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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. 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'…

  3. 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.

  4. Perceptual fluency and affect without recognition.

    PubMed

    Anand, P; Sternthal, B

    1991-05-01

    A dichotic listening task was used to investigate the affect-without-recognition phenomenon. Subjects performed a distractor task by responding to the information presented in one ear while ignoring the target information presented in the other ear. The subjects' recognition of and affect toward the target information as well as toward foils was measured. The results offer evidence for the affect-without-recognition phenomenon. Furthermore, the data suggest that the subjects' affect toward the stimuli depended primarily on the extent to which the stimuli were perceived as familiar (i.e., subjective familiarity), and this perception was influenced by the ear in which the distractor or the target information was presented. These data are interpreted in terms of current models of recognition memory and hemispheric lateralization.

  5. Affect Recognition in Adults with ADHD

    ERIC Educational Resources Information Center

    Miller, Meghan; Hanford, Russell B.; Fassbender, Catherine; Duke, Marshall; Schweitzer, Julie B.

    2011-01-01

    Objective: This study compared affect recognition abilities between adults with and without ADHD. Method: The sample consisted of 51 participants (34 men, 17 women) divided into 3 groups: ADHD-combined type (ADHD-C; n = 17), ADHD-predominantly inattentive type (ADHD-I; n = 16), and controls (n = 18). The mean age was 34 years. Affect recognition…

  6. 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.

  7. Facial affect recognition in criminal psychopaths.

    PubMed

    Kosson, David S; Suchy, Yana; Mayer, Andrew R; Libby, John

    2002-12-01

    Prior studies provide consistent evidence of deficits for psychopaths in processing verbal emotional material but are inconsistent regarding nonverbal emotional material. To examine whether psychopaths exhibit general versus specific deficits in nonverbal emotional processing, 34 psychopaths and 33 nonpsychopaths identified with Hare's (R. D. Hare, 1991) Psychopathy Checklist--Revised were asked to complete a facial affect recognition test. Slides of prototypic facial expressions were presented. Three hypotheses regarding hemispheric lateralization anomalies in psychopaths were also tested (right-hemisphere dysfunction, reduced lateralization, and reversed lateralization). Psychopaths were less accurate than nonpsychopaths at classifying facial affect under conditions promoting reliance on right-hemisphere resources and displayed a specific deficit in classifying disgust. These findings demonstrate that psychopaths exhibit specific deficits in nonverbal emotional processing.

  8. 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.

  9. 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,…

  10. Effect of camera resolution and bandwidth on facial affect recognition.

    PubMed

    Cruz, Mario; Cruz, Robyn Flaum; Krupinski, Elizabeth A; Lopez, Ana Maria; McNeeley, Richard M; Weinstein, Ronald S

    2004-01-01

    This preliminary study explored the effect of camera resolution and bandwidth on facial affect recognition, an important process and clinical variable in mental health service delivery. Sixty medical students and mental health-care professionals were recruited and randomized to four different combinations of commonly used teleconferencing camera resolutions and bandwidths: (1) one chip charged coupling device (CCD) camera, commonly used for VHSgrade taping and in teleconferencing systems costing less than $4,000 with a resolution of 280 lines, and 128 kilobytes per second bandwidth (kbps); (2) VHS and 768 kbps; (3) three-chip CCD camera, commonly used for Betacam (Beta) grade taping and in teleconferencing systems costing more than $4,000 with a resolution of 480 lines, and 128 kbps; and (4) Betacam and 768 kbps. The subjects were asked to identify four facial affects dynamically presented on videotape by an actor and actress presented via a video monitor at 30 frames per second. Two-way analysis of variance (ANOVA) revealed a significant interaction effect for camera resolution and bandwidth (p = 0.02) and a significant main effect for camera resolution (p = 0.006), but no main effect for bandwidth was detected. Post hoc testing of interaction means, using the Tukey Honestly Significant Difference (HSD) test and the critical difference (CD) at the 0.05 alpha level = 1.71, revealed subjects in the VHS/768 kbps (M = 7.133) and VHS/128 kbps (M = 6.533) were significantly better at recognizing the displayed facial affects than those in the Betacam/768 kbps (M = 4.733) or Betacam/128 kbps (M = 6.333) conditions. Camera resolution and bandwidth combinations differ in their capacity to influence facial affect recognition. For service providers, this study's results support the use of VHS cameras with either 768 kbps or 128 kbps bandwidths for facial affect recognition compared to Betacam cameras. The authors argue that the results of this study are a consequence of the

  11. 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.

  12. Covert face recognition relies on affective valence in congenital prosopagnosia.

    PubMed

    Bate, Sarah; Haslam, Catherine; Jansari, Ashok; Hodgson, Timothy L

    2009-06-01

    Dominant accounts of covert recognition in prosopagnosia assume subthreshold activation of face representations created prior to onset of the disorder. Yet, such accounts cannot explain covert recognition in congenital prosopagnosia, where the impairment is present from birth. Alternatively, covert recognition may rely on affective valence, yet no study has explored this possibility. The current study addressed this issue in 3 individuals with congenital prosopagnosia, using measures of the scanpath to indicate recognition. Participants were asked to memorize 30 faces paired with descriptions of aggressive, nice, or neutral behaviours. In a later recognition test, eye movements were monitored while participants discriminated studied from novel faces. Sampling was reduced for studied--nice compared to studied--aggressive faces, and performance for studied--neutral and novel faces fell between these two conditions. This pattern of findings suggests that (a) positive emotion can facilitate processing in prosopagnosia, and (b) covert recognition may rely on emotional valence rather than familiarity.

  13. FRONTLINE: teaching affect recognition to medical students: evaluation and reflections.

    PubMed

    Forrest, David V

    2011-01-01

    Techniques developed for teaching more empathic affect recognition and reflection to medical students during their introduction to psychiatric interviewing begin with a concrete grounding in facial muscular movements and facial affect recognition, and proceed to the use of countertransferential affective experience to aid in ascertaining personality types. Observations about the temper of today's medical students by psychoanalysts may be of help in avoiding increasing their already substantial characterological resistance to affective learning and empathy that has recently been reported in the medical education literature.

  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. An audiovisual emotion recognition system

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  16. Spelling-to-sound correspondences affect acronym recognition processes.

    PubMed

    Playfoot, David; Izura, Cristina

    2015-01-01

    A large body of research has examined the factors that affect the speed with which words are recognized in lexical decision tasks. Nothing has yet been reported concerning the important factors in differentiating acronyms (e.g., BBC, HIV, NASA) from nonwords. It appears that this task poses little problem for skilled readers, in spite of the fact that acronyms have uncommon, even illegal, spellings in English. We used regression techniques to examine the role of a number of lexical and nonlexical variables known to be important in word processing in relation to lexical decision for acronym targets. Findings indicated that acronym recognition is affected by age of acquisition and imageability. In a departure from findings in word recognition, acronym recognition was not affected by frequency. Lexical decision responses for acronyms were also affected by the relationship between spelling and sound-a pattern not usually observed in word recognition. We argue that the complexity of acronym recognition means that the process draws phonological information in addition to semantics.

  17. Combat Systems Department Employee Recognition System

    DTIC Science & Technology

    1996-08-01

    the individual’s view of positive reinforcement . Include them in discussions. Ask for their opinions. 4 NSWCDD/MP-96/137 SECTION 3 INSTRUCTIONS 3.1...PROVIDES POSITIVE REINFORCEMENT . THE EASIER IT IS TO DO, THE MORE LIKELY IT IS TO GET DONE. N-DEPARTMENT EMPLOYEE RECOGNITION SYSTEM PRI NCI PLES THERE ARE...INDIVIDUAL’S VIEW OF POSITIVE REINFORCEMENT . ASK THEM I Papa .18Iv 15 N-DEPARTMENT EMPLOYEE RECOGNITION SYSTEM * OUTLINE A. TASK FORCE MEMBERSHIP

  18. Eye movement during facial affect recognition by patients with schizophrenia, using Japanese pictures of facial affect.

