successfully avoid them. Clinical evaluation of the proposed methodology has been made in parallel by using electrodermal activity sensor. To the best of our knowledge, the system presented herein is the first one that enables recognition of chronic stress situations on the basis of user context. PMID:23202238

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

    NASA Astrophysics Data System (ADS)

    Yew, Chuu Tian; Suandi, Shahrel Azmin

    2012-04-01

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

  19. Toward design of an environment-aware adaptive locomotion-mode-recognition system.

    PubMed

    Du, Lin; Zhang, Fan; Liu, Ming; Huang, He

    2012-10-01

    In this study, we aimed to improve the performance of a locomotion-mode-recognition system based on neuromuscular-mechanical fusion by introducing additional information about the walking environment. Linear-discriminant-analysis-based classifiers were first designed to identify a lower limb prosthesis user's locomotion mode based on electromyographic signals recorded from residual leg muscles and ground reaction forces measured from the prosthetic pylon. Nine transfemoral amputees who wore a passive hydraulic knee or powered prosthetic knee participated in this study. Information about the walking terrain was simulated and modeled as prior probability based on the principle of maximum entropy and integrated into the discriminant functions of the classifier. When the correct prior knowledge of walking terrain was simulated, the classification accuracy for each locomotion mode significantly increased and no task transitions were missed. In addition, simulated incorrect prior knowledge did not significantly reduce system performance, indicating that our design is robust against noisy and imperfect prior information. Furthermore, these observations were independent of the type of prosthesis applied. The promising results in this study may assist the further development of an environment-aware adaptive system for locomotion-mode recognition for powered lower limb prostheses or orthoses. PMID:22996721

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

    PubMed

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

    2016-03-01

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

  1. The neural substrates of affective face recognition in patients with Hwa-Byung and healthy individuals in Korea.

    PubMed

    Lee, Byeong-Taek; Paik, Jong-Woo; Kang, Rhee-Hun; Chung, Sun-Yong; Kwon, Ho-In; Khang, Hyun-Soo; Lyoo, In Kyoon; Chae, Jeong-Ho; Kwon, Jung-Hye; Kim, Jong-Woo; Lee, Min-Soo; Ham, Byung-Joo

    2009-01-01

    Hwa-Byung (HB) is a Korean culture-bound psychiatric syndrome caused by the suppression of anger. HB patients have various psychological and somatic symptoms, such as chest discomfort, a sensation of heat, and the sensation of having an epigastric mass. In this study, we measured brain activity in HB patients and healthy individuals in response to affective facial stimuli. Using functional magnetic resonance imaging (fMRI), the current study measured neural responses to neutral, sad, and angry facial stimuli in 12 healthy individuals and 12 patients with HB. In response to all types of facial stimuli, HB patients showed increased activations in the lingual gyrus and fusiform gyrus compared with healthy persons, but they showed relatively lower activation in the thalamus. We also found that patients with HB showed lower activity in response to the neutral condition in the right ACC than healthy controls. The current study indicates that the suppression of affect results in aberrant function of the brain regions of the visual pathway, and functional impairment in the ACC may contribute to the pathophysiology of HB. PMID:18609429

  2. Fear recognition in the voice is modulated by unconsciously recognized facial expressions but not by unconsciously recognized affective pictures

    PubMed Central

    de Gelder, Beatrice; Pourtois, Gilles; Weiskrantz, Lawrence

    2002-01-01

    Multisensory integration is a powerful mechanism for increasing adaptive responses, as illustrated by binding of fear expressed in a face with fear present in a voice. To understand the role of awareness in intersensory integration of affective information we studied multisensory integration under conditions of conscious and nonconscious processing of the visual component of an audiovisual stimulus pair. Auditory-event-related potentials were measured in two patients (GY and DB) who were unable to perceive visual stimuli consciously because of striate cortex damage. To explore the role of conscious vision of audiovisual pairing, we also compared audiovisual integration in either naturalistic pairings (a facial expression paired with an emotional voice) or semantic pairings (an emotional picture paired with the same voice). We studied the hypothesis that semantic pairings, unlike naturalistic pairings, might require mediation by intact visual cortex and possibly by feedback to primary cortex from higher cognitive processes. Our results indicate that presenting incongruent visual affective information together with the voice translates as an amplitude decrease of auditory-event-related potentials. This effect obtains for both naturalistic and semantic pairings in the intact field, but is restricted to the naturalistic pairings in the blind field. PMID:11904455

  3. Global research priorities for infections that affect the nervous system.

    PubMed

    John, Chandy C; Carabin, Hélène; Montano, Silvia M; Bangirana, Paul; Zunt, Joseph R; Peterson, Phillip K

    2015-11-19

    Infections that cause significant nervous system morbidity globally include viral (for example, HIV, rabies, Japanese encephalitis virus, herpes simplex virus, varicella zoster virus, cytomegalovirus, dengue virus and chikungunya virus), bacterial (for example, tuberculosis, syphilis, bacterial meningitis and sepsis), fungal (for example, cryptococcal meningitis) and parasitic (for example, malaria, neurocysticercosis, neuroschistosomiasis and soil-transmitted helminths) infections. The neurological, cognitive, behavioural or mental health problems caused by the infections probably affect millions of children and adults in low- and middle-income countries. However, precise estimates of morbidity are lacking for most infections, and there is limited information on the pathogenesis of nervous system injury in these infections. Key research priorities for infection-related nervous system morbidity include accurate estimates of disease burden; point-of-care assays for infection diagnosis; improved tools for the assessment of neurological, cognitive and mental health impairment; vaccines and other interventions for preventing infections; improved understanding of the pathogenesis of nervous system disease in these infections; more effective methods to treat and prevent nervous system sequelae; operations research to implement known effective interventions; and improved methods of rehabilitation. Research in these areas, accompanied by efforts to implement promising technologies and therapies, could substantially decrease the morbidity and mortality of infections affecting the nervous system in low- and middle-income countries. PMID:26580325

  4. Global research priorities for infections that affect the nervous system

    PubMed Central

    John, Chandy C.; Carabin, Hélène; Montano, Silvia M.; Bangirana, Paul; Zunt, Joseph R.; Peterson, Phillip K.

    2015-01-01

    Infections that cause significant nervous system morbidity globally include viral (for example, HIV, rabies, Japanese encephalitis virus, herpes simplex virus, varicella zoster virus, cytomegalovirus, dengue virus and chikungunya virus), bacterial (for example, tuberculosis, syphilis, bacterial meningitis and sepsis), fungal (for example, cryptococcal meningitis) and parasitic (for example, malaria, neurocysticercosis, neuroschistosomiasis and soil-transmitted helminths) infections. The neurological, cognitive, behavioural or mental health problems caused by the infections probably affect millions of children and adults in low- and middle-income countries. However, precise estimates of morbidity are lacking for most infections, and there is limited information on the pathogenesis of nervous system injury in these infections. Key research priorities for infection-related nervous system morbidity include accurate estimates of disease burden; point-of-care assays for infection diagnosis; improved tools for the assessment of neurological, cognitive and mental health impairment; vaccines and other interventions for preventing infections; improved understanding of the pathogenesis of nervous system disease in these infections; more effective methods to treat and prevent nervous system sequelae; operations research to implement known effective interventions; and improved methods of rehabilitation. Research in these areas, accompanied by efforts to implement promising technologies and therapies, could substantially decrease the morbidity and mortality of infections affecting the nervous system in low- and middle-income countries. PMID:26580325

  5. Automatic intraductal breast carcinoma classification using a neural network-based recognition system.

    PubMed

    Reigosa, A; Hernández, L; Torrealba, V; Barrios, V; Montilla, G; Bosnjak, A; Araez, M; Turiaf, M; Leon, A

    1998-07-01

    A contour-based automatic recognition system was applied to classify intraductal breast carcinoma into high nuclear grade and low nuclear grade in a digitized histologic image. The image discriminating characteristics were selected by their invariability condition to rotation and translation. They were acquired from cellular contours information. The totally interconnected multilayer perceptron network architecture was selected, and it was trained with the error back propagation algorithm. Forty cases were analyzed by the system and the diagnoses were compared with that of pathologist consensus, obtaining agreement in 97.5% (p < .00001 of cases). The system may become a very useful tool for the pathologist in the definitive classification of intraductal carcinoma. PMID:21223442

  6. A Single Accelerometer based Wireless Embedded System for Predefined Dynamic Gesture Recognition

    NASA Astrophysics Data System (ADS)

    Parsani, Rahul; Singh, Karandeep

    The use of hand gestures provides an attractive alternative to cumbersome interface devices for human-computer interaction. A complete embedded system which facilitates the data acquisition, analysis, recognition, and the transmission wirelessly, of human dynamic gestures to a computer, is described. An intuitive algorithm for processing the accelerometer data was implemented and tested. This method permits all the analysis to be done by the embedded system processor. The system is capable of recognizing gestures involving a combination of straight line motions in three dimensions. These gestures are then used to control a host computer which executes tasks based on the gesture received. A sample application showing how the gestures can be mapped to the English alphabet is also shown.

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

    USGS Publications Warehouse

    Maddox, Brian G.; Swadley, Casey L.

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Norlin, B.; Manuilskiy, A.; Nilsson, H.-E.; Fröjdh, C.

    2004-09-01

    An energy sensitive imaging system like Medipix1 has proved to be promising in distinguishing different materials in an X-ray image of an object. We propose a general method utilising X-ray energy information for material recognition. For objects where the thickness of the materials is unknown, a convenient material parameter to identify is K=α1/α2, which is the ratio of the logarithms of the measured transmissions ln(t1)/ln(t2). If a database of the parameter K for different materials and energies is created, this method can be used for material recognition independent of the thickness of the materials.Series of images of an object consisting of aluminium and silicon were taken with different energy thresholds. The X-ray absorption for silicon and aluminium is very similar for the range 40-60keV and only differs for lower energies. The results show that it is possible to distinguish between aluminium and silicon on images achieved by Medipix1 using a standard dental source. By decreasing the spatial resolution a better contrast between the materials was achieved. The resolution of contrasts shown by the histograms was close to the limit of the system due to the statistical noise of the signal.

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

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.

    1988-02-01

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

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

    NASA Technical Reports Server (NTRS)

    Dhawan, Atam P.

    1988-01-01

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

  11. 77 FR 31043 - National Technical Systems, Inc.: Expiration of Recognition as a Nationally Recognized Testing...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-24

    ... recognition effective on the date of the notice (63 FR 68306). On June 21, 2007, OSHA renewed the recognition of NTS as an NRTL (see 72 FR 34320), which extended the recognition for a period of five years, to... Health Act of 1970 (29 U.S.C. 657(g)(2)), ] Secretary of Labor's Order No. 1-2012 (77 FR 3912), and...