    PubMed

    Shiraishi, Yuko; Ando, Kazuhiro; Toyama, Sayaka; Norikane, Kazuya; Kurayama, Shigeki; Abe, Hiroshi; Ishida, Yasushi

    2011-10-01

    A possible relationship between recognition of facial affect and aberrant eye movement was examined in patients with schizophrenia. A Japanese version of standard pictures of facial affect was prepared. These pictures of basic emotions (surprise, anger, happiness, disgust, fear, sadness) were shown to 19 schizophrenic patients and 20 healthy controls who identified emotions while their eye movements were measured. The proportion of correct identifications of 'disgust' was significantly lower for schizophrenic patients, their eye fixation time was significantly longer for all pictures of facial affect, and their eye movement speed was slower for some facial affects (surprise, fear, and sadness). One index, eye fixation time for "happiness," showed a significant difference between the high- and low-dosage antipsychotic drug groups. Some expected facial affect recognition disorder was seen in schizophrenic patients responding to the Japanese version of affect pictures, but there was no correlation between facial affect recognition disorder and aberrant eye movement.

  19. Dynamics of alpha oscillations elucidate facial affect recognition in schizophrenia.

    PubMed

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

    2014-03-01

    Impaired facial affect recognition is characteristic of schizophrenia and has been related to impaired social function, but the relevant neural mechanisms have not been fully identified. The present study sought to identify the role of oscillatory alpha activity in that deficit during the process of facial emotion recognition. Neuromagnetic brain activity was monitored while 44 schizophrenia patients and 44 healthy controls viewed 5-s videos showing human faces gradually changing from neutral to fearful or happy expressions or from the neutral face of one poser to the neutral face of another. Recognition performance was determined separately by self-report. Relative to prestimulus baseline, controls exhibited a 10- to 15-Hz power increase prior to full recognition and a 10- to 15-Hz power decrease during the postrecognition phase. These results support recent proposals about the function of alpha-band oscillations in normal stimulus evaluation. The patients failed to show this sequence of alpha power increase and decrease and also showed low 10- to 15-Hz power and high 10- to 15-Hz connectivity during the prestimulus baseline. In light of the proposal that a combination of alpha power increase and functional disconnection facilitates information intake and processing, the finding of an abnormal association of low baseline alpha power and high connectivity in schizophrenia suggests a state of impaired readiness that fosters abnormal dynamics during facial affect recognition.

  20. 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

  1. 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.

  2. 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.

  3. 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.,…

  4. Interplay between Affect and Arousal in Recognition Memory

    PubMed Central

    Greene, Ciara M.; Bahri, Pooja; Soto, David

    2010-01-01

    Background Emotional states linked to arousal and mood are known to affect the efficiency of cognitive performance. However, the extent to which memory processes may be affected by arousal, mood or their interaction is poorly understood. Methodology/Principal Findings Following a study phase of abstract shapes, we altered the emotional state of participants by means of exposure to music that varied in both mood and arousal dimensions, leading to four different emotional states: (i) positive mood-high arousal; (ii) positive mood-low arousal; (iii) negative mood-high arousal; (iv) negative mood-low arousal. Following the emotional induction, participants performed a memory recognition test. Critically, there was an interaction between mood and arousal on recognition performance. Memory was enhanced in the positive mood-high arousal and in the negative mood-low arousal states, relative to the other emotional conditions. Conclusions/Significance Neither mood nor arousal alone but their interaction appears most critical to understanding the emotional enhancement of memory. PMID:20668532

  5. 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

  6. 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.

  7. Toward the ultimate synthesis/recognition system.

    PubMed

    Furui, S

    1995-10-24

    This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.

  8. How the clustering of phonological neighbors affects visual word recognition.

    PubMed

    Yates, Mark

    2013-09-01

    In recent years, a new scientific field known as network science has been emerging. Network science is concerned with understanding the structure and properties of networks. One concept that is commonly used in describing a network is how the nodes in the network cluster together. The current research applied the idea of clustering to the study of how phonological neighbors influence visual word recognition. The results of 2 experiments converge to show that words with neighbors that are highly clustered (i.e., are closely related in terms of sound) are recognized more slowly than are those having neighbors that are less clustered. This result is explained in terms of the principles of interactive activation where the interplay between phoneme and phonological word units is affected by the neighborhood structure of the word. It is argued that neighbors in more clustered neighborhoods become more active and directly compete with the target word, thereby slowing processing.

  9. 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.

  10. Catechol-O-methyltransferase val(158)met Polymorphism Interacts with Sex to Affect Face Recognition Ability.

    PubMed

    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.

  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. 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.

  13. 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

  14. 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

  15. 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.

  16. 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

  17. Affect recognition across manic and euthymic phases of bipolar disorder in Han-Chinese patients.

    PubMed

    Pan, Yi-Ju; Tseng, Huai-Hsuan; Liu, Shi-Kai

    2013-11-01

    Patients with bipolar disorder (BD) have affect recognition deficits. Whether affect recognition deficits constitute a state or trait marker of BD has great etiopathological significance. The current study aims to explore the interrelationships between affect recognition and basic neurocognitive functions for patients with BD across different mood states, using the Diagnostic Analysis of Non-Verbal Accuracy-2, Taiwanese version (DANVA-2-TW) as the index measure for affect recognition. To our knowledge, this is the first study examining affect recognition deficits of BPD across mood states in the Han Chinese population. Twenty-nine manic patients, 16 remitted patients with BD, and 40 control subjects are included in the study. Distinct association patterns between affect recognition and neurocognitive functions are demonstrated for patients with BD and control subjects, implicating alternations in emotion associated neurocognitive processing. Compared to control subjects, manic patients but not remitted subjects perform significantly worse in the recognition of negative emotions as a whole and specifically anger, after adjusting for differences in general intellectual ability and basic neurocognitive functions. Affect recognition deficit may be a relatively independent impairment in BD rather than consequences arising from deficits in other basic neurocognition. The impairments of manic patients in the recognition of negative emotions, specifically anger, may further our understanding of core clinical psychopathology of BD and have implications in treating bipolar patients across distinct mood phases.

  18. 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.

  19. License Plate Recognition System for Indian Vehicles

    NASA Astrophysics Data System (ADS)

    Sanap, P. R.; Narote, S. P.

    2010-11-01

    We consider the task of recognition of Indian vehicle number plates (also called license plates or registration plates in other countries). A system for Indian number plate recognition must cope with wide variations in the appearance of the plates. Each state uses its own range of designs with font variations between the designs. Also, vehicle owners may place the plates inside glass covered frames or use plates made of nonstandard materials. These issues compound the complexity of automatic number plate recognition, making existing approaches inadequate. We have developed a system that incorporates a novel combination of image processing and artificial neural network technologies to successfully locate and read Indian vehicle number plates in digital images. Commercial application of the system is envisaged.

  20. 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

  1. Assessing the utility of a virtual environment for enhancing facial affect recognition in adolescents with autism.

    PubMed

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

    2014-07-01

    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.

  2. 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.

  3. A Motivational Determinant of Facial Emotion Recognition: Regulatory Focus Affects Recognition of Emotions in Faces

    PubMed Central

    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. Role of adolescent and maternal depressive symptoms on transactional emotion recognition: context and state affect matter.