  12. Major neurotransmitter systems in dorsal hippocampus and basolateral amygdala control social recognition memory.

    PubMed

    Garrido Zinn, Carolina; Clairis, Nicolas; Silva Cavalcante, Lorena Evelyn; Furini, Cristiane Regina Guerino; de Carvalho Myskiw, Jociane; Izquierdo, Ivan

    2016-08-16

    Social recognition memory (SRM) is crucial for reproduction, forming social groups, and species survival. Despite its importance, SRM is still relatively little studied. Here we examine the participation of the CA1 region of the dorsal hippocampus (CA1) and the basolateral amygdala (BLA) and that of dopaminergic, noradrenergic, and histaminergic systems in both structures in the consolidation of SRM. Male Wistar rats received intra-CA1 or intra-BLA infusions of different drugs immediately after the sample phase of a social discrimination task and 24-h later were subjected to a 5-min retention test. Animals treated with the protein synthesis inhibitor, anisomycin, into either the CA1 or BLA were unable to recognize the previously exposed juvenile (familiar) during the retention test. When infused into the CA1, the β-adrenoreceptor agonist, isoproterenol, the D1/D5 dopaminergic receptor antagonist, SCH23390, and the H2 histaminergic receptor antagonist, ranitidine, also hindered the recognition of the familiar juvenile 24-h later. The latter drug effects were more intense in the CA1 than in the BLA. When infused into the BLA, the β-adrenoreceptor antagonist, timolol, the D1/D5 dopamine receptor agonist, SKF38393, and the H2 histaminergic receptor agonist, ranitidine, also hindered recognition of the familiar juvenile 24-h later. In all cases, the impairment to recognize the familiar juvenile was abolished by the coinfusion of agonist plus antagonist. Clearly, both the CA1 and BLA, probably in that order, play major roles in the consolidation of SRM, but these roles are different in each structure vis-à-vis the involvement of the β-noradrenergic, D1/D5-dopaminergic, and H2-histaminergic receptors therein. PMID:27482097

  13. Factors Affecting Successful Implementation of Hospital Information Systems

    PubMed Central

    Farzandipur, Mehrdad; jeddi, Fatemeh Rangraz; Azimi, Esmaeil

    2016-01-01

    Background: Today, the use of information systems in health environments, like any other fields, is necessary and organizational managers are convinced to use these systems. However, managers’ satisfaction is not the only factor in successfully implementing these systems and failed information technology projects (IT) are reported despite the consent of the directors. Therefore, this study aims to determine the factors affecting the successful implementation of a hospital information system. Methods: The study was carried out as a descriptive method in 20 clinical hospitals that the hospital information system (HIS) was conducted in them. The clinical and paraclinical users of mentioned hospitals are the study group. 400 people were chosen as samples in scientific method and the data was collected using a questionnaire consisted of three main human, managerial and organizational, and technological factors, by questionnaire and interview. Then the data was scored in Likert scale (score of 1 to 5) and were analyzed using the SPSS software. Results: About 75 percent of the population were female, with average work experience of 10 years and the mean age was 30 years. The human factors affecting the success of hospital information system implementation achieved the mean score of 3.5, both organizational and managerial factors 2.9 and technological factors the mean of 3. Conclusion: Human factors including computer skills, perceiving usefulness and perceiving the ease of a hospital information system use are more effective on the acceptance and successful implementation of hospital information systems; then the technological factors play a greater role. It is recommended that for the successful implementation of hospital information systems, most of these factors to be considered PMID:27041811

  14. Real-time imaging systems' combination of methods to achieve automatic target recognition

    NASA Astrophysics Data System (ADS)

    Maraviglia, Carlos G.; Williams, Elmer F.; Pezzulich, Alan Z.

    1998-03-01

    Using a combination of strategies real time imaging weapons systems are achieving their goals of detecting their intended targets. The demands of acquiring a target in a cluttered environment in a timely manner with a high degree of confidence demands compromise be made as to having a truly automatic system. A combination of techniques such as dedicated image processing hardware, real time operating systems, mixes of algorithmic methods, and multi-sensor detectors are a forbearance of the unleashed potential of future weapons system and their incorporation in truly autonomous target acquisition. Elements such as position information, sensor gain controls, way marks for mid course correction, and augmentation with different imaging spectrums as well as future capabilities such as neural net expert systems and decision processors over seeing a fusion matrix architecture may be considered tools for a weapon system's achievement of its ultimate goal. Currently, acquiring a target in a cluttered environment in a timely manner with a high degree of confidence demands compromises be made as to having a truly automatic system. It is now necessary to include a human in the track decision loop, a system feature that may be long lived. Automatic Track Recognition will still be the desired goal in future systems due to the variability of military missions and desirability of an expendable asset. Furthermore, with the increasing incorporation of multi-sensor information into the track decision the human element's real time contribution must be carefully engineered.

  15. Comparison of bimodal and bilateral cochlear implant users on speech recognition with competing talker, music perception, affective prosody discrimination and talker identification

    PubMed Central

    Cullington, Helen E; Zeng, Fan-Gang

    2010-01-01

    Objectives Despite excellent performance in speech recognition in quiet, most cochlear implant users have great difficulty with speech recognition in noise, music perception, identifying tone of voice, and discriminating different talkers. This may be partly due to the pitch coding in cochlear implant speech processing. Most current speech processing strategies use only the envelope information; the temporal fine structure is discarded. One way to improve electric pitch perception is to utilize residual acoustic hearing via a hearing aid on the non-implanted ear (bimodal hearing). This study aimed to test the hypothesis that bimodal users would perform better than bilateral cochlear implant users on tasks requiring good pitch perception. Design Four pitch-related tasks were used: Hearing in Noise Test (HINT) sentences spoken by a male talker with a competing female, male, or child talker. Montreal Battery of Evaluation of Amusia. This is a music test with six subtests examining pitch, rhythm and timing perception, and musical memory. Aprosodia Battery. This has five subtests evaluating aspects of affective prosody and recognition of sarcasm. Talker identification using vowels spoken by ten different talkers (three male, three female, two boys, and two girls). Bilateral cochlear implant users were chosen as the comparison group. Thirteen bimodal and thirteen bilateral adult cochlear implant users were recruited; all had good speech perception in quiet. Results There were no significant differences between the mean scores of the bimodal and bilateral groups on any of the tests, although the bimodal group did perform better than the bilateral group on almost all tests. Performance on the different pitch-related tasks was not correlated, meaning that if a subject performed one task well they would not necessarily perform well on another. The correlation between the bimodal users' hearing threshold levels in the aided ear and their performance on these tasks was weak

  16. Recognition- and reactivity-based fluorescent probes for studying transition metal signaling in living systems.

    PubMed

    Aron, Allegra T; Ramos-Torres, Karla M; Cotruvo, Joseph A; Chang, Christopher J

    2015-08-18

    Metals are essential for life, playing critical roles in all aspects of the central dogma of biology (e.g., the transcription and translation of nucleic acids and synthesis of proteins). Redox-inactive alkali, alkaline earth, and transition metals such as sodium, potassium, calcium, and zinc are widely recognized as dynamic signals, whereas redox-active transition metals such as copper and iron are traditionally thought of as sequestered by protein ligands, including as static enzyme cofactors, in part because of their potential to trigger oxidative stress and damage via Fenton chemistry. Metals in biology can be broadly categorized into two pools: static and labile. In the former, proteins and other macromolecules tightly bind metals; in the latter, metals are bound relatively weakly to cellular ligands, including proteins and low molecular weight ligands. Fluorescent probes can be useful tools for studying the roles of transition metals in their labile forms. Probes for imaging transition metal dynamics in living systems must meet several stringent criteria. In addition to exhibiting desirable photophysical properties and biocompatibility, they must be selective and show a fluorescence turn-on response to the metal of interest. To meet this challenge, we have pursued two general strategies for metal detection, termed "recognition" and "reactivity". Our design of transition metal probes makes use of a recognition-based approach for copper and nickel and a reactivity-based approach for cobalt and iron. This Account summarizes progress in our laboratory on both the development and application of fluorescent probes to identify and study the signaling roles of transition metals in biology. In conjunction with complementary methods for direct metal detection and genetic and/or pharmacological manipulations, fluorescent probes for transition metals have helped reveal a number of principles underlying transition metal dynamics. In this Account, we give three recent

  17. Detection and location of multiple events by MARS. Final report. [Multiple Arrival Recognition System

    SciTech Connect

    Wang, J.; Masso, J.F.; Archambeau, C.B.; Savino, J.M.

    1980-09-01

    Seismic data from two explosions was processed using the Systems Science and Software MARS (Multiple Arrival Recognition System) seismic event detector in an effort to determine their relative spatial and temporal separation on the basis of seismic data alone. The explosions were less than 1.0 kilometer apart and were separated by less than 0.5 sec in origin times. The seismic data consisted of nine local accelerograms (r < 1.0 km) and four regional (240 through 400 km) seismograms. The MARS processing clearly indicates the presence of multiple explosions, but the restricted frequency range of the data inhibits accurate time picks and hence limits the precision of the event location.

  18. Speech recognition and understanding

    SciTech Connect

    Vintsyuk, T.K.

    1983-05-01

    This article discusses the automatic processing of speech signals with the aim of finding a sequence of works (speech recognition) or a concept (speech understanding) being transmitted by the speech signal. The goal of the research is to develop an automatic typewriter that will automatically edit and type text under voice control. A dynamic programming method is proposed in which all possible class signals are stored, after which the presented signal is compared to all the stored signals during the recognition phase. Topics considered include element-by-element recognition of words of speech, learning speech recognition, phoneme-by-phoneme speech recognition, the recognition of connected speech, understanding connected speech, and prospects for designing speech recognition and understanding systems. An application of the composition dynamic programming method for the solution of basic problems in the recognition and understanding of speech is presented.

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

    PubMed

    Smitha, K G; Vinod, A P

    2015-11-01

    Children with autism spectrum disorder have difficulty in understanding the emotional and mental states from the facial expressions of the people they interact. The inability to understand other people's emotions will hinder their interpersonal communication. Though many facial emotion recognition algorithms have been proposed in the literature, they are mainly intended for processing by a personal computer, which limits their usability in on-the-move applications where portability is desired. The portability of the system will ensure ease of use and real-time emotion recognition and that will aid for immediate feedback while communicating with caretakers. Principal component analysis (PCA) has been identified as the least complex feature extraction algorithm to be implemented in hardware. In this paper, we present a detailed study of the implementation of serial and parallel implementation of PCA in order to identify the most feasible method for realization of a portable emotion detector for autistic children. The proposed emotion recognizer architectures are implemented on Virtex 7 XC7VX330T FFG1761-3 FPGA. We achieved 82.3% detection accuracy for a word length of 8 bits. PMID:26239162

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

    DOE PAGESBeta

    Upadhyayula, Venkata K. K.; Ghoshroy, Soumitra; Nair, Vinod S.; Smith, Geoffrey B.; Mitchell, Martha C.; Deng, Shuguang

    2008-01-01

    Tmore » he possibility of using single-walled carbon nanotubes (SWCNTs) aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies.he Freundlich adsorption equilibrium constant ( k ) for S.aureus and E.coli determined from batch adsorption study was found to be 9 × 10 8 and 2 × 10 8  ml/g, respectively.he visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen.he results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability.his is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.« less

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

    NASA Astrophysics Data System (ADS)

    Zhou, Xuebing

    2007-04-01

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

  2. Characterization of the systems governing sexual and self-recognition in the white rot homobasidiomycete Amylostereum areolatum.

    PubMed

    van der Nest, Magriet A; Slippers, Bernard; Stenlid, Jan; Wilken, Pieter M; Vasaitis, Rimvis; Wingfield, Michael J; Wingfield, Brenda D

    2008-06-01

    This study considered the systems controlling sexual and self-recognition in Amylostereum areolatum, a homobasidiomycetous symbiont of the Sirex woodwasp. To investigate the structure and organization of these systems in A. areolatum, we identified a portion of a putative homologue (RAB1) of the pheromone receptor genes of Schizophyllum commune and Coprinus cinereus, and a portion of a putative homologue of the S. commune mitochondrial intermediate peptidase (mip) gene. Diagnostic DNA-based assays for mating-type were developed and their application confirmed that the fungus has a heterothallic tetrapolar mating system. Segregation analysis showed that RAB1 is linked to mating-type B, while mip is linked to mating-type A. The results of sexual and vegetative compatibility tests suggest that sexual recognition in A. areolatum is controlled by two multiallelic mat loci, while self-recognition is controlled by at least two multiallelic het loci. Therefore, despite the association of A. areolatum with the woodwasp and the unique mixture of sexual and clonal reproduction of the fungus, both recognition systems of the fungus appear to be similar in structure and function to those of other homobasidiomycetes. This is the first report regarding the genes controlling recognition of a homobasidiomycete involved in an obligate mutualistic relationship with an insect. PMID:18414867

  3. Cost-sensitive learning for emotion robust speaker recognition.

    PubMed

    Li, Dongdong; Yang, Yingchun; Dai, Weihui

    2014-01-01

    In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved. PMID:24999492

  4. Cost-Sensitive Learning for Emotion Robust Speaker Recognition

    PubMed Central

    Li, Dongdong; Yang, Yingchun

    2014-01-01

    In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved. PMID:24999492

  5. Analytical derivation of distortion constraints and their verification in a learning vector quantization-based target recognition system

    NASA Astrophysics Data System (ADS)

    Iftekharuddin, Khan M.; Razzaque, Mohammad A.