    PubMed

    Luebbe, Aaron M; Fussner, Lauren M; Kiel, Elizabeth J; Early, Martha C; Bell, Debora J

    2013-12-01

    Depressive symptomatology is associated with impaired recognition of emotion. Previous investigations have predominantly focused on emotion recognition of static facial expressions neglecting the influence of social interaction and critical contextual factors. In the current study, we investigated how youth and maternal symptoms of depression may be associated with emotion recognition biases during familial interactions across distinct contextual settings. Further, we explored if an individual's current emotional state may account for youth and maternal emotion recognition biases. Mother-adolescent dyads (N = 128) completed measures of depressive symptomatology and participated in three family interactions, each designed to elicit distinct emotions. Mothers and youth completed state affect ratings pertaining to self and other at the conclusion of each interaction task. Using multiple regression, depressive symptoms in both mothers and adolescents were associated with biased recognition of both positive affect (i.e., happy, excited) and negative affect (i.e., sadness, anger, frustration); however, this bias emerged primarily in contexts with a less strong emotional signal. Using actor-partner interdependence models, results suggested that youth's own state affect accounted for depression-related biases in their recognition of maternal affect. State affect did not function similarly in explaining depression-related biases for maternal recognition of adolescent emotion. Together these findings suggest a similar negative bias in emotion recognition associated with depressive symptoms in both adolescents and mothers in real-life situations, albeit potentially driven by different mechanisms.

  6. Changing facial affect recognition in schizophrenia: effects of training on brain dynamics.

    PubMed

    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.

  7. 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

  8. 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

  9. 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

  10. A Neural Network Object Recognition System

    DTIC Science & Technology

    1990-07-01

    useful for exploring different neural network configurations. There are three main computation phases of a model based object recognition system...segmentation, feature extraction, and object classification. This report focuses on the object classification stage. For segmentation, a neural network based...are available with the current system. Neural network based feature extraction may be added at a later date. The classification stage consists of a

  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. Towards Real-Time Speech Emotion Recognition for Affective E-Learning

    ERIC Educational Resources Information Center

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2016-01-01

    This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…

  13. 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

  14. A neural network based speech recognition system

    NASA Astrophysics Data System (ADS)

    Carroll, Edward J.; Coleman, Norman P., Jr.; Reddy, G. N.

    1990-02-01

    An overview is presented of the development of a neural network based speech recognition system. The two primary tasks involved were the development of a time invariant speech encoder and a pattern recognizer or detector. The speech encoder uses amplitude normalization and a Fast Fourier Transform to eliminate amplitude and frequency shifts of acoustic clues. The detector consists of a back-propagation network which accepts data from the encoder and identifies individual words. This use of neural networks offers two advantages over conventional algorithmic detectors: the detection time is no more than a few network time constants, and its recognition speed is independent of the number of the words in the vocabulary. The completed system has functioned as expected with high tolerance to input variation and with error rates comparable to a commercial system when used in a noisy environment.

  15. 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.

  16. Cross domains Arabic named entity recognition system

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  17. Signal evolution in prey recognition systems.

    PubMed

    Pie, Marcio R

    2005-01-31

    In this paper a graphical model first developed in the context of kin recognition is adapted to the study of signalling in predator-prey systems. Antipredation strategies are envisioned as points along a signal-to-noise (S/N) axis, with concealing (low S/N) and conspicuous (high S/N) strategies being placed at opposite sides of this axis. Optimal prey recognition systems should find a trade-off between acceptance errors (going after a background cue as if it were a prey) and rejection errors (not going after a prey as if it were background noise). The model also predicts the types of cues the predator should use in opposite sides of the S/N axis.

  18. The Functional Significance of Affect Recognition, Neurocognition, and Clinical Symptoms in Schizophrenia

    PubMed Central

    Hsiao, Sigmund

    2017-01-01

    Objectives The complex relationship and exact extent of the contribution of plausible indictors to social functional outcome in schizophrenia remain unclear. The present study aimed to explore the functional significance of clinical symptoms, neurocognition, and affect recognition simultaneously in schizophrenia. Methods The clinical symptoms, basic neurocognition, facial emotion recognition, and social functioning of 154 subjects, including 74 with schizophrenia and 80 nonclinical comparisons, were assessed. Results We observed that various subdomains of social functioning were extensively related to general intelligence, basic neurocognition, facial emotion recognition, and clinical symptoms, with different association patterns. Multivariate regression analyses revealed that years of education, age, sustained attention, working memory, and facial emotion recognition were significantly associated with global social functioning in schizophrenia. Conclusion Our findings suggest that affect recognition combined with nonsocial neurocognition demonstrated a crucial role in predicting global social function in schizophrenia. PMID:28099444

  19. Dance recognition system using lower body movement.

    PubMed

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

    2014-02-01

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

  20. Structural Target Analysis And Recognition System

    NASA Astrophysics Data System (ADS)

    Lee, Harry C.

    1984-06-01

    The structural target analysis and recognition system (STARS) is a pyramid and syntactical based vision system that uniquely classifies targets, using their viewable internal structure. Being a totally structural approach, STARS uses a resolution sequence to develop a hierarchical pyramid organized segmentation and formal language to perform the recognition function. Global structure of the target is derived by the segment connectivity of the inter-resolution levels, while local structure is based on the local relationship of segments at a single level. The relationships of both the global and local structures form a resolution syntax tree (RST). Two targets are said to be structurally similar if they have similar RSTs. The matching process of the RSTs proceeds from the root to the leaves of the tree. The depth to which the match progresses before failure or completion determines the degree of patch in a resolution sense. RSTs from various views of a target are grouped together to form a formal language. The underlying grammar is transformed into a stochastic grammar so as to accommodate segmentation and environmental variations. Recognition metrics are a function of the resolution structure and posterior probability at each resolution level. Because of the inherent resolution sequence, STARS can accommodate both candidate and reference targets from various resolutions.

  1. 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.

  2. 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.

  3. Euro Banknote Recognition System for Blind People

    PubMed Central

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

    2017-01-01

    This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively. PMID:28117703

  4. Euro Banknote Recognition System for Blind People.

    PubMed

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

    2017-01-20

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

  5. Affect influences false memories at encoding: evidence from recognition data.

    PubMed

    Storbeck, Justin; Clore, Gerald L

    2011-08-01

    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.

  6. 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.

  7. Study on Information Fusion Based Check Recognition System

    NASA Astrophysics Data System (ADS)

    Wang, Dong

    Automatic check recognition techniques play an important role in financial systems, especially in risk management. This paper presents a novel check recognition system based on multi-cue information fusion theory. For Chinese bank check, the amount can be independently determined by legal amount, courtesy amount, or E13B code. The check recognition algorithm consists of four steps: preprocessing, check layout analysis, segmentation and recognition, and information fusion. For layout analysis, an adaptive template matching algorithm is presented to locate the target recognition regions on the check. The hidden markov model is used to segment and recognize legal amount. Courtesy and E13B code are recognized by artificial neural network method, respectively. Finally, D-S evidence theory is then introduced to fuse above three recognition results for better recognition performance. Experimental results demonstrate that the system can robustly recognize checks and the information fusion based algorithm improves the recognition rate by 5~10 percent.

  8. 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.

  9. 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

  10. 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…

  11. 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.

  12. 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.

  13. 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…

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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…

  3. Voice recognition interface for a radiology information system

    NASA Astrophysics Data System (ADS)

    Hinson, William H.; Boehme, Johannes M.; Choplin, Robert H.; Santago, Peter, II

    1990-08-01

    We have implemented a voice recognition interface using a Dragon Systems VoiceScribe-1000 Speech Recognition system installed on an AT&T 6310 personal computer. The Dragon Systems DragonKey software allows the user to emulate keyboard functions using the speech recognition system and replaces the presently used bar code system. The software supports user voice training, grammar design and compilation, as well as speech recognition. We have successfully integrated this voice interface in the clinical report generation system for most standard mammography studies. We have found that the voice system provides a simple, user-friendly interface which is more widely accepted in a medical environment because of its similarities to tradition dictation. Although the system requires some initial time for voice training, it avoids potential delays in transcription and proofreading. This paper describes the design and implementation of this voice recognition interface in our department.

  4. 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…

  5. 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…

  6. 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…

  7. Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats.

    PubMed

    Rosselli, Federica B; Alemi, Alireza; Ansuini, Alessio; Zoccolan, Davide

    2015-01-01

    In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning.