    2005-06-01

    We obtain a novel analytical derivation for distortion-related constraints in a neural network- (NN)-based automatic target recognition (ATR) system. We obtain two types of constraints for a realistic ATR system implementation involving 4-f correlator architecture. The first constraint determines the relative size between the input objects and input correlation filters. The second constraint dictates the limits on amount of rotation, translation, and scale of input objects for system implementation. We exploit these constraints in recognition of targets varying in rotation, translation, scale, occlusion, and the combination of all of these distortions using a learning vector quantization (LVQ) NN. We present the simulation verification of the constraints using both the gray-scale images and Defense Advanced Research Projects Agency's (DARPA's) Moving and Stationary Target Recognition (MSTAR) synthetic aperture radar (SAR) images with different depression and pose angles.

  6. RNA Recognition Motif-Containing Protein ORRM4 Broadly Affects Mitochondrial RNA Editing and Impacts Plant Development and Flowering1[OPEN

    PubMed Central

    Germain, Arnaud

    2016-01-01

    Plant RNA editosomes modify cytidines (C) to uridines (U) at specific sites in plastid and mitochondrial transcripts. Members of the RNA-editing factor interacting protein (RIP) family and Organelle RNA Recognition Motif-containing (ORRM) family are essential components of the Arabidopsis (Arabidopsis thaliana) editosome. ORRM2 and ORRM3 have been recently identified as minor mitochondrial editing factors whose silencing reduces editing efficiency at ∼6% of the mitochondrial C targets. Here we report the identification of ORRM4 (for organelle RRM protein 4) as a novel, major mitochondrial editing factor that controls ∼44% of the mitochondrial editing sites. C-to-U conversion is reduced, but not eliminated completely, at the affected sites. The orrm4 mutant exhibits slower growth and delayed flowering time. ORRM4 affects editing in a site-specific way, though orrm4 mutation affects editing of the entire transcript of certain genes. ORRM4 contains an RRM domain at the N terminus and a Gly-rich domain at the C terminus. The RRM domain provides the editing activity of ORRM4, whereas the Gly-rich domain is required for its interaction with ORRM3 and with itself. The presence of ORRM4 in the editosome is further supported by its interaction with RIP1 in a bimolecular fluorescence complementation assay. The identification of ORRM4 as a major mitochondrial editing factor further expands our knowledge of the composition of the RNA editosome and reveals that adequate mitochondrial editing is necessary for normal plant development. PMID:26578708

  7. SWIMMING PATTERN AS AN INDICATOR OF THE ROLES OF COPEPOD SENSORY SYSTEMS IN THE RECOGNITION OF FOOD

    EPA Science Inventory

    The roles of copepod sensory systems in the recognition of food were investigated using the 'Bugwatcher', a video-computer system designed to track and describe quantitatively the swimming patterns of aquatic organisms. Copepods acclimated, or non-acclimated to a chemosensory sti...

  8. Towards Evidence-Based, Quality-Controlled Health Promotion: The Dutch Recognition System for Health Promotion Interventions

    ERIC Educational Resources Information Center

    Brug, Johannes; van Dale, Djoeke; Lanting, Loes; Kremers, Stef; Veenhof, Cindy; Leurs, Mariken; van Yperen, Tom; Kok, Gerjo

    2010-01-01

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

  9. Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

    NASA Technical Reports Server (NTRS)

    Huang, Yiteng; Chen, Jingdong; Chen, Shaoyan

    2010-01-01

    A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

  10. High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

    2005-09-01

    Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

  11. Automatic recognition of piping system from laser scanned point clouds using normal-based region growing

    NASA Astrophysics Data System (ADS)

    Kawashima, K.; Kanai, S.; Date, H.

    2013-10-01

    In recent years, renovations of plant equipment have been more frequent, and constructing 3D as-built models of existing plants from large-scale laser scanned data is expected to make rebuilding processes more efficient. However, laser scanned data consists of enormous number of points, captures tangled objects and includes a high noise level, so that the manual reconstruction of a 3D model is very time-consuming. Among plant equipment, piping systems especially account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from large-scale laser scanned data of plants. The straight portion of pipes, connecting parts and connection relationship of the piping system can be automatically recognized. Normal-based region growing enables the extraction of points on the piping system. Eigen analysis of the normal tensor and cylinder surface fitting allows the algorithm to recognize portions of straight pipes. Tracing the axes of the piping system and interpolation of the axes can derive connecting parts and connection relationships between elements of the piping system. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. The recognition rate of straight pipes, elbows, junctions achieved 93%, 88% and 87% respectively.

  12. Dynamic Data Driven Applications Systems (DDDAS) modeling for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Blasch, Erik; Seetharaman, Guna; Darema, Frederica

    2013-05-01

    The Dynamic Data Driven Applications System (DDDAS) concept uses applications modeling, mathematical algorithms, and measurement systems to work with dynamic systems. A dynamic systems such as Automatic Target Recognition (ATR) is subject to sensor, target, and the environment variations over space and time. We use the DDDAS concept to develop an ATR methodology for multiscale-multimodal analysis that seeks to integrated sensing, processing, and exploitation. In the analysis, we use computer vision techniques to explore the capabilities and analogies that DDDAS has with information fusion. The key attribute of coordination is the use of sensor management as a data driven techniques to improve performance. In addition, DDDAS supports the need for modeling from which uncertainty and variations are used within the dynamic models for advanced performance. As an example, we use a Wide-Area Motion Imagery (WAMI) application to draw parallels and contrasts between ATR and DDDAS systems that warrants an integrated perspective. This elementary work is aimed at triggering a sequence of deeper insightful research towards exploiting sparsely sampled piecewise dense WAMI measurements - an application where the challenges of big-data with regards to mathematical fusion relationships and high-performance computations remain significant and will persist. Dynamic data-driven adaptive computations are required to effectively handle the challenges with exponentially increasing data volume for advanced information fusion systems solutions such as simultaneous target tracking and ATR.

  13. Pumping system fault detection and diagnosis utilizing pattern recognition and fuzzy inference techniques

    SciTech Connect

    Singer, R.M.; Gross, K.C. ); Humenik, K.E. . Dept. of Computer Science)

    1991-01-01

    An integrated fault detection and diagnostic system with a capability of providing extremely early detection of disturbances in a process through the analysis of the stochastic content of dynamic signals is described. The sequential statistical analysis of the signal noise (a pattern-recognition technique) that is employed has been shown to provide the theoretically shortest sampling time to detect disturbances and thus has the potential of providing incipient fault detection information to operators sufficiently early to avoid forced process shutdowns. This system also provides a diagnosis of the cause of the initiating fault(s) by a physical-model-derived rule-based expert system in which system and subsystem state uncertainties are handled using fuzzy inference techniques. This system has been initially applied to the monitoring of the operational state of the primary coolant pumping system on the EBR-II nuclear reactor. Early validation studies have shown that a rapidly developing incipient fault on centrifugal pumps can be detected well in advance of any changes in the nominal process signals. 17 refs., 6 figs.

  14. Portable Electronic Nose System for Identification of Synthesized Gasoline Using Metal Oxide Gas Sensor and Pattern Recognition

    NASA Astrophysics Data System (ADS)

    Kim, Young Wung; Park, Hong Bae; Lee, In Soo; Cho, Jung Hwan

    2011-09-01

    This paper describes a portable electronic nose (e-nose) system for use in the identification of synthesized gasoline, comprised of a single semiconductor type of gas sensor and pattern recognition neural networks. The designed e-nose system consists of a one-chip microcontroller, a pre-concentrator, and a gas sensor. Two different neural networks, a multilayer perceptron (MLP) neural network and a fuzzy ARTMAP neural network were applied to discriminate synthesized gasoline from normal gasoline. The results of the classification showed 100% and 85% recognition rates for the training data set and testing data set, respectively.

  15. The inheritance of female preference functions in a mate recognition system.

    PubMed Central

    Ritchie, M G

    2000-01-01

    Mate recognition systems (MRSs) play a major role in sexual selection and speciation, yet few studies have analysed both male and female components in detail. Here, female preference functions have been characterized for the tettigoniid bushcricket Ephippiger ephippiger, and the inheritance of male song and female preference functions followed in crosses between subspecies. Songs are disproportionately determined by sex-linked genes. However, there is no evidence for a role of maternally derived sex-linked genes in female preference or of maternal effects. At the genetic level, there is a mismatch between peak preferences and male song, consistent with an evolutionary history of persistent directional preferences. Such a pattern of inheritance could contribute to the process of speciation via the evolution of new MRSs. PMID:10722212

  16. Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

    PubMed Central

    Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

    2015-01-01

    Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant. PMID:25856329

  17. Lessons Learned from Implementation of Voice Recognition for Documentation in the Military Electronic Health Record System

    PubMed Central

    Hoyt, Robert; Yoshihashi, Ann

    2010-01-01

    This study evaluated the implementation of voice recognition (VR) for documenting outpatient encounters in the electronic health record (EHR) system at a military hospital and its 12 outlying clinics. Seventy-five clinicians volunteered to use VR, and 64 (85 percent) responded to an online questionnaire post implementation to identify variables related to VR continuance or discontinuance. The variables investigated were user characteristics, training experience, logistics, and VR utility. Forty-four respondents (69 percent) continued to use VR and overall felt that the software was accurate, was faster than typing, improved note quality, and permitted closing a patient encounter the same day. The discontinuation rate of 31 percent was related to location at an outlying clinic and perceptions of inadequacy of training, decreased productivity due to VR inaccuracies, and no improvement in note quality. Lessons learned can impact future deployment of VR in other military and civilian healthcare facilities. PMID:20697464

  18. Combining users' activity survey and simulators to evaluate human activity recognition systems.

    PubMed

    Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

    2015-01-01

    Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant. PMID:25856329

  19. 'Order from disorder sprung': recognition and regulation in the immune system

    NASA Astrophysics Data System (ADS)

    Mak, Tak W.

    2003-06-01

    Milton's epic poem Paradise lost supplies a colourful metaphor for the immune system and its responses to pathogens. With the role of Satan played by pathogens seeking to destroy the paradise of human health, GOD intervenes and imposes order out of chaos. In this context, GOD means 'generation of diversity': the capacity of the innate and specific immune responses to recognize and eliminate a universe of pathogens. Thus, the immune system can be thought of as an entity that self-assembles the elements required to combat bodily invasion and injury. In so doing, it brings to bear the power of specific recognition: the ability to distinguish self from non-self, and the threatening from the benign. This ability to define and protect self is evolutionarily very old. Self-recognition and biochemical and barrier defences can be detected in primitive organisms, and elements of these mechanisms are built upon in an orderly way to establish the mammalian immune system. Innate immune responses depend on the use of a limited number of germline-encoded receptors to recognize conserved molecular patterns that occur on the surfaces of a broad range of pathogens. The B and T lymphocytes of the specific immune response use complex gene-rearrangement machinery to generate a diversity of antigen receptors capable of recognizing any pathogen in the universe. Binding to receptors on both innate and specific immune-system cells triggers intricate intracellular signalling pathways that lead to new gene transcription and effector-cell activation. And yet, regulation is imposed on these responses so that Paradise is not lost to the turning of the immune system onto self-tissues, the spectre of autoimmunity. Lymphocyte activation requires multiple signals and intercellular interactions. Mechanisms exist to establish tolerance to self by the selection and elimination of cells recognizing self-antigens. Immune system cell populations are reduced by programmed cell death once the pathogen

  20. 'Order from disorder sprung': recognition and regulation in the immune system.