  8. Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats

    PubMed Central

    Rosselli, Federica B.; Alemi, Alireza; Ansuini, Alessio; Zoccolan, Davide

    2015-01-01

    In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning. PMID:25814936

  9. Do I Know You? How Individual Recognition Affects Group Formation and Structure

    PubMed Central

    2017-01-01

    Groups in nature can be formed by interactions between individuals, or by external pressures like predation. It is reasonable to assume that groups formed by internal and external conditions have different dynamics and structures. We propose a computational model to investigate the effects of individual recognition on the formation and structure of animal groups. Our model is composed of agents that can recognize each other and remember previous interactions, without any external pressures, in order to isolate the effects of individual recognition. We show that individual recognition affects the number and size of groups, and the modularity of the social networks. This model can be used as a null model to investigate the effects of external factors on group formation and persistence. PMID:28125708

  10. 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.

  11. A Neural Network Based Speech Recognition System

    DTIC Science & Technology

    1990-02-01

    encoder and identifies individual words. This use of neural networks offers two advantages over conventional algorithmic detectors: the detection...environment. Keywords: Artificial intelligence; Neural networks : Back propagation; Speech recognition.

  12. Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

    PubMed

    Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

    2014-02-01

    Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia.

  13. Modulation of α power and functional connectivity during facial affect recognition.

    PubMed

    Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte; Weisz, Nathan

    2013-04-03

    Research has linked oscillatory activity in the α frequency range, particularly in sensorimotor cortex, to processing of social actions. Results further suggest involvement of sensorimotor α in the processing of facial expressions, including affect. The sensorimotor face area may be critical for perception of emotional face expression, but the role it plays is unclear. The present study sought to clarify how oscillatory brain activity contributes to or reflects processing of facial affect during changes in facial expression. Neuromagnetic oscillatory brain activity was monitored while 30 volunteers viewed videos of human faces that changed their expression from neutral to fearful, neutral, or happy expressions. Induced changes in α power during the different morphs, source analysis, and graph-theoretic metrics served to identify the role of α power modulation and cross-regional coupling by means of phase synchrony during facial affect recognition. Changes from neutral to emotional faces were associated with a 10-15 Hz power increase localized in bilateral sensorimotor areas, together with occipital power decrease, preceding reported emotional expression recognition. Graph-theoretic analysis revealed that, in the course of a trial, the balance between sensorimotor power increase and decrease was associated with decreased and increased transregional connectedness as measured by node degree. Results suggest that modulations in α power facilitate early registration, with sensorimotor cortex including the sensorimotor face area largely functionally decoupled and thereby protected from additional, disruptive input and that subsequent α power decrease together with increased connectedness of sensorimotor areas facilitates successful facial affect recognition.

  14. Beta-glucan recognition by the innate immune system.

    PubMed

    Goodridge, Helen S; Wolf, Andrea J; Underhill, David M

    2009-07-01

    Beta-glucans are recognized by the innate immune system. This recognition plays important roles in host defense and presents specific opportunities for clinical modulation of the host immune response. Neutrophils, macrophages, and dendritic cells among others express several receptors capable of recognizing beta-glucan in its various forms. This review explores what is currently known about beta-glucan recognition and how this recognition stimulates immune responses. Special emphasis is placed on Dectin-1, as we know the most about how this key beta-glucan receptor translates recognition into intracellular signaling, stimulates cellular responses, and participates in orchestrating the adaptive immune response.

  15. Application of Voice Recognition Input to Decision Support Systems

    DTIC Science & Technology

    1988-12-01

    Support System (GDSS) Talkwriter Human Computer Interface Voice Input Individual Decision Support System (IDSS) Voice Input/Output Man Machine Voice ... Interface Voice Processing Natural Language Voice Input Voice Recognition Natural Language Accessed Voice Recognizer Speech Entry Voice Vocabulary

  16. 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.

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

    PubMed

    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.

  18. 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

  19. 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)

  20. Deficits in facial affect recognition among antisocial populations: a meta-analysis.

    PubMed

    Marsh, Abigail A; Blair, R J R

    2008-01-01

    Individuals with disorders marked by antisocial behavior frequently show deficits in recognizing displays of facial affect. Antisociality may be associated with specific deficits in identifying fearful expressions, which would implicate dysfunction in neural structures that subserve fearful expression processing. A meta-analysis of 20 studies was conducted to assess: (a) if antisocial populations show any consistent deficits in recognizing six emotional expressions; (b) beyond any generalized impairment, whether specific fear recognition deficits are apparent; and (c) if deficits in fear recognition are a function of task difficulty. Results show a robust link between antisocial behavior and specific deficits in recognizing fearful expressions. This impairment cannot be attributed solely to task difficulty. These results suggest dysfunction among antisocial individuals in specified neural substrates, namely the amygdala, involved in processing fearful facial affect.

  1. Encoding physiological signals as images for affective state recognition using convolutional neural networks.

    PubMed

    Yu, Guangliang; Li, Xiang; Song, Dawei; Zhao, Xiaozhao; Zhang, Peng; Hou, Yuexian; Hu, Bin; Guangliang Yu; Xiang Li; Dawei Song; Xiaozhao Zhao; Peng Zhang; Yuexian Hou; Bin Hu; Zhao, Xiaozhao; Hou, Yuexian; Li, Xiang; Hu, Bin; Zhang, Peng; Song, Dawei; Yu, Guangliang

    2016-08-01

    Affective state recognition based on multiple modalities of physiological signals has been a hot research topic. Traditional methods require designing hand-crafted features based on domain knowledge, which is time-consuming and has not achieved a satisfactory performance. On the other hand, conducting classification on raw signals directly can also cause some problems, such as the interference of noise and the curse of dimensionality. To address these problems, we propose a novel approach that encodes different modalities of data as images and use convolutional neural networks (CNN) to perform the affective state recognition task. We validate our aproach on the DECAF dataset in comparison with two state-of-the-art methods, i.e., the Support Vector Machines (SVM) and Random Forest (RF). Experimental results show that our aproach outperforms the baselines by 5% to 9%.

  2. 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

  3. 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.

  4. 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)…

  5. 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.

  6. Improvements in the BYBLOS Continuous Speech Recognition System

    DTIC Science & Technology

    1990-11-01

    improve recognition accuracy, exploring new techniques for speaker-independent training, and developing speaker adaptation techniques that allow system...improve recognition accuracy, exploring new techniques for speaker-independent training, and developing speaker adaptation techniques that allow the system...4 Speaker AdaptationI I During the previous three-year eifort, we developed a technique for speaker adaptation in which we modified the HMM parameters

  7. Subjective disturbance of perception is related to facial affect recognition in schizophrenia.

    PubMed

    Comparelli, Anna; De Carolis, Antonella; Corigliano, Valentina; Romano, Silvia; Kotzalidis, Giorgio D; Campana, Chiara; Ferracuti, Stefano; Tatarelli, Roberto; Girardi, Paolo

    2011-10-01

    To examine the relationship between facial affect recognition (FAR) and subjective perceptual disturbances (SPDs), we assessed SPDs in 82 patients with DSM-IV schizophrenia (44 with first-episode psychosis [FEP] and 38 with multiple episodes [ME]) using two subscales of the Frankfurt Complaint Questionnaire (FCQ), WAS (simple perception) and WAK (complex perception). Emotional judgment ability was assessed using Ekman and Friesen's FAR task. Impaired recognition of emotion correlated with scores on the WAS but not on the WAK. The association was significant in the entire group and in the ME group. FAR was more impaired in the ME than in the FEP group. Our findings suggest that there is a relationship between SPDs and FAR impairment in schizophrenia, particularly in multiple-episode patients.

  8. Effectiveness of feature and classifier algorithms in character recognition systems

    NASA Astrophysics Data System (ADS)

    Wilson, Charles L.

    1993-04-01

    At the first Census Optical Character Recognition Systems Conference, NIST generated accuracy data for more than character recognition systems. Most systems were tested on the recognition of isolated digits and upper and lower case alphabetic characters. The recognition experiments were performed on sample sizes of 58,000 digits, and 12,000 upper and lower case alphabetic characters. The algorithms used by the 26 conference participants included rule-based methods, image-based methods, statistical methods, and neural networks. The neural network methods included Multi-Layer Perceptron's, Learned Vector Quantitization, Neocognitrons, and cascaded neural networks. In this paper 11 different systems are compared using correlations between the answers of different systems, comparing the decrease in error rate as a function of confidence of recognition, and comparing the writer dependence of recognition. This comparison shows that methods that used different algorithms for feature extraction and recognition performed with very high levels of correlation. This is true for neural network systems, hybrid systems, and statistically based systems, and leads to the conclusion that neural networks have not yet demonstrated a clear superiority to more conventional statistical methods. Comparison of these results with the models of Vapnick (for estimation problems), MacKay (for Bayesian statistical models), Moody (for effective parameterization), and Boltzmann models (for information content) demonstrate that as the limits of training data variance are approached, all classifier systems have similar statistical properties. The limiting condition can only be approached for sufficiently rich feature sets because the accuracy limit is controlled by the available information content of the training set, which must pass through the feature extraction process prior to classification.

  9. Effects of levodopa-carbidopa-entacapone and smoked cocaine on facial affect recognition in cocaine smokers.

    PubMed

    Bedi, Gillinder; Shiffrin, Laura; Vadhan, Nehal P; Nunes, Edward V; Foltin, Richard W; Bisaga, Adam

    2016-04-01

    In addition to difficulties in daily social functioning, regular cocaine users have decrements in social processing (the cognitive and affective processes underlying social behavior) relative to non-users. Little is known, however, about the effects of clinically-relevant pharmacological agents, such as cocaine and potential treatment medications, on social processing in cocaine users. Such drug effects could potentially alleviate or compound baseline social processing decrements in cocaine abusers. Here, we assessed the individual and combined effects of smoked cocaine and a potential treatment medication, levodopa-carbidopa-entacapone (LCE), on facial emotion recognition in cocaine smokers. Healthy non-treatment-seeking cocaine smokers (N = 14; two female) completed this 11-day inpatient within-subjects study. Participants received LCE (titrated to 400mg/100mg/200mg b.i.d.) for five days with the remaining time on placebo. The order of medication administration was counterbalanced. Facial emotion recognition was measured twice during target LCE dosing and twice on placebo: once without cocaine and once after repeated cocaine doses. LCE increased the response threshold for identification of facial fear, biasing responses away from fear identification. Cocaine had no effect on facial emotion recognition. Results highlight the possibility for candidate pharmacotherapies to have unintended impacts on social processing in cocaine users, potentially exacerbating already existing difficulties in this population.

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

    PubMed

    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. 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. PMID:27563379

  12. 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).

  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.

  14. Speech recognition in dental software systems: features and functionality.

    PubMed

    Yuhaniak Irwin, Jeannie; Fernando, Shawn; Schleyer, Titus; Spallek, Heiko

    2007-01-01

    Speech recognition allows clinicians a hands-free option for interacting with computers, which is important for dentists who have difficulty using a keyboard and a mouse when working with patients. While roughly 13% of all general dentists with computers at chairside use speech recognition for data entry, 16% have tried and discontinued using this technology. In this study, researches explored the speech recognition features and functionality of four dental software applications. For each system, the documentation as well as the working program was evaluated to determine speech recognition capabilities. A comparison checklist was created to highlight each program's speech functionality. Next, after the development of charting scripts, feasibility user tests were conducted to determine if performance comparisons could be made across systems. While four systems were evaluated in the feature comparison, only two of the systems were reviewed during the feasibility user tests. Results show that current speech functionality, instead of being intuitive, is directly comparable to using a mouse. Further, systems require memorizing an enormous amount of specific terminology opposed to using natural language. User testing is a feasible way to measure the performance of speech recognition across systems and will be conducted in the near future. Overall, limited speech functionality reduces the ability of clinicians to interact directly with the computer during clinical care. This can hinder the benefits of electronic patient records and clinical decision support systems.

  15. 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.

  16. 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

  17. VOTAN V5000 speech recognition system performance test report

    NASA Astrophysics Data System (ADS)

    Fitzgerald, W. J.

    1984-08-01

    Evaluation of speech recognition equipment in both quiet office and noisy environments is necessary for such projects as the Low Data Rate Voice Terminal System (LDRVTS), which rely heavily on speech recognition technology for their implementation. To keep abreast of the current state of this changing technology, the VOTAN V5000 system is evaluated in this report. The selection of the VOTAN system for evaluation was influenced by a report in an article from the September/October 1982 issue of Speech Technology, a trade magazine, which described encouraging noise test results with the VOTAN unit in a NASA evaluation test.

  18. 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

  19. 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.

  20. 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

  1. The Recognition System for the Voluntary Wink with EMG

    NASA Astrophysics Data System (ADS)

    Mizutani, Kengi

    There are many reports about the system controlled by the eye movement in the medical instruments and human technology. In this study, we report a new way of recognition for the voluntary wink with EMG, which can use for the controller about some systems with free hand.

  2. Developing A General Purpose Optical Character Recognition System

    NASA Astrophysics Data System (ADS)

    Marosi, I.; Kovacs, E.

    1989-07-01

    The most important points in the development of an OCR system are the font independence and the ability to read free layout text. The feature extraction algorithm based on contour tracing generates size invariant geometrical and topological features which make the recognition as font independent as possible. In our OCR system (Recognita) these features are arranged in a tree structure which enables fast classification to be done. The character and line finding algorithm is designed to meet the second requirement including the recognition of proportional spacing, ligatures, kerning and automatic separation of graphics and text.

  3. Adamantane in Drug Delivery Systems and Surface Recognition.

    PubMed

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

    2017-02-16

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

  4. 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

  5. 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

  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.

  7. 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…

  8. Design of embedded intelligent monitoring system based on face recognition

    NASA Astrophysics Data System (ADS)

    Liang, Weidong; Ding, Yan; Zhao, Liangjin; Li, Jia; Hu, Xuemei

    2017-01-01

    In this paper, a new embedded intelligent monitoring system based on face recognition is proposed. The system uses Pi Raspberry as the central processor. A sensors group has been designed with Zigbee module in order to assist the system to work better and the two alarm modes have been proposed using the Internet and 3G modem. The experimental results show that the system can work under various light intensities to recognize human face and send alarm information in real time.

  9. 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.

  10. Japanese document recognition and retrieval system using programmable SIMD processor

    NASA Astrophysics Data System (ADS)

    Miyahara, Sueharu; Suzuki, Akira; Tada, Shunkichi; Kawatani, Takahiko

    1991-02-01

    This paper describes a new efficient information-filing system for a large number of documents. The system is designed to recognize Japanese characters and make full-text searches across a document database. Key components of the system are a small fully-programmable parallel processor for both recognition and retrieval an image scanner for document input and a personal computer as the operator console. The processor is constructed by a bit-serial single instruction multiple data stream architecture (SIMD) and all components including the 256 processor elements and 11 MB of RAM are integrated on one board. The recognition process divides a document into text lines isolates each character extracts character pattern features and then identifies character categories. The entire process is performed by a single micro-program package down-loaded from the console. The recognition accuracy is more than 99. 0 for about 3 printed Japanese characters at a performance speed of more than 14 characters per second. The processor can also be made available for high speed information retrieval by changing the down-loaded microprogram package. The retrieval process can obtain sentences that include the same information as an inquiry text from the database previously created through character recognition. Retrieval performance is very fast with 20 million individual Japanese characters being examined each second when the database is stored in the processor''s IC memory. It was confirmed that a high performance but flexible and cost-effective document-information-processing system

  11. 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.

  12. The MIT Summit Speech Recognition System: A Progress Report

    DTIC Science & Technology

    1989-01-01

    understanding of the human communication process. Despite recent development of some speech recognition systems with high accuracy, the performance of such...over the past four decades on human communication , in the hope that such systems will one day have a performance approaching that of humans. We are...optimize its use. Third, the system must have a stochastic component to deal with the present state of ignorance in our understanding of the human

  13. 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.