    PubMed

    Mak, Tak W

    2003-06-15

    Milton's epic poem Paradise lost supplies a colourful metaphor for the immune system and its responses to pathogens. With the role of Satan played by pathogens seeking to destroy the paradise of human health, GOD intervenes and imposes order out of chaos. In this context, GOD means 'generation of diversity': the capacity of the innate and specific immune responses to recognize and eliminate a universe of pathogens. Thus, the immune system can be thought of as an entity that self-assembles the elements required to combat bodily invasion and injury. In so doing, it brings to bear the power of specific recognition: the ability to distinguish self from non-self, and the threatening from the benign. This ability to define and protect self is evolutionarily very old. Self-recognition and biochemical and barrier defences can be detected in primitive organisms, and elements of these mechanisms are built upon in an orderly way to establish the mammalian immune system. Innate immune responses depend on the use of a limited number of germline-encoded receptors to recognize conserved molecular patterns that occur on the surfaces of a broad range of pathogens. The B and T lymphocytes of the specific immune response use complex gene-rearrangement machinery to generate a diversity of antigen receptors capable of recognizing any pathogen in the universe. Binding to receptors on both innate and specific immune-system cells triggers intricate intracellular signalling pathways that lead to new gene transcription and effector-cell activation. And yet, regulation is imposed on these responses so that Paradise is not lost to the turning of the immune system onto self-tissues, the spectre of autoimmunity. Lymphocyte activation requires multiple signals and intercellular interactions. Mechanisms exist to establish tolerance to self by the selection and elimination of cells recognizing self-antigens. Immune system cell populations are reduced by programmed cell death once the pathogen

  1. Managing predefined templates and macros for a departmental speech recognition system using common software.

    PubMed

    Sistrom, C L; Honeyman, J C; Mancuso, A; Quisling, R G

    2001-09-01

    The authors have developed a networked database system to create, store, and manage predefined radiology report definitions. This was prompted by complete departmental conversion to a computer speech recognition system (SRS) for clinical reporting. The software complements and extends the capabilities of the SRS, and 2 systems are integrated by means of a simple text file format and import/export functions within each program. This report describes the functional requirements, design considerations, and implementation details of the structured report management software. The database and its interface are designed to allow all radiologists and division managers to define and update template structures relevant to their practice areas. Two key conceptual extensions supported by the template management system are the addition of a template type construct and allowing individual radiologists to dynamically share common organ system or modality-specific templates. In addition, the template manager software enables specifying predefined report structures that can be triggered at the time of dictation from printed lists of barcodes. Initial experience using the program in a regional, multisite, academic radiology practice has been positive. PMID:11720335

  2. Three-dimensional image segmentation and recognition in an intelligent vision system

    NASA Astrophysics Data System (ADS)

    Zhu, Dongping; Conners, Richard W.; Araman, Philip A.

    1992-02-01

    Research is underway to apply computerized tomography (CT) imaging to hardwood log inspection in the forest products industry. For this purpose, an intelligent vision system is being created that is aimed at locating, identifying, and quantifying the internal defects inside logs by analyzing their CT image data. This inspection system is designed to be wood species independent. It is composed of three components: a CT scanner-based data acquisition system; a low-level module for image segmentation; and a high-level module for defect recognition. Defect quantification is attained by computing the volume and orientation of each defect. This paper discusses the problems of segmenting CT image sequence and 3-D object detection by a rule-based expert system approach. Experimental results with real-world images of different hardwood log species are provided to show the usefulness, efficacy, and robustness of the proposed inspection system. This allows solutions to hardwood log inspection, as well as to problems in other nondestructive testing applications where image analysis plays an important role.

  3. Automatic Recognition of Ocean Structures from Satellite Images by Means of Neural Nets and Expert Systems

    NASA Astrophysics Data System (ADS)

    Guindos-Rojas, F.; Cantón-Garbín, M.; Torres-Arriaza, J. A.; Peralta-López, M.; Piedra-Fernández, J. A.; Molina-Martínez, A.

    2004-09-01

    Images received from satellites have became a great source of information about our environment. This is raw information that needs experts to make the most of it, but there are not many experts and the work is too much. The solution to this problem is the compilation of human experience into automatic systems that could do the same work. We depict here the structure for a knowledge based system capable of taking the place of human experts when it is properly trained. This structure has been used to build an automatic recognition system that process AVHRR images from NOAA satellites to detect and locate ocean phenomena of interest like upwellings, eddies and island wakes. The model covers every phase of the process from the source image, once it is corrected and geocoded, to the final features map. In the most delicate phase of the process pipeline, artificial neural nets and rule-based expert systems are used in a parallel redundant way so results can be validated by comparing the outcome of both subsystems. The automatic knowledge driven image processing system has been trained with ubiquitous and localized information and has proved his qualities with images of Canary Island, Mediterranean Sea and Cantabric and Portuguese coasts.

  4. Interactions between Artificial Gravity, the Affected Physiological Systems, and Nutrition

    NASA Technical Reports Server (NTRS)

    Heer, Martina; Baecker, Nathalie; Zwart, Sara; Smith, Scott

    2006-01-01

    Malnutrition, either by insufficient supply of some nutrients or by overfeeding, has a profound effect on the health of an organism. Therefore, optimal nutrition is a necessity in normal gravity on Earth, in microgravity, and when applying artificial gravity to the human system. Reduced physical activity, such as observed in microgravity or bed rest, has an effect on many physiological systems, such as the cardiovascular, musculoskeletal, immune, and body fluids regulation systems. There is currently no countermeasure that is effective to counteract both the cardiovascular and musculoskeletal deconditioning when applied for a short duration (see Chapter 1). Artificial gravity therefore seems the simplest physiological approach to keep these systems intact. The application of intermittent daily dose of artificial gravity by means of centrifugation has often been proposed as a potential countermeasure against the physiological deconditioning induced by spaceflight. However, neither the optimal gravity level, nor its optimal duration of exposure have been enough studied to recommend a validated, effective, and efficient artificial gravity application. As discussed in previous chapters, artificial gravity has a very high potential to counteract any changes caused by reduced physical activity. The nutrient supply, which ideally should match the actual needs, will interact with these changes and therefore has also to be taken into account. This chapter reviews the potential interactions between these nutrients (energy intake, vitamins, minerals) and the other physiological systems affected by artificial gravity generated by an on-board short-radius centrifuge.

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

    PubMed Central

    Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

    2014-01-01

    Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital. PMID:24991942

  6. The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

    PubMed

    Bahlmann, Claus; Burkhardt, Hans

    2004-03-01

    In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device. PMID:15376878

  7. Early prediction of student goals and affect in narrative-centered learning environments

    NASA Astrophysics Data System (ADS)

    Lee, Sunyoung

    Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students

  8. Hybrid neural network and rule-based pattern recognition system capable of self-modification

    SciTech Connect

    Glover, C.W.; Silliman, M.; Walker, M.; Spelt, P.F. ); Rao, N.S.V. . Dept. of Computer Science)

    1990-01-01

    This paper describes a hybrid neural network and rule-based pattern recognition system architecture which is capable of self-modification or learning. The central research issue to be addressed for a multiclassifier hybrid system is whether such a system can perform better than the two classifiers taken by themselves. The hybrid system employs a hierarchical architecture, and it can be interfaced with one or more sensors. Feature extraction routines operating on raw sensor data produce feature vectors which serve as inputs to neural network classifiers at the next level in the hierarchy. These low-level neural networks are trained to provide further discrimination of the sensor data. A set of feature vectors is formed from a concatenation of information from the feature extraction routines and the low-level neural network results. A rule-based classifier system uses this feature set to determine if certain expected environmental states, conditions, or objects are present in the sensors' current data stream. The rule-based system has been given an a priori set of models of the expected environmental states, conditions, or objects which it is expected to identify. The rule-based system forms many candidate directed graphs of various combinations of incoming features vectors, and it uses a suitably chosen metric to measure the similarity between candidate and model directed graphs. The rule-based system must decide if there is a match between one of the candidate graphs and a model graph. If a match is found, then the rule-based system invokes a routine to create and train a new high-level neural network from the appropriate feature vector data to recognize when this model state is present in future sensor data streams. 12 refs., 3 figs.

  9. Recognition- and Reactivity-Based Fluorescent Probes for Studying Transition Metal Signaling in Living Systems

    PubMed Central

    2015-01-01

    Conspectus Metals are essential for life, playing critical roles in all aspects of the central dogma of biology (e.g., the transcription and translation of nucleic acids and synthesis of proteins). Redox-inactive alkali, alkaline earth, and transition metals such as sodium, potassium, calcium, and zinc are widely recognized as dynamic signals, whereas redox-active transition metals such as copper and iron are traditionally thought of as sequestered by protein ligands, including as static enzyme cofactors, in part because of their potential to trigger oxidative stress and damage via Fenton chemistry. Metals in biology can be broadly categorized into two pools: static and labile. In the former, proteins and other macromolecules tightly bind metals; in the latter, metals are bound relatively weakly to cellular ligands, including proteins and low molecular weight ligands. Fluorescent probes can be useful tools for studying the roles of transition metals in their labile forms. Probes for imaging transition metal dynamics in living systems must meet several stringent criteria. In addition to exhibiting desirable photophysical properties and biocompatibility, they must be selective and show a fluorescence turn-on response to the metal of interest. To meet this challenge, we have pursued two general strategies for metal detection, termed “recognition” and “reactivity”. Our design of transition metal probes makes use of a recognition-based approach for copper and nickel and a reactivity-based approach for cobalt and iron. This Account summarizes progress in our laboratory on both the development and application of fluorescent probes to identify and study the signaling roles of transition metals in biology. In conjunction with complementary methods for direct metal detection and genetic and/or pharmacological manipulations, fluorescent probes for transition metals have helped reveal a number of principles underlying transition metal dynamics. In this Account, we give

  10. A pattern recognition system for prostate mass spectra discrimination based on the CUDA parallel programming model

    NASA Astrophysics Data System (ADS)

    Kostopoulos, Spiros; Glotsos, Dimitris; Sidiropoulos, Konstantinos; Asvestas, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis

    2014-03-01

    The aim of the present study was to implement a pattern recognition system for the discrimination of healthy from malignant prostate tumors from proteomic Mass Spectroscopy (MS) samples and to identify m/z intervals of potential biomarkers associated with prostate cancer. One hundred and six MS-spectra were studied in total. Sixty three spectra corresponded to healthy cases (PSA < 1) and forty three spectra were cancerous (PSA > 10). The MS-spectra are publicly available from the NCI Clinical Proteomics Database. The pre-processing comprised the steps: denoising, normalization, peak extraction and peak alignment. Due to the enormous number of features that rose from MS-spectra as informative peaks, and in order to secure optimum system design, the classification task was performed by programming in parallel the multiprocessors of an nVIDIA GPU card, using the CUDA framework. The proposed system achieved 98.1% accuracy. The identified m/z intervals displayed significant statistical differences between the two classes and were found to possess adequate discriminatory power in characterizing prostate samples, when employed in the design of the classification system. Those intervals should be further investigated since they might lead to the identification of potential new biomarkers for prostate cancer.

  11. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition

    PubMed Central

    Subhi Al-batah, Mohammad; Mat Isa, Nor Ashidi; Klaib, Mohammad Fadel; Al-Betar, Mohammed Azmi

    2014-01-01

    To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy. PMID:24707316

  12. Multiple adaptive neuro-fuzzy inference system with automatic features extraction algorithm for cervical cancer recognition.

    PubMed

    Al-batah, Mohammad Subhi; Isa, Nor Ashidi Mat; Klaib, Mohammad Fadel; Al-Betar, Mohammed Azmi

    2014-01-01

    To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy. PMID:24707316

  13. Mammographic density measurements are not affected by mammography system

    PubMed Central

    Damases, Christine N.; Brennan, Patrick C.; McEntee, Mark F.

    2015-01-01

    Abstract. Mammographic density (MD) is a significant risk factor for breast cancer and has been shown to reduce the sensitivity of mammography screening. Knowledge of a woman’s density can be used to predict her risk of developing breast cancer and personalize her imaging pathway. However, measurement of breast density has proven to be troublesome with wide variations in density recorded using radiologists’ visual Breast Imaging Reporting and Data System (BIRADS). Several automated methods for assessing breast density have been proposed, each with their own source of measurement error. The use of differing mammographic imaging systems further complicates MD measurement, especially for the same women imaged over time. The purpose of this study was to investigate whether having a mammogram on differing manufacturer’s equipment affects a woman’s MD measurement. Raw mammographic images were acquired on two mammography imaging systems (General Electric and Hologic) one year apart and processed using VolparaDensity™ to obtain the Volpara Density Grade (VDG) and average volumetric breast density percentage (AvBD%). Visual BIRADS scores were also obtained from 20 expert readers. BIRADS scores for both systems showed strong positive correlation (ρ=0.904; p<0.001), while the VDG (ρ=0.978; p<0.001) and AvBD% (ρ=0.973; p<0.001) showed stronger positive correlations. Substantial agreement was shown between the systems for BIRADS (κ=0.692; p<0.001), however, the systems demonstrated an almost perfect agreement for VDG (κ=0.933; p<0.001). PMID:26158085

  14. Diagnostic odor recognition

    PubMed

    Rosenblatt; Phan; Desandre; Lobon; Hsu

    2000-10-01

    Many diseases, toxic ingestions, and intoxications have characteristic odors. These odors may provide diagnostic clues that affect rapid treatment long before laboratory confirmation or clinical deterioration. Odor recognition skills, similar to auscultation and palpation skills, require teaching and practical exposure. Dr. Goldfrank and colleagues recognized the importance of teaching odor recognition to emergency service providers. They proposed the "sniffing bar" method for odor recognition training. OBJECTIVES: (1) To identify the recognition rates of medically important odors among emergency care providers. (2) To investigate the effectiveness of teaching odor recognition. Hypothesis: The recognition rates of medically important odors will increase after teaching exposure. METHODS: The study exposed emergency care providers to 11 tubes of odors. Identifications of each substance were recorded. After corrective feedback, subjects were re-tested on their ability to identify the odors. Analysis of odor recognition improvement after teaching was done via chi-square test. RESULTS: Improvement in identification after teaching was seen in all odors. However, the improvement was significant only in the lesscommon substances because their initial recognition was especially low. Significant changes may improve with a larger sample size. Subjects often confuse the odors of alcohol with acetone, and wintergreen with camphor. CONCLUSIONS: The recognition rates are higher for the more-common odors, and lower for the less-common odors. Teaching exposures to the less well-known odors are effective and can significantly improve the recognition rate of these substances. Because odor recognition may affect rapid diagnosis and treatment of certain medical emergencies such as toxic ingestion, future studies should investigate the correlation between odor recognition and the ability to identify corresponding medical emergencies. PMID:11015270

  15. Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis.