  14. 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.

  15. Do congenital prosopagnosia and the other-race effect affect the same face recognition mechanisms?

    PubMed

    Esins, Janina; Schultz, Johannes; Wallraven, Christian; Bülthoff, Isabelle

    2014-01-01

    Congenital prosopagnosia (CP), an innate impairment in recognizing faces, as well as the other-race effect (ORE), a disadvantage in recognizing faces of foreign races, both affect face recognition abilities. Are the same face processing mechanisms affected in both situations? To investigate this question, we tested three groups of 21 participants: German congenital prosopagnosics, South Korean participants and German controls on three different tasks involving faces and objects. First we tested all participants on the Cambridge Face Memory Test in which they had to recognize Caucasian target faces in a 3-alternative-forced-choice task. German controls performed better than Koreans who performed better than prosopagnosics. In the second experiment, participants rated the similarity of Caucasian faces that differed parametrically in either features or second-order relations (configuration). Prosopagnosics were less sensitive to configuration changes than both other groups. In addition, while all groups were more sensitive to changes in features than in configuration, this difference was smaller in Koreans. In the third experiment, participants had to learn exemplars of artificial objects, natural objects, and faces and recognize them among distractors of the same category. Here prosopagnosics performed worse than participants in the other two groups only when they were tested on face stimuli. In sum, Koreans and prosopagnosic participants differed from German controls in different ways in all tests. This suggests that German congenital prosopagnosics perceive Caucasian faces differently than do Korean participants. Importantly, our results suggest that different processing impairments underlie the ORE and CP.

  16. Do congenital prosopagnosia and the other-race effect affect the same face recognition mechanisms?

    PubMed Central

    Esins, Janina; Schultz, Johannes; Wallraven, Christian; Bülthoff, Isabelle

    2014-01-01

    Congenital prosopagnosia (CP), an innate impairment in recognizing faces, as well as the other-race effect (ORE), a disadvantage in recognizing faces of foreign races, both affect face recognition abilities. Are the same face processing mechanisms affected in both situations? To investigate this question, we tested three groups of 21 participants: German congenital prosopagnosics, South Korean participants and German controls on three different tasks involving faces and objects. First we tested all participants on the Cambridge Face Memory Test in which they had to recognize Caucasian target faces in a 3-alternative-forced-choice task. German controls performed better than Koreans who performed better than prosopagnosics. In the second experiment, participants rated the similarity of Caucasian faces that differed parametrically in either features or second-order relations (configuration). Prosopagnosics were less sensitive to configuration changes than both other groups. In addition, while all groups were more sensitive to changes in features than in configuration, this difference was smaller in Koreans. In the third experiment, participants had to learn exemplars of artificial objects, natural objects, and faces and recognize them among distractors of the same category. Here prosopagnosics performed worse than participants in the other two groups only when they were tested on face stimuli. In sum, Koreans and prosopagnosic participants differed from German controls in different ways in all tests. This suggests that German congenital prosopagnosics perceive Caucasian faces differently than do Korean participants. Importantly, our results suggest that different processing impairments underlie the ORE and CP. PMID:25324757

  17. 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.

  18. Systemic affects of methamphetamine use.

    PubMed

    Hauer, Patrick

    2010-08-01

    Methamphetamine (meth) is the most widely used illegal stimulant in the United States and is especially prevalent in Midwestern states. The sense of euphoria caused by the drug, the ease of manufacturing and the relatively low cost make it a drug of choice for many. The broad range of systemic effects potentially caused by the use of this drug is wide reaching and can vary in degree and presentation from patient to patient. Abnormalities include cardiac and pulmonary disorders as well as observable integumentary problems, psychoses, CNS disturbances, problems associated with immunity and constitutional signs and symptoms. Health care providers need to be vigilant in their efforts to identify patients who may be users of meth and to identify any subtle abnormal findings that may be indicative of significant underlying systemic pathology. Questionnaires like the RAFFT (Relax, Alone, Forget, Friends, Trouble) and the MINI (Mini-International Neuropsychiatric Interview) can be helpful in identifying substance abuse disorders in patients.

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

    PubMed

    Merino, M Dolores; Privado, Jesús

    2015-09-14

    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.

  20. 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.

  1. 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

  2. Affect recognition and the quality of mother-infant interaction: understanding parenting difficulties in mothers with schizophrenia.

    PubMed

    Healy, Sarah J; Lewin, Jona; Butler, Stephen; Vaillancourt, Kyla; Seth-Smith, Fiona

    2016-02-01

    This study investigated the quality of mother-infant interaction and maternal ability to recognise adult affect in three study groups consisting of mothers with a diagnosis of schizophrenia, mothers with depression and healthy controls. Sixty-four mothers were recruited from a Mother and Baby Unit and local children's centres. A 5-min mother-infant interaction was coded on a number of caregiving variables. Affect recognition and discrimination abilities were tested via a series of computerised tasks. Group differences were found both in measures of affect recognition and in the mother-infant interaction. Mothers with schizophrenia showed consistent impairments across most of the parenting measures and all measures of affect recognition and discrimination. Mothers with depression fell between the mothers with schizophrenia and healthy controls on most measures. However, depressed women's parenting was not significantly poorer than controls on any of the measures, and only showed trends for differences with mothers with schizophrenia on a few measures. Regression analyses found impairments in affect recognition and a diagnosis of schizophrenia to predict the occurrence of odd or unusual speech in the mother-infant interaction. Results add to the growing body of knowledge on the mother-infant interaction in mothers with schizophrenia and mothers with depression compared to healthy controls, suggesting a need for parenting interventions aimed at mothers with these conditions. While affect recognition impairments were not found to fully explain differences in parenting among women with schizophrenia, further research is needed to understand the psychopathology of parenting disturbances within this clinical group.

  3. 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…

  4. Recognition of Streptococcus pneumoniae by the innate immune system.

    PubMed

    Koppe, Uwe; Suttorp, Norbert; Opitz, Bastian

    2012-04-01

    Streptococcus pneumoniae is both a frequent colonizer of the upper respiratory tract and a leading cause of life-threatening infections such as pneumonia, meningitis and sepsis. The innate immune system is critical for the control of colonization and for defence during invasive disease. Initially, pneumococci are recognized by different sensors of the innate immune system called pattern recognition receptors (PRRs), which control most subsequent host defence pathways. These PRRs include the transmembrane Toll-like receptors (TLRs) as well as the cytosolic NOD-like receptors (NLRs) and DNA sensors. Recognition of S. pneumoniae by members of these PRR families regulates the production of inflammatory mediators that orchestrate the following immune response of infected as well as neighbouring non-infected cells, stimulates the recruitment of immune cells such as neutrophils and macrophages, and shapes the adaptive immunity. This review summarizes the current knowledge of the function of different PRRs in S. pneumoniae infection.

  5. Perceived Task-Difficulty Recognition from Log-File Information for the Use in Adaptive Intelligent Tutoring Systems

    ERIC Educational Resources Information Center

    Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars

    2016-01-01

    Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

  6. Challenges Associated with Providing Speech Recognition User Interfaces for Computer-Based Educational Systems.

    ERIC Educational Resources Information Center

    Bergeron, Bryan

    1991-01-01

    Discussion of speech recognition technology and its use in computer-assisted instruction focuses on prototype systems designed for medical education. Commercial speech recognition systems are described, hardware and software requirements are examined, and the use of a speech recognition system to streamline an existing user interface is discussed.…

  7. 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.

  8. Shape Recognition Using A CMAC Based Learning System

    NASA Astrophysics Data System (ADS)

    Glanz, F. H.; Miller, W. T.