    PubMed

    López, Vladimir; Villar, Margarita; Queirós, João; Vicente, Joaquín; Mateos-Hernández, Lourdes; Díez-Delgado, Iratxe; Contreras, Marinela; Alves, Paulo C; Alberdi, Pilar; Gortázar, Christian; de la Fuente, José

    2016-03-01

    Mycobacteria of the Mycobacterium tuberculosis complex (MTBC) greatly impact human and animal health worldwide. The mycobacterial life cycle is complex, and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Eurasian wild boar (Sus scrofa) are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis (TB). In the wild boar TB model, mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils, and biomarkers have been proposed as correlates with resistance to natural infection. However, the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized. Our hypothesis is that the immune system proteins under-represented in infected animals, when compared to uninfected controls, are used by mycobacteria to guarantee pathogen infection and transmission. To address this hypothesis, a comparative proteomics approach was used to compare host response between uninfected (TB-) and M. bovis-infected young (TB+) and adult animals with different infection status [TB lesions localized in the head (TB+) or affecting multiple organs (TB++)]. The results identified host immune system proteins that play an important role in host response to mycobacteria. Calcium binding protein A9, Heme peroxidase, Lactotransferrin, Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls, but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar. MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls. The results reported here suggest that M. bovis manipulates host immune response by reducing the production of immune system proteins. However, as infection progresses, wild boar immune response recovers to limit pathogen

  16. Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis

    PubMed Central

    López, Vladimir; Villar, Margarita; Queirós, João; Vicente, Joaquín; Mateos-Hernández, Lourdes; Díez-Delgado, Iratxe; Contreras, Marinela; Alves, Paulo C.; Alberdi, Pilar; Gortázar, Christian; de la Fuente, José

    2016-01-01

    Mycobacteria of the Mycobacterium tuberculosis complex (MTBC) greatly impact human and animal health worldwide. The mycobacterial life cycle is complex, and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Eurasian wild boar (Sus scrofa) are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis (TB). In the wild boar TB model, mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils, and biomarkers have been proposed as correlates with resistance to natural infection. However, the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized. Our hypothesis is that the immune system proteins under-represented in infected animals, when compared to uninfected controls, are used by mycobacteria to guarantee pathogen infection and transmission. To address this hypothesis, a comparative proteomics approach was used to compare host response between uninfected (TB-) and M. bovis-infected young (TB+) and adult animals with different infection status [TB lesions localized in the head (TB+) or affecting multiple organs (TB++)]. The results identified host immune system proteins that play an important role in host response to mycobacteria. Calcium binding protein A9, Heme peroxidase, Lactotransferrin, Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls, but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar. MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls. The results reported here suggest that M. bovis manipulates host immune response by reducing the production of immune system proteins. However, as infection progresses, wild boar immune response recovers to limit pathogen

  17. Changes to freshwater systems affecting Arctic infrastructure and natural resources

    NASA Astrophysics Data System (ADS)

    Instanes, Arne; Kokorev, Vasily; Janowicz, Richard; Bruland, Oddbjørn; Sand, Knut; Prowse, Terry

    2016-03-01

    The resources component of the Arctic Freshwater Synthesis focuses on the potential impact of future climate and change on water resources in the Arctic and how Arctic infrastructure and exploration and production of natural resources are affected. Freshwater availability may increase in the Arctic in the future in response to an increase in middle- and high-latitude annual precipitation. Changes in type of precipitation, its seasonal distribution, timing, and rate of snowmelt represent a challenge to municipalities and transportation networks subjected to flooding and droughts and to current industries and future industrial development. A reliable well-distributed water source is essential for all infrastructures, industrial development, and other sectorial uses in the Arctic. Fluctuations in water supply and seasonal precipitation and temperature may represent not only opportunities but also threats to water quantity and quality for Arctic communities and industrial use. The impact of future climate change is varying depending on the geographical area and the current state of infrastructure and industrial development. This paper provides a summary of our current knowledge related to the system function and key physical processes affecting northern water resources, industry, and other sectorial infrastructure.

  18. Visual word recognition models should also be constrained by knowledge about the visual system.

    PubMed

    Gomez, Pablo; Silins, Sarah

    2012-10-01

    Frost's article advocates for universal models of reading and critiques recent models that concentrate in what has been described as "cracking the orthographic code." Although the challenge to develop models that can account for word recognition beyond Indo-European languages is welcomed, we argue that reading models should also be constrained by general principles of visual processing and object recognition. PMID:22929059

  19. A compensation method to improve the performance of IPI-based entity recognition system in body sensor networks.

    PubMed

    Bao, Shu-Di; He, Zhong-Kun; Jin, Rong; An, Peng

    2013-01-01

    Security of wireless body sensor networks (BSNs) with telemedicine applications remains a crucial issue. A family of novel biometrics schemes has been recently proposed for node recognition and cryptographic key distribution without any pre-deployment in BSNs, where dynamic entity identifiers (EIs) generated from physiological signals captured by individual sensor nodes are used for nodes to recognize each other. As the recognition performance of EIs determines the maximal performance that can be achieved in such biometric systems, several kinds of EI generation schemes have been proposed. The inter-pulse intervals based EI generation scheme is more promising for such applications in actual scenarios because of its acceptable recognition performance. However, it was found that such generated EIs by true pairs of nodes, i.e. two nodes from the same BSN, have some error pattern which could be considered while doing node recognition or key distribution for an improved success rate. To address the problem, this work proposes an error-correcting code based compensation method which can be easily combined together with the key distribution process to achieve an improved recognition performance. Results of statistical analysis with experimental data collected from 14 subjects show that the bit difference between EIs from true pairs of nodes can be effectively reduced with the proposed method. PMID:24109921

  20. Ghosts, UFOs, and magic: positive affect and the experiential system.

    PubMed

    King, Laura A; Burton, Chad M; Hicks, Joshua A; Drigotas, Stephen M

    2007-05-01

    Three studies examined the potential interactions of the experiential system and positive affect (PA) in predicting superstitious beliefs and sympathetic magic. In Study 1, experientiality and induced positive mood interacted to predict the emergence of belief in videos purporting to show unidentified flying objects or ghosts. In Study 2, naturally occurring PA interacted with experientiality to predict susceptibility to sympathetic magic, specifically difficulty in throwing darts at a picture of a baby (demonstrating the law of similarity). In Study 3, induced mood interacted with experientiality to predict sitting farther away from, and expressing less liking for, a partner who had stepped in excrement (demonstrating the law of contagion). Results are interpreted as indicating that PA promotes experiential processing. Implications for the psychology of nonrational beliefs and behaviors are discussed. PMID:17484612

  1. Identification and correction of rejection and substitution errors in optical character recognition systems

    NASA Astrophysics Data System (ADS)

    Himes, Glenn S.; Scholl, Marty M.; DeCosta, Frank A., III

    1993-04-01

    We examine the use of character image analysis coupled with contextual information in complex data gathering forms to identify and correct optical character recognition (OCR) system rejection and substitution errors. Segmented characters from a complex data gathering form are initially classified using an OCR engine based on a combination of Karhunen-Loeve transforms and a back-propagation neural network. Systems of equations are derived from the data gathering form to determine the values of characters rejected by the OCR engine and to verify the consistency of the data captured. If the OCR results for a single form are determined to be inconsistent with respect to the form's data relationships, a set of decision algorithms which incorporates a second neural network and uses additional character features is used to tag characters according to their likelihood of substitution error. Potential substitution errors are incrementally added to the set of OCR reject errors and are processed through dynamically selected systems of equations and search techniques which correct both error classes. We provide experimental results and determine the extent to which errors can be detected and corrected for various OCR error rates.

  2. Real-time gait cycle parameter recognition using a wearable accelerometry system.

    PubMed

    Yang, Che-Chang; Hsu, Yeh-Liang; Shih, Kao-Shang; Lu, Jun-Ming

    2011-01-01

    This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson's disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications. PMID:22164019

  3. Hybrid system of optics and computer for 3-D object recognition

    NASA Astrophysics Data System (ADS)

    Li, Qun Z.; Miao, Peng C.; He, Anzhi

    1992-03-01

    In this paper, a hybrid system of optics and computer for 3D object recognition is presented. The system consists of a Twyman-Green interferometer, a He-Ne laser, a computer, a TV camera, and an image processor. The structured light produced by a Twyman-Green interferometer is split in and illuminates objects in two directions at the same time. Moire contour is formed on the surface of object. In order to delete unwanted patterns in moire contour, we don't utilize the moire contour on the surface of object. We place a TV camera in the middle of the angle between two illuminating directions and take two groups of deformed fringes on the surface of objects. Two groups of deformed fringes are processed using the digital image processing system controlled and operated by XOR logic in the computer, moire fringes are then extracted from the complicated environment. 3D coordinates of points of the object are obtained after moire fringe is followed, and points belonging to the same fringe are given the same altitude. The object is described by its projected drawings in three coordinate planes. The projected drawings in three coordinate planes of the known objects are stored in the library of judgment. The object can be recognized by inquiring the library of judgment.

  4. A Vision-Based Automated Guided Vehicle System with Marker Recognition for Indoor Use

    PubMed Central

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-01-01

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system. PMID:23966180

  5. Recombinase-based isothermal amplification of nucleic acids with self-avoiding molecular recognition systems (SAMRS).

    PubMed

    Sharma, Nidhi; Hoshika, Shuichi; Hutter, Daniel; Bradley, Kevin M; Benner, Steven A

    2014-10-13

    Recombinase polymerase amplification (RPA) is an isothermal method to amplify nucleic acid sequences without the temperature cycling that classical PCR uses. Instead of using heat to denature the DNA duplex, RPA uses recombination enzymes to swap single-stranded primers into the duplex DNA product; these are then extended using a strand-displacing polymerase to complete the cycle. Because RPA runs at low temperatures, it never forces the system to recreate base-pairs following Watson-Crick rules, and therefore it produces undesired products that impede the amplification of the desired product, complicating downstream analysis. Herein, we show that most of these undesired side products can be avoided if the primers contain components of a self-avoiding molecular recognition system (SAMRS). Given the precision that is necessary in the recombination systems for them to function biologically, it is surprising that they accept SAMRS. SAMRS-RPA is expected to be a powerful tool within the range of amplification techniques available to scientists. PMID:25209570

  6. A vision-based automated guided vehicle system with marker recognition for indoor use.

    PubMed

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-01-01

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system. PMID:23966180

  7. Constructing a safety and security system by medical applications of a fast face recognition optical parallel correlator

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Murakami, Yasuo; Kodate, Kashiko

    2006-01-01

    Medical errors and patient safety have always received a great deal of attention, as they can be critically life-threatening and significant matters. Hospitals and medical personnel are trying their utmost to avoid these errors. Currently in the medical field, patients' record is identified through their PIN numbers and ID cards. However, for patients who cannot speak or move, or who suffer from memory disturbances, alternative methods would be more desirable, and necessary in some cases. The authors previously proposed and fabricated a specially-designed correlator called FARCO (Fast Face Recognition Optical Correlator) based on the Vanderlugt Correlator1, which operates at the speed of 1000 faces/s 2,3,4. Combined with high-speed display devices, the four-channel processing could achieve such high operational speed as 4000 faces/s. Running trial experiments on a 1-to-N identification basis using the optical parallel correlator, we succeeded in acquiring low error rates of 1 % FMR and 2.3 % FNMR. In this paper, we propose a robust face recognition system using the FARCO for focusing on the safety and security of the medical field. We apply our face recognition system to registration of inpatients, in particular children and infants, before and after medical treatments or operations. The proposed system has recorded a higher recognition rate by multiplexing both input and database facial images from moving images. The system was also tested and evaluated for further practical use, leaving excellent results. Hence, our face recognition system could function effectively as an integral part of medical system, meeting these essential requirements of safety, security and privacy.

  8. Textual emotion recognition for enhancing enterprise computing

    NASA Astrophysics Data System (ADS)

    Quan, Changqin; Ren, Fuji

    2016-05-01

    The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

  9. Neuroscience-inspired computational systems for speech recognition under noisy conditions

    NASA Astrophysics Data System (ADS)

    Schafer, Phillip B.

    Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes

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

    NASA Astrophysics Data System (ADS)

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

    1991-07-01

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

  11. An integrated and interactive decision support system for automated melanoma recognition of dermoscopic images.

    PubMed

    Rahman, M M; Bhattacharya, P

    2010-09-01

    This paper presents an integrated and interactive decision support system for the automated melanoma recognition of the dermoscopic images based on image retrieval by content and multiple expert fusion. In this context, the ultimate aim is to support the decision making by retrieving and displaying the relevant past cases as well as predicting the image categories (e.g., melanoma, benign and dysplastic nevi) by combining outputs from different classifiers. However, the most challenging aspect in this domain is to detect the lesion from the healthy background skin and extract the lesion-specific local image features. A thresholding-based segmentation method is applied on the intensity images generated from two different schemes to detect the lesion. For the fusion-based image retrieval and classification, the lesion-specific local color and texture features are extracted and represented in the form of the mean and variance-covariance of color channels and in a combined feature space. The performance is evaluated by using both the precision-recall and classification accuracies. Experimental results on a dermoscopic image collection demonstrate the effectiveness of the proposed system and show the viability of a real-time clinical application. PMID:19942406

  12. Fast Scene Recognition and Camera Relocalisation for Wide Area Augmented Reality Systems

    PubMed Central

    Guan, Tao; Duan, Liya; Chen, Yongjian; Yu, Junqing

    2010-01-01

    This paper focuses on online scene learning and fast camera relocalisation which are two key problems currently limiting the performance of wide area augmented reality systems. Firstly, we propose to use adaptive random trees to deal with the online scene learning problem. The algorithm can provide more accurate recognition rates than traditional methods, especially with large scale workspaces. Secondly, we use the enhanced PROSAC algorithm to obtain a fast camera relocalisation method. Compared with traditional algorithms, our method can significantly reduce the computation complexity, which facilitates to a large degree the process of online camera relocalisation. Finally, we implement our algorithms in a multithreaded manner by using a parallel-computing scheme. Camera tracking, scene mapping, scene learning and relocalisation are separated into four threads by using multi-CPU hardware architecture. While providing real-time tracking performance, the resulting system also possesses the ability to track multiple maps simultaneously. Some experiments have been conducted to demonstrate the validity of our methods. PMID:22219700

  13. Fast scene recognition and camera relocalisation for wide area augmented reality systems.

    PubMed

    Guan, Tao; Duan, Liya; Chen, Yongjian; Yu, Junqing

    2010-01-01

    This paper focuses on online scene learning and fast camera relocalisation which are two key problems currently limiting the performance of wide area augmented reality systems. Firstly, we propose to use adaptive random trees to deal with the online scene learning problem. The algorithm can provide more accurate recognition rates than traditional methods, especially with large scale workspaces. Secondly, we use the enhanced PROSAC algorithm to obtain a fast camera relocalisation method. Compared with traditional algorithms, our method can significantly reduce the computation complexity, which facilitates to a large degree the process of online camera relocalisation. Finally, we implement our algorithms in a multithreaded manner by using a parallel-computing scheme. Camera tracking, scene mapping, scene learning and relocalisation are separated into four threads by using multi-CPU hardware architecture. While providing real-time tracking performance, the resulting system also possesses the ability to track multiple maps simultaneously. Some experiments have been conducted to demonstrate the validity of our methods. PMID:22219700

  14. A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

    PubMed Central

    Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

    2015-01-01

    The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

  15. Peptidoglycan Recognition Proteins kill bacteria by inducing suicide through protein-sensing two-component systems

    PubMed Central

    Kashyap, Des Raj; Wang, Minhui; Liu, Li-Hui; Boons, Geert-Jan; Gupta, Dipika; Dziarski, Roman

    2011-01-01

    Mammalian Peptidoglycan Recognition Proteins (PGRPs), similar to antimicrobial lectins, bind to bacterial cell wall and kill bacteria through an unknown mechanism. We show that PGRPs enter Gram-positive cell wall at the site of daughter cell separation during cell division. In Bacillus subtilis PGRPs activate the CssR-CssS two-component system that detects and disposes of misfolded proteins exported out of bacterial cells. This activation results in membrane depolarization, cessation of intracellular peptidoglycan, protein, RNA, and DNA synthesis, and production of hydroxyl radicals, which are responsible for bacterial death. PGRPs also bind to the outer membrane in Escherichia coli and activate functionally homologous CpxA-CpxR two-component system, which results in bacterial death. We excluded other potential bactericidal mechanisms (inhibition of extracellular peptidoglycan synthesis, hydrolysis of peptidoglycan, and membrane permeabilization). Thus we reveal a novel mechanism of bacterial killing by innate immunity proteins that bind to cell wall or outer membrane and exploit bacterial stress defense response to kill bacteria. PMID:21602801

  16. A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

    PubMed

    Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

    2015-01-01

    The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

  17. Modulation of a Glycoprotein Recognition System on Rat Hepatic Endothelial Cells by Glucose and Diabetes Mellitus

    PubMed Central

    Summerfield, John A.; Vergalla, John; Jones, E. Anthony

    1982-01-01

    The cellular location and carbohydrate specificities of a glycoprotein recognition system on rat hepatic sinusoidal cells have been determined. Purified preparations of endothelial, Kupffer, and parenchymal cells were prepared by collagenase liver perfusion, centrifugation on Percoll gradients, and centrifugal elutriation. 125I-labeled agalactoorosomucoid, an N-acetylglucosamine-terminated glycoprotein, was selectively taken up in vitro by endothelial cells. Uptake was shown to be protein dependent, calcium ion dependent, and saturable, and could be described by Michaelis-Menten kinetics (apparent Km 0.29 μM; apparent maximum velocity 4.8 pmol/h per 5 × 106 cells). Uptake was inhibited not only by N-acetylglucosamine, mannose, and mannan but also by glucose, fructose, and a glucose-albumin conjugate. Inhibition by glucose was competitive over a wide range of concentrations and was almost 100% at a glucose concentration of 56 mM. Fasting and the induction of diabetes mellitus prior to isolation of cells was associated with 60% reductions in the recovery of endothelial cells. Uptake by cells isolated from fasted rats was enhanced (apparent maximum velocity 14.3 pmol/h per 5 × 106 cells without change in the apparent Km). These observations suggest that fasting is associated with a marked increase in the mean number of glycoprotein receptors per endothelial cell isolated from normal rats. This effect of fasting could be due to upregulation of glycoprotein receptors on endothelial cells or to the selective isolation of a subpopulation of endothelial cells from fasted animals that bears more glycoprotein receptors per cell than does another subpopulation of these cells. In addition, in vivo studies of the fate of intravenously administered 125I-agalactoorosomucoid indicated that its rate of disappearance from plasma, hepatic accumulation, and catabolism were slower in diabetic than in normal rats. The results suggest that modulation of a carbohydrate

  18. Macromolecular recognition: Structural aspects of the origin of the genetic system

    NASA Technical Reports Server (NTRS)

    Rein, Robert; Barak, Dov; Luo, Ning; Zielinski, Theresa Julia; Shibata, Masayuki

    1991-01-01

    Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of evolution of life. Using computational and modeling techniques and guided by analogies from present day systems we, seek to understand the emergence of genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. In one possible scenario, the RNA enzymatic reaction plays a key role in the emergence of the self-replicating and offers a clue to the onset of enzymatic catalysis prior to the existence of the protein biosynthetic machinery. Our ultimate goal is to propose a simple RNA segment which contains the specificity and catalytic activity of the contemporary RNA enzyme and which could emerge in a primordial chemical environment. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation have been studied. Another important aspect of this reaction is the identity of the functional groups which are essential for the acid base catalysis. The structural characteristics of the target helices, particularly a possible role of G center dot T pair, is under examination by molecular dynamics (MD) simulation technique. Modeling of the ancestral aminoacyl-tRNA synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. Assuming that the catalytic function evolved before the elements of specific recognition of a particular amino acid, we are exploring the minimal structural requirements for the catalysis of tRNA aminoacylation. The molecular modeling system SYBYL was used for this study based on the high resolution crystallographic structures of the present day tyrosyl-adenylate:tyrRS and

  19. Color pattern recognition with CIELAB coordinates

    NASA Astrophysics Data System (ADS)

    Corbalan-Fuertes, Montserrat; Millan Garcia-Verela, Maria S.; Yzuel, Maria J.

    2002-01-01

    A color pattern recognition system must identify a target by its shape and color distribution. In real situations, however, the color information is affected by changes of the light source (e.g., from indoor illumination to outdoor daylight), often making recognition impossible. In this work, we propose a color pattern recognition technique with tolerance for illumination changes within the common sources of white light. This can be accomplished using the coordinates of the CIELAB system, luminance (L*), chroma (C*), and hue (h*) instead of the conventional RGB system. The proposal has some additional advantages: there is no need to store a matched filters base to analyze scenes captured under different light sources (one set of filters for each illuminant light source) and therefore the recognition process can be simplified; and in most cases, the contribution of only two channels (C* and h*) is enough to avoid false alarms in color pattern recognition. From the results, we show that the recognition system is improved when CIELAB coordinates are used.

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

    PubMed

    Jaafar, Haryati; Ibrahim, Salwani; Ramli, Dzati Athiar

    2015-01-01

    Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN), was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%. PMID:26113861

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

    PubMed Central

    Jaafar, Haryati; Ibrahim, Salwani; Ramli, Dzati Athiar

    2015-01-01

    Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN), was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%. PMID:26113861

  2. Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

    SciTech Connect

    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. Automatic recognition system of aquatic organisms by classical and fluorescence microscopy

    NASA Astrophysics Data System (ADS)

    Lauffer, M.; Genty, F.; Margueron, S.; Collette, J. L.; Pihan, J. C.

    2015-05-01

    Blooming of algae and more generally phytoplankton in water ponds or marine environments can lead to hyper eutrophication and lethal consequences on other organisms. The selective recognition of invading species is investigated by automatic recognition algorithms of optical and fluorescence imaging. On one hand, morphological characteristics of algae of microscopic imaging are treated. The image processing lead to the identification the genus of aquatic organisms and compared to a morphologic data base. On the other hand, fluorescence images allow an automatic recognition based on multispectral data that identify locally the ratio of different photosynthetic pigments and gives a unique finger print of algae. It is shown that the combination of both methods are useful in the recognition of aquatic organisms.

  4. A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

    NASA Technical Reports Server (NTRS)

    Burl, M. C.; Fayyad, U. M.; Smyth, P.; Aubele, J. C.; Crumpler, L. S.

    1993-01-01

    The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary

  5. A pattern recognition system for locating small volcanoes in Magellan SAR images of Venus

    NASA Astrophysics Data System (ADS)

    Burl, M. C.; Fayyad, U. M.; Smyth, P.; Aubele, J. C.; Crumpler, L. S.

    1993-03-01

    The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 105 to 106 of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for

  6. [The contemporary relationship between work, qualification and recognition: repercussions on the Unified Health System (SUS) workers].