    1988-02-01

    This paper discusses pattern recognition using a learning system which can learn an arbitrary function of the input and which has built-in generalization with the characteristic that similar inputs lead to similar outputs even for untrained inputs. The amount of similarity is controlled by a parameter of the program at compile time. Inputs and/or outputs may be vectors. The system is trained in a way similar to other pattern recognition systems using an LMS rule. Patterns in the input space are not separated by hyperplanes in the way they normally are using adaptive linear elements. As a result, linear separability is not the problem it is when using Perceptron or Adaline type elements. In fact, almost any shape category region is possible, and a region need not be simply connected nor convex. An example is given of geometric shape recognition using as features autoregressive model parameters representing the shape boundaries. These features are approximately independent of translation, rotation, and size of the shape. Results in the form of percent correct on test sets are given for eight different combinations of training and test sets derived from two groups of shapes.

  9. Toward Development of a Face Recognition System for Watchlist Surveillance.

    PubMed

    Kamgar-Parsi, Behrooz; Lawson, Wallace; Kamgar-Parsi, Behzad

    2011-10-01

    The interest in face recognition is moving toward real-world applications and uncontrolled sensing environments. An important application of interest is automated surveillance, where the objective is to recognize and track people who are on a watchlist. For this open world application, a large number of cameras that are increasingly being installed at many locations in shopping malls, metro systems, airports, etc., will be utilized. While a very large number of people will approach or pass by these surveillance cameras, only a small set of individuals must be recognized. That is, the system must reject every subject unless the subject happens to be on the watchlist. While humans routinely reject previously unseen faces as strangers, rejection of previously unseen faces has remained a difficult aspect of automated face recognition. In this paper, we propose an approach motivated by human perceptual ability of face recognition which can handle previously unseen faces. Our approach is based on identifying the decision region(s) in the face space which belong to the target person(s). This is done by generating two large sets of borderline images, projecting just inside and outside of the decision region. For each person on the watchlist, a dedicated classifier is trained. Results of extensive experiments support the effectiveness of our approach. In addition to extensive experiments using our algorithm and prerecorded images, we have conducted considerable live system experiments with people in realistic environments.

  10. 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...

  11. 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

  12. 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.

  13. 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.

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

    PubMed

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

    2015-08-07

    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.

  15. 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

  16. 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

  17. 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.

  18. 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

  19. Context affects nestmate recognition errors in honey bees and stingless bees.

    PubMed

    Couvillon, Margaret J; Segers, Francisca H I D; Cooper-Bowman, Roseanne; Truslove, Gemma; Nascimento, Daniela L; Nascimento, Fabio S; Ratnieks, Francis L W

    2013-08-15

    Nestmate recognition studies, where a discriminator first recognises and then behaviourally discriminates (accepts/rejects) another individual, have used a variety of methodologies and contexts. This is potentially problematic because recognition errors in discrimination behaviour are predicted to be context-dependent. Here we compare the recognition decisions (accept/reject) of discriminators in two eusocial bees, Apis mellifera and Tetragonisca angustula, under different contexts. These contexts include natural guards at the hive entrance (control); natural guards held in plastic test arenas away from the hive entrance that vary either in the presence or absence of colony odour or the presence or absence of an additional nestmate discriminator; and, for the honey bee, the inside of the nest. For both honey bee and stingless bee guards, total recognition errors of behavioural discrimination made by guards (% nestmates rejected + % non-nestmates accepted) are much lower at the colony entrance (honey bee: 30.9%; stingless bee: 33.3%) than in the test arenas (honey bee: 60-86%; stingless bee: 61-81%; P<0.001 for both). Within the test arenas, the presence of colony odour specifically reduced the total recognition errors in honey bees, although this reduction still fell short of bringing error levels down to what was found at the colony entrance. Lastly, in honey bees, the data show that the in-nest collective behavioural discrimination by ca. 30 workers that contact an intruder is insufficient to achieve error-free recognition and is not as effective as the discrimination by guards at the entrance. Overall, these data demonstrate that context is a significant factor in a discriminators' ability to make appropriate recognition decisions, and should be considered when designing recognition study methodologies.

  20. 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

  1. 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.

  2. Recent developments in affective recommender systems

    NASA Astrophysics Data System (ADS)

    Katarya, Rahul; Verma, Om Prakash

    2016-11-01

    Recommender systems (RSs) are playing a significant role since 1990s as they provide relevant, personalized information to the users over the internet. Lots of work have been done in information filtering, utilization, and application related to RS. However, an important area recently draws our attention which is affective recommender system. Affective recommender system (ARS) is latest trending area of research, as publication in this domain are few and recently published. ARS is associated with human behaviour, human factors, mood, senses, emotions, facial expressions, body gesture and physiological with human-computer interaction (HCI). Due to this assortment and various interests, more explanation is required, as it is in premature phase and growing as compared to other fields. So we have done literature review (LR) in the affective recommender systems by doing classification, incorporate reputed articles published from the year 2003 to February 2016. We include articles which highlight, analyse, and perform a study on affective recommender systems. This article categorizes, synthesizes, and discusses the research and development in ARS. We have classified and managed ARS papers according to different perspectives: research gaps, nature, algorithm or method adopted, datasets, the platform on executed, types of information and evaluation techniques applied. The researchers and professionals will positively support this survey article for understanding the current position, research in affective recommender systems and will guide future trends, opportunity and research focus in ARS.

  3. 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…

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

    PubMed

    Barwick, D Shane

    2008-09-10

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

  5. 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

  6. 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.

  7. Robust laser speckle recognition system for authenticity identification.

    PubMed

    Yeh, Chia-Hung; Sung, Po-Yi; Kuo, Chih-Hung; Yeh, Ruey-Nan

    2012-10-22

    This paper proposes a laser speckle recognition system for authenticity verification. Because of the unique imperfection surfaces of objects, laser speckle provides identifiable features for authentication. A Gabor filter, SIFT (Scale-Invariant Feature Transform), and projection were used to extract the features of laser speckle images. To accelerate the matching process, the extracted Gabor features were organized into an indexing structure using the K-means algorithm. Plastic cards were used as the target objects in the proposed system and the hardware of the speckle capturing system was built. The experimental results showed that the retrieval performance of the proposed method is accurate when the database contains 516 laser speckle images. The proposed system is robust and feasible for authenticity verification.

  8. 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

    2011-03-29

    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.

  9. Named Entity Recognition for Bacterial Type IV Secretion Systems

    PubMed Central

    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

  10. How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

    PubMed

    Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

    2015-01-01

    The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy.

  11. 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.

  12. 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.

  13. 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…

  14. 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…

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

    PubMed

    Kang, Byung Jun; Park, Kang Ryoung

    2007-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Abolmaesumi, Purang; Jahed, M.

    1997-09-01

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

  17. 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.

  18. Transient emotional events and individual affective traits affect emotion recognition in a perceptual decision-making task

    PubMed Central

    Garcia Quesada, Maria; Antico, Lia; Bavelier, Daphne; Vuilleumier, Patrik; Pichon, Swann

    2017-01-01

    Both affective states and personality traits shape how we perceive the social world and interpret emotions. The literature on affective priming has mostly focused on brief influences of emotional stimuli and emotional states on perceptual and cognitive processes. Yet this approach does not fully capture more dynamic processes at the root of emotional states, with such states lingering beyond the duration of the inducing external stimuli. Our goal was to put in perspective three different types of affective states (induced affective states, more sustained mood states and affective traits such as depression and anxiety) and investigate how they may interact and influence emotion perception. Here, we hypothesized that absorption into positive and negative emotional episodes generate sustained affective states that outlast the episode period and bias the interpretation of facial expressions in a perceptual decision-making task. We also investigated how such effects are influenced by more sustained mood states and by individual affect traits (depression and anxiety) and whether they interact. Transient emotional states were induced using movie-clips, after which participants performed a forced-choice emotion classification task with morphed facial expressions ranging from fear to happiness. Using a psychometric approach, we show that negative (vs. neutral) clips increased participants’ propensity to classify ambiguous faces as fearful during several minutes. In contrast, positive movies biased classification toward happiness only for those clips perceived as most absorbing. Negative mood, anxiety and depression had a stronger effect than transient states and increased the propensity to classify ambiguous faces as fearful. These results provide the first evidence that absorption and different temporal dimensions of emotions have a significant effect on how we perceive facial expressions. PMID:28151976