    PubMed

    Vieira, Monica; Chinelli, Filippina

    2013-06-01

    This paper discusses the relationship between work, qualification and recognition as it occurs in the field of health today, specifically considering the employability of technical workers in the Unified Health System, the way they perceive the employment relationship with respect to their self-esteem regarding their subjectivities. Based on a review of the relevant literature, the subject is treated in the wider context of ongoing changes in the workplace, which are associated with intensification, flexibility and precariousness of labor relations, with repercussions on the specific aspects mentioned. An attempt is made to establish a critical dialogue with the analytical aspect that emphasizes daily work as a privileged forum for overcoming the contradictions that characterize the field of work and education in the SUS nowadays. The text emphasizes the following issues: analysis of the relationship between work and education from the perspective of the concept of skill; the broadening of the meaning of health work; and a critical evaluation of policies that end up making the workers liable for the quality of services rendered. PMID:23752526

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

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad; Shirkhodaie, Amir

    2013-05-01

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

  8. Molecular recognition and controlled release in drug delivery systems based on nanostructured lipid surfactants

    NASA Astrophysics Data System (ADS)

    Angius, R.; Murgia, S.; Berti, D.; Baglioni, P.; Monduzzi, M.

    2006-08-01

    Several monoolein/water (MO/W) based liquid crystalline (LC) nanostructured mesophases have been revisited in view of the new trends of modern drug delivery formulations. The shape and amphiphilic character of the investigated lipid molecules address the preferential polar-apolar interfacial curvature and the delicate interplay of different intermolecular forces that drive self-assembly and thermodynamic stability of the nanostructures. Here some preliminary results related to the release of the antiviral drug 1-amine-adamantane hydrochloride, solubilized in the aqueous domain of bicontinuous cubic and reverse hexagonal LC phases, suggest these MO based LC phases as possible nano-depot systems for long term controlled release. Drug release was followed by conductivity measurements during a period of ten days. An effective and targeted drug delivery often requires a specific molecular recognition. With this aim, the possibility to entrap suitable molecules such as lauroylcholine (LCh, a cationic surfactant having a peptide-like polar head that can 'recognize' membrane proteins) and adenosine monophosphate disodium salt (NaAMP, an electrolyte that can 'recognize' purine receptors) has been tested. The addition of LCh to MO/W cubic gyroid (CG) LC phase causes a cubic-lamellar phase transition. The addition of NaAMP still allows the formation of the CG nanostructure. In the presence of both NaAMP and LCh again a CG LC phase forms. The bicontinuous CG LC phases have been characterized by NMR and SAXS.

  9. Analog Integrated Circuit for Motion Detection with Simple-Shape Recognition Based on Frog Vision System

    NASA Astrophysics Data System (ADS)

    Nishio, Kimihiro; Yonezu, Hiroo; Furukawa, Yuzo

    2007-09-01

    We proposed in this research a novel two-dimensional network based on the frog visual system, with a motion detection function and a newly developed simple-shape recognition function, for use in object discrimination by integrated circuits. Specifically, the network mimics the signal processing of the small-field cell in a frog brain, consisting of the tectum and thalamus, which generates signals of the motion and simple shape of an object. The proposed network is constructed from simple analog complementary metal oxide semiconductor (CMOS) circuits; a test chip of the proposed network was fabricated with a 1.2 μm CMOS process. Measurements on the chip clarified that the proposed network can generate signals of the moving direction, velocity, and simple shape, as well as perform information processing of the small-field cell. Results with the simulation program with integrated circuit emphasis (SPICE) showed that the analog circuits used in the network have low power consumption. Applications of the proposed network are expected to realize advanced vision chips with functions such as object discrimination and target tracking.

  10. The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis.

    PubMed

    Hachaj, Tomasz; Ogiela, Marek R

    2016-06-01

    The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newly applied scripting language allows easily extension and integration of classifier with other software technologies and applications. The obtained execution speed allows using the methodology in the real-time motion capture data processing where capturing frequency differs from 100 Hz to even 500 Hz depending on number of features or classes to be calculated and recognized. Due to this fact the proposed methodology can be used to the high-end motion capture system. We anticipate that using novel, efficient and effective method will highly help both sport trainers and physiotherapist in they practice. The proposed approach can be directly applied to motion capture data kinematics analysis (evaluation of motion without regard to the forces that cause that motion). The ability to apply pattern recognition methods for GDL description can be utilized in virtual reality environment and used for sport training or rehabilitation treatment. PMID:27106581

  11. Structural basis and dynamics of multidrug recognition in a minimal bacterial multidrug resistance system

    PubMed Central

    Habazettl, Judith; Allan, Martin; Jensen, Pernille Rose; Sass, Hans-Jürgen; Thompson, Charles J.; Grzesiek, Stephan

    2014-01-01

    TipA is a transcriptional regulator found in diverse bacteria. It constitutes a minimal autoregulated multidrug resistance system against numerous thiopeptide antibiotics. Here we report the structures of its drug-binding domain TipAS in complexes with promothiocin A and nosiheptide, and a model of the thiostrepton complex. Drug binding induces a large transition from a partially unfolded to a globin-like structure. The structures rationalize the mechanism of promiscuous, yet specific, drug recognition: (i) a four-ring motif present in all known TipA-inducing antibiotics is recognized specifically by conserved TipAS amino acids; and (ii) the variable part of the antibiotic is accommodated within a flexible cleft that rigidifies upon drug binding. Remarkably, the identified four-ring motif is also the major interacting part of the antibiotic with the ribosome. Hence the TipA multidrug resistance mechanism is directed against the same chemical motif that inhibits protein synthesis. The observed identity of chemical motifs responsible for antibiotic function and resistance may be a general principle and could help to better define new leads for antibiotics. PMID:25489067

  12. Geometric filtration of classification-based object detectors in realtime road scene recognition systems

    NASA Astrophysics Data System (ADS)

    Prun, Viktor; Bocharov, Dmitry; Koptelov, Ivan; Sholomov, Dmitry; Postnikov, Vassily

    2015-12-01

    We study the issue of performance improvement of classification-based object detectors by including certain geometric-oriented filters. Configurations of the observed 3D scene may be used as a priori or a posteriori information for object filtration. A priori information is used to select only those object parameters (size and position on image plane) that are in accordance with the scene, restricting implausible combinations of parameters. On the other hand the detection robustness can be enhanced by rejecting detection results using a posteriori information about 3D scene. For example, relative location of detected objects can be used as criteria for filtration. We have included proposed filters in object detection modules of two different industrial vision-based recognition systems and compared the resulting detection quality before detectors improving and after. Filtering with a priori information leads to significant decrease of detector's running time per frame and increase of number of correctly detected objects. Including filter based on a posteriori information leads to decrease of object detection false positive rate.

  13. Multidimensional normative ratings for the International Affective Picture System.

    PubMed

    Libkuman, Terry M; Otani, Hajime; Kern, Rosalie; Viger, Steen G; Novak, Nicole

    2007-05-01

    The purpose of the present investigation was to replicate and extend the International Affective Picture System norms (Ito, Cacioppo, & Lang, 1998; Lang, Bradley, & Cuthbert, 1999). These norms were developed to provide researchers with photographic slides that varied in emotional evocation, especially arousal and valence. In addition to collecting rating data on the dimensions of arousal and valence, we collected data on the dimensions of consequentiality, meaningfulness, familiarity, distinctiveness, and memorability. Furthermore, we collected ratings on the primary emotions of happiness, surprise, sadness, anger, disgust, and fear. A total of 1,302 participants were tested in small groups. The participants in each group rated a subset of 18 slides on 14 dimensions. Ratings were obtained on 703 slides. The means and standard deviations for all of the ratings are provided. We found our valence ratings to be similar to the previous norms. In contrast, our participants were more likely to rate the slides as less arousing than in the previous norms. The mean ratings on the remaining 12 dimensions were all below the midpoint of the 9-point Likert scale. However, sufficient variability in ratings across the slides indicates that selecting slides on the basis of these variables is feasible. Overall, the present ratings should allow investigators to use these norms for research purposes, especially in research dealing with the interrelationships among emotion and cognition. The means and standard deviations for emotions may be downloaded as an Excel spreadsheet from www.psychonomic.org/archive. PMID:17695361

  14. Diagnosing Tuberculosis With a Novel Support Vector Machine-Based Artificial Immune Recognition System

    PubMed Central

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

    2015-01-01

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

  15. Optical Pattern Recognition

    NASA Astrophysics Data System (ADS)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

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

  16. A Smartwatch-Based Assistance System for the Elderly Performing Fall Detection, Unusual Inactivity Recognition and Medication Reminding.

    PubMed

    Deutsch, Markus; Burgsteiner, Harald

    2016-01-01

    The growing number of elderly people in our society makes it increasingly important to help them live an independent and self-determined life up until a high age. A smartwatch-based assistance system should be implemented that is capable of automatically detecting emergencies and helping elderly people to adhere to their medical therapy. Using the acceleration data of a widely available smartwatch, we implemented fall detection and inactivity recognition based on a smartphone connected via Bluetooth. The resulting system is capable of performing fall detection, inactivity recognition, issuing medication reminders and alerting relatives upon manual activation. Though some challenges, like the dependence on a smartphone remain, the resulting system is a promising approach to help elderly people as well as their relatives to live independently and with a feeling of safety. PMID:27139412

  17. Pitch underlies activation of the vocal system during affective vocalization.

    PubMed

    Belyk, Michel; Brown, Steven

    2016-07-01

    Affective prosody is that aspect of speech that conveys a speaker's emotional state through modulations in various vocal parameters, most prominently pitch. While a large body of research implicates the cingulate vocalization area in controlling affective vocalizations in monkeys, no systematic test of functional homology for this area has yet been reported in humans. In this study, we used functional magnetic resonance imaging to compare brain activations when subjects produced affective vocalizations in the form of exclamations vs non-affective vocalizations with similar pitch contours. We also examined the perception of affective vocalizations by having participants make judgments about either the emotions being conveyed by recorded affective vocalizations or the pitch contours of the same vocalizations. Production of affective vocalizations and matched pitch contours activated a highly overlapping set of brain areas, including the larynx-phonation area of the primary motor cortex and a region of the anterior cingulate cortex that is consistent with the macro-anatomical position of the cingulate vocalization area. This overlap contradicts the dominant view that these areas form two distinct vocal pathways with dissociable functions. Instead, we propose that these brain areas are nodes in a single vocal network, with an emphasis on pitch modulation as a vehicle for affective expression. PMID:26078385

  18. Strategic mutations in the class I major histocompatibility complex HLA-A2 independently affect both peptide binding and T cell receptor recognition.

    PubMed

    Baxter, Tiffany K; Gagnon, Susan J; Davis-Harrison, Rebecca L; Beck, John C; Binz, Anne-Kathrin; Turner, Richard V; Biddison, William E; Baker, Brian M

    2004-07-01

    Mutational studies of T cell receptor (TCR) contact residues on the surface of the human class I major histocompatibility complex (MHC) molecule HLA-A2 have identified a "functional hot spot" that comprises Arg(65) and Lys(66) and is involved in recognition by most peptide-specific HLA-A2-restricted TCRs. Although there is a significant amount of functional data on the effects of mutations at these positions, there is comparatively little biochemical information that could illuminate their mode of action. Here, we have used a combination of fluorescence anisotropy, functional assays, and Biacore binding experiments to examine the effects of mutations at these positions on the peptide-MHC interaction and TCR recognition. The results indicate that mutations at both position 65 and position 66 influence peptide binding by HLA-A2 to various extents. In particular, mutations at position 66 result in significantly increased peptide dissociation rates. However, these effects are independent of their effects on TCR recognition, and the Arg(65)-Lys(66) region thus represents a true "hot spot" for TCR recognition. We also made the observation that in vitro T cell reactivity does not scale with the half-life of the peptide-MHC complex, as is often assumed. Finally, position 66 is implicated in the "dual recognition" of both peptide and TCR, emphasizing the multiple roles of the class I MHC peptide-binding domain. PMID:15131131

  19. [Development of a new position-recognition system for robotic radiosurgery systems using machine vision].