  19. 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

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

    PubMed

    Ashok, Amit; Neifeld, Mark A

    2010-04-01

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

  1. Innate immune recognition of flagellin limits systemic persistence of Brucella.

    PubMed

    Terwagne, Matthieu; Ferooz, Jonathan; Rolán, Hortensia G; Sun, Yao-Hui; Atluri, Vidya; Xavier, Mariana N; Franchi, Luigi; Núñez, Gabriel; Legrand, Thomas; Flavell, Richard A; De Bolle, Xavier; Letesson, Jean-Jacques; Tsolis, Renée M

    2013-06-01

    Brucella are facultative intracellular bacteria that cause chronic infections by limiting innate immune recognition. It is currently unknown whether Brucella FliC flagellin, the monomeric subunit of flagellar filament, is sensed by the host during infection. Here, we used two mutants of Brucella melitensis, either lacking or overexpressing flagellin, to show that FliC hinders bacterial replication in vivo. The use of cells and mice genetically deficient for different components of inflammasomes suggested that FliC was a target of the cytosolic innate immune receptor NLRC4 in vivo but not in macrophages in vitro where the response to FliC was nevertheless dependent on the cytosolic adaptor ASC, therefore suggesting a new pathway of cytosolic flagellin sensing. However, our work also suggested that the lack of TLR5 activity of Brucella flagellin and the regulation of its synthesis and/or delivery into host cells are both part of the stealthy strategy of Brucella towards the innate immune system. Nevertheless, as a flagellin-deficient mutant of B. melitensis wasfound to cause histologically demonstrable injuries in the spleen of infected mice, we suggested that recognition of FliC plays a role in the immunological stand-off between Brucella and its host, which is characterized by a persistent infection with limited inflammatory pathology.

  2. Biased figure-ground assignment affects conscious object recognition in spatial neglect.

    PubMed

    Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

    2010-09-01

    Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.

  3. 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.

  4. 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

  5. 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

  6. Separate but interacting recognition memory systems for different senses: The role of the rat perirhinal cortex

    PubMed Central

    Albasser, Mathieu M.; Amin, Eman; Iordanova, Mihaela D.; Brown, Malcolm W.; Pearce, John M.; Aggleton, John P.

    2011-01-01

    Two different models (convergent and parallel) potentially describe how recognition memory, the ability to detect the re-occurrence of a stimulus, is organized across different senses. To contrast these two models, rats with or without perirhinal cortex lesions were compared across various conditions that controlled available information from specific sensory modalities. Intact rats not only showed visual, tactile, and olfactory recognition, but also overcame changes in the types of sensory information available between object sampling and subsequent object recognition, e.g., between sampling in the light and recognition in the dark, or vice versa. Perirhinal lesions severely impaired object recognition whenever visual cues were available, but spared olfactory recognition and tactile-based object recognition when tested in the dark. The perirhinal lesions also blocked the ability to recognize an object sampled in the light and then tested for recognition in the dark, or vice versa. The findings reveal parallel recognition systems for different senses reliant on distinct brain areas, e.g., perirhinal cortex for vision, but also show that: (1) recognition memory for multisensory stimuli involves competition between sensory systems and (2) perirhinal cortex lesions produce a bias to rely on vision, despite the presence of intact recognition memory systems serving other senses. PMID:21685150

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

    DOEpatents

    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.

  8. An overview of the SPHINX speech recognition system

    NASA Astrophysics Data System (ADS)

    Lee, Kai-Fu; Hon, Hsiao-Wuen; Reddy, Raj

    1990-01-01

    A description is given of SPHINX, a system that demonstrates the feasibility of accurate, large-vocabulary, speaker-independent, continuous speech recognition. SPHINX is based on discrete hidden Markov models (HMMs) with linear-predictive-coding derived parameters. To provide speaker independence, knowledge was added to these HMMs in several ways: multiple codebooks of fixed-width parameters, and an enhanced recognizer with carefully designed models and word-duration modeling. To deal with coarticulation in continuous speech, yet still adequately represent a large vocabulary, two new subword speech units are introduced: function-word-dependent phone models and generalized triphone models. With grammars of perplexity 997, 60, and 20, SPHINX attained word accuracies of 71, 94, and 96 percent, respectively, on a 997-word task.

  9. The Drosophila immune system detects bacteria through specific peptidoglycan recognition.

    PubMed

    Leulier, François; Parquet, Claudine; Pili-Floury, Sebastien; Ryu, Ji-Hwan; Caroff, Martine; Lee, Won-Jae; Mengin-Lecreulx, Dominique; Lemaitre, Bruno

    2003-05-01

    The Drosophila immune system discriminates between different classes of infectious microbes and responds with pathogen-specific defense reactions through selective activation of the Toll and the immune deficiency (Imd) signaling pathways. The Toll pathway mediates most defenses against Gram-positive bacteria and fungi, whereas the Imd pathway is required to resist infection by Gram-negative bacteria. The bacterial components recognized by these pathways remain to be defined. Here we report that Gram-negative diaminopimelic acid-type peptidoglycan is the most potent inducer of the Imd pathway and that the Toll pathway is predominantly activated by Gram-positive lysine-type peptidoglycan. Thus, the ability of Drosophila to discriminate between Gram-positive and Gram-negative bacteria relies on the recognition of specific forms of peptidoglycan.

  10. 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.

  11. 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.

  12. Digital image pattern recognition system using normalized Fourier transform and normalized analytical Fourier-Mellin transform

    NASA Astrophysics Data System (ADS)

    Vélez-Rábago, Rodrigo; Solorza-Calderón, Selene; Jordan-Aramburo, Adina

    2016-12-01

    This work presents an image pattern recognition system invariant to translation, scale and rotation. The system uses the Fourier transform to achieve the invariance to translation and the analytical Forier-Mellin transform for the invariance to scale and rotation. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  13. Modularized reconfigurable system for target recognition with multi-DSP processing

    NASA Astrophysics Data System (ADS)

    Li, Yun; Li, Huili; Xie, Xiaoming

    2013-10-01

    A modularized reconfigurable system for target recognition with multi-DSP processing is designed to reconfigure the target recognition modules and update the distributed target feature libraries through the serial channel to adapt to the varied application. The system is separated into three independent modules and two work modes running at different time slides based on project switch. The modularized reconfiguration module is designed as a minimum security kernel separated from the target recognition module to decrease their coupling and interrelationship. This kind of multi-project design based on cyclic redundancy check presents a more independent and reliable target recognition system with modularized reconfiguration ability.

  14. 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

  15. Optical-digital-neural network system for aided target recognition

    NASA Astrophysics Data System (ADS)

    Farr, Keith B.; Hartman, Richard L.

    1995-07-01

    Many military systems have a critical need for aided target recognition, or cuing. This includes several systems with wide field-of-view search missions such as the UAV, EFOG-M, and Comanche. This report discusses one new approach: a multiple region of interest processor based on diffraction pattern sampling and digital neural network processing. In this concept an optical system segments the image into multiple, rectangular regions of interest and in parallel converts each ROI, be it visible, IR, or radar, to a spatial frequency power spectrum and samples that spectrum for 64 features. A neural network learns to correlate those features with target classes or identifications. A digital system uses the network weights to recognize unknown targets. The research discussed in this report using a single ROI processor showed a very high level of performance. Out of 1024 trials with models of five targets of F- 14, F-18, HIND, SCUD, and M1 tanks, there were 1023 correct classifications and 1 incorrect classification. Out of 1514 trials with those images plus 490 real clutter scenes, there were 1514 correct decisions between target or no-target. Of the 1024 target detections, there were 1023 correct classifications. Out of 60 trials with low resolution IR