    PubMed

    Mohri, Issai; Umezu, Yoshiyuki; Fukunaga, Junnichi; Tane, Hiroyuki; Nagata, Hironori; Hirashima, Hideaki; Nakamura, Katsumasa; Hirata, Hideki

    2014-08-01

    CyberKnife(®) provides continuous guidance through radiography, allowing instantaneous X-ray images to be obtained; it is also equipped with 6D adjustment for patient setup. Its disadvantage is that registration is carried out just before irradiation, making it impossible to perform stereo-radiography during irradiation. In addition, patient movement cannot be detected during irradiation. In this study, we describe a new registration system that we term "Machine Vision," which subjects the patient to no additional radiation exposure for registration purposes, can be set up promptly, and allows real-time registration during irradiation. Our technique offers distinct advantages over CyberKnife by enabling a safer and more precise mode of treatment. "Machine Vision," which we have designed and fabricated, is an automatic registration system that employs three charge coupled device cameras oriented in different directions that allow us to obtain a characteristic depiction of the shape of both sides of the fetal fissure and external ears in a human head phantom. We examined the degree of precision of this registration system and concluded it to be suitable as an alternative method of registration without radiation exposure when displacement is less than 1.0 mm in radiotherapy. It has potential for application to CyberKnife in clinical treatment. PMID:25142385

  20. A preliminary study on automated freshwater algae recognition and classification system

    PubMed Central

    2012-01-01

    Background Freshwater algae can be used as indicators to monitor freshwater ecosystem condition. Algae react quickly and predictably to a broad range of pollutants. Thus they provide early signals of worsening environment. This study was carried out to develop a computer-based image processing technique to automatically detect, recognize, and identify algae genera from the divisions Bacillariophyta, Chlorophyta and Cyanobacteria in Putrajaya Lake. Literature shows that most automated analyses and identification of algae images were limited to only one type of algae. Automated identification system for tropical freshwater algae is even non-existent and this study is partly to fill this gap. Results The development of the automated freshwater algae detection system involved image preprocessing, segmentation, feature extraction and classification by using Artificial neural networks (ANN). Image preprocessing was used to improve contrast and remove noise. Image segmentation using canny edge detection algorithm was then carried out on binary image to detect the algae and its boundaries. Feature extraction process was applied to extract specific feature parameters from algae image to obtain some shape and texture features of selected algae such as shape, area, perimeter, minor and major axes, and finally Fourier spectrum with principal component analysis (PCA) was applied to extract some of algae feature texture. Artificial neural network (ANN) is used to classify algae images based on the extracted features. Feed-forward multilayer perceptron network was initialized with back propagation error algorithm, and trained with extracted database features of algae image samples. System's accuracy rate was obtained by comparing the results between the manual and automated classifying methods. The developed system was able to identify 93 images of selected freshwater algae genera from a total of 100 tested images which yielded accuracy rate of 93%. Conclusions This study

  1. A state-of-the-art hotspot recognition system for full chip verification with lithographic simulation

    NASA Astrophysics Data System (ADS)

    Simmons, Mark C.; Kang, Jae-Hyun; Kim, Youngkeun; Park, Joung Il; Paek, Seung weon; Kim, Kee-sup

    2011-04-01

    In today's semiconductor industry, prior to wafer fabrication, it has become a desirable practice to scan layout designs for lithography-induced defects using advanced process window simulations in conjunction with corresponding manufacturing checks. This methodology has been proven to provide the highest level of accuracy when correlating systematic defects found on the wafer with those identified through simulation. To date, when directly applying this methodology at the full chip level, there has been unfavorable expenses incurred that are associated with simulation which are currently overshadowing its primary benefit of accuracy - namely, long runtimes and the requirement for an abundance of cpus. Considering the aforementioned, the industry has begun to lean towards a more practical application for hotspot identification that revolves around topological pattern recognition in an attempt to sidestep the simulation runtime. This solution can be much less costly when weighing against the negative runtime overhead of simulation. The apparent benefits of pattern matching are, however, counterbalanced with a fundamental concern regarding detection accuracy; topological pattern identification can only detect polygonal configurations, or some derivative of a configuration, which have been previously identified. It is evident that both systems have their strengths and their weaknesses, and that one system's strength is the other's weakness, and vice-versa. A novel hotspot detection methodology that utilizes pattern matching combined with lithographic simulation will be introduced. This system will attempt to minimize the negative aspects of both pattern matching and simulation. The proposed methodology has a high potential to decrease the amount of processing time spent during simulation, to relax the high cpu count requirement, and to maximize pattern matching accuracy by incorporating a multi-staged pattern matching flow prior to performing simulation on a reduced

  2. Computerized system for recognition of autism on the basis of gene expression microarray data.

    PubMed

    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

    The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. PMID:25464350

  3. Spatially resolved mapping of disorder type and distribution in random systems using artificial neural network recognition

    NASA Astrophysics Data System (ADS)

    Kumar, A.; Ovchinnikov, O.; Guo, S.; Griggio, F.; Jesse, S.; Trolier-McKinstry, S.; Kalinin, S. V.

    2011-07-01

    The spatial variability of the polarization dynamics in thin film ferroelectric capacitors was probed by recognition analysis of spatially resolved spectroscopic data. Switching spectroscopy piezoresponse force microscopy (SSPFM) was used to measure local hysteresis loops and map them on a two dimensional (2D) random-bond, random-field Ising model. A neural-network based recognition approach was utilized to analyze the hysteresis loops and their spatial variability. Strong variability is observed in the polarization dynamics around macroscopic cracks because of the modified local-elastic and electric-boundary conditions, with the most pronounced effect on the length scale of ˜100 nm away from the crack. The recognition approach developed here is universal and can potentially be applied for arbitrary macroscopic and spatially resolved data, including temperature- and field-dependent hysteresis, I-V curve mapping, electron microscopy electron energy loss spectroscopy (EELS) imaging, and many others.

  4. Optoelectronic face recognition system using diffractive optical elements: design and evaluation of compact parallel joint transform correlator (COPaC)

    NASA Astrophysics Data System (ADS)

    Kodate, Kashiko; Watanabe, Eriko; Inaba, Rieko

    2001-12-01

    Individual identification based on biological characteristics such as fingerprint, iris and countenance is regarded as a highly essential technique in security systems. As a simple and rapid recognition system satisfying required performance, we have proposed an opto-electronic system, which combines a parallel joint transform correlator (PJTC) with a personal computer. In this paper, the PJTC method using a new design multiple diffractive optical element as a Fourier transform lens was reviewed and proved to be one of the most practical optical computers for face recognition. Furthermore, based on these first trial results, we proposed the design and fabrication of a portable type compact PJTC (COPaC), of which the size is 23 X 15 X 16.3 cm3 and the weight is 4 kg. We obtained its high accuracy performance for one-to-one correlation using 300 front facial images in a database and proved its practicability. Additionally we performed experiments on ID-less discrimination of twins who look alike for human eyes. Successful recognition rate was obtained, indicating its excellent performance and feasibility.

  5. Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems

    NASA Astrophysics Data System (ADS)

    Fedorov, A. K.; Anufriev, M. N.; Zhirnov, A. A.; Stepanov, K. V.; Nesterov, E. T.; Namiot, D. E.; Karasik, V. E.; Pnev, A. B.

    2016-03-01

    We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples.

  6. Spatially Resolved Mapping of Disorder Type and Distribution in Random Systems using Artificial Neural Network Recognition

    SciTech Connect

    Jesse, Stephen; Kalinin, Sergei V; Kumar, Amit; Ovchinnikov, Oleg S; Guo, Senli; Griggio, Flavio; Trolier-Mckinstry, Susan E

    2011-01-01

    The spatial variability of the polarization dynamics in thin film ferroelectric capacitors was probed by recognition analysis of spatially-resolved spectroscopic data. Switching spectroscopy piezoresponse force microscopy was used to measure local hysteresis loops and map them on a 2D random-bond, random-field Ising model. A neural-network based recognition approach was utilized to analyze the hysteresis loops and their spatial variability. Strong variability is observed in the polarization dynamics around macroscopic cracks due to the modified local elastic and electric boundary conditions, with most pronounced effect on the length scale of ~100 nm away from the crack.

  7. Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems.

    PubMed

    Fedorov, A K; Anufriev, M N; Zhirnov, A A; Stepanov, K V; Nesterov, E T; Namiot, D E; Karasik, V E; Pnev, A B

    2016-03-01

    We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples. PMID:27036840

  8. Comparison of two real-time hand gesture recognition systems involving stereo cameras, depth camera, and inertial sensor

    NASA Astrophysics Data System (ADS)

    Liu, Kui; Kehtarnavaz, Nasser; Carlsohn, Matthias

    2014-05-01

    This paper presents a comparison of two real-time hand gesture recognition systems. One system utilizes a binocular stereo camera set-up while the other system utilizes a combination of a depth camera and an inertial sensor. The latter system is a dual-modality system as it utilizes two different types of sensors. These systems have been previously developed in the Signal and Image Processing Laboratory at the University of Texas at Dallas and the details of the algorithms deployed in these systems are reported in previous papers. In this paper, a comparison is carried out between these two real-time systems in order to examine which system performs better for the same set of hand gestures under realistic conditions.

  9. A novel genome-wide polyadenylation sites recognition system based on condition random field.

    PubMed

    Han, Jiuqiang; Zhang, Shanxin; Liu, Jun; Liu, Ruiling

    2014-01-01

    Polyadenylation including the cleavage of pre-mRNA and addition of a stretch of adenosines to the 3'-end is an essential step of pre-mRNA processing in eukayotes. The known regulatory role of polyadenylation in mRNA localization, stability, and translation and the emerging link between poly(A) and disease states underline the necessary to fully characterize polyadenylation sites. Several artificial intelligence methods have been proposed for poly(A) sites recognition. However, these methods are suitable to small subsets of genome sequences. It is necessary to propose a method for genome-wide recognition of poly(A) sites. Recent efforts have found a lot of poly(A) related factors on DNA level. Here, we proposed a novel genome-wide poly(A) recognition method based on the Condition Random Field (CRF) by integrating multiple features. Compared with the polya_svm (the most accurate program for prediction of poly(A) sites till date), our method had a higher performance with the area under ROC curve(0.8621 versus 0.6796). The result suggests that our method is an effective method in genome wide poly(A) sites recognition. PMID:25571055

  10. The Architecture of the Bilingual Word Recognition System: From Identification to Decision.

    ERIC Educational Resources Information Center

    Dijkstra, Ton; van Heuven, Walter J. B.

    2002-01-01

    Evaluates the BIA model of bilingual word recognition in the light of recent empirical evidence. Points out problems with the model and proposes a new model, the BIA+. The new model extends the old one by adding phonological and semantic lexical representations to the available orthographic ones, and assigns a different role to the so-called…

  11. Description and Recognition of the Concept of Social Capital in Higher Education System

    ERIC Educational Resources Information Center

    Tonkaboni, Forouzan; Yousefy, Alireza; Keshtiaray, Narges

    2013-01-01

    The current research is intended to describe and recognize the concept of social capital in higher education based on theoretical method in a descriptive-analytical approach. Description and Recognition of the data, gathered from theoretical and experimental studies, indicated that social capital is one of the most important indices for…

  12. Factors Affecting Soil Microbial Community Structure in Tomato Cropping Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil and rhizosphere microbial communities in agroecosystems may be affected by soil, climate, plant species, and management. We identified some of the most important factors controlling microbial biomass and community structure in an agroecosystem utilizing tomato plants with the following nine tre...

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

    PubMed

    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. PMID:23697176

  14. Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

    NASA Technical Reports Server (NTRS)

    White, R. W.; Parks, D. L.

    1985-01-01

    A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept.

  15. Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment.

    PubMed

    Lemaire, Edward D; Tundo, Marco D; Baddour, Natalie

    2015-01-01

    recognition systems in rehabilitation medicine where mobility monitoring may be beneficial in clinical decision-making. PMID:26710275

  16. Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System

    NASA Astrophysics Data System (ADS)

    Wang, Hongcui; Kawahara, Tatsuya

    CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

  17. Image preprocessing study on KPCA-based face recognition

    NASA Astrophysics Data System (ADS)

    Li, Xuan; Li, Dehua

    2015-12-01

    Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

  18. Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

    SciTech Connect

    McClanahan, Richard; De Leon, Phillip L.

    2014-08-20

    The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, we can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.

  19. Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

    DOE PAGESBeta

    McClanahan, Richard; De Leon, Phillip L.

    2014-08-20

    The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

  20. Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

    NASA Astrophysics Data System (ADS)

    Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

    2016-06-01

    High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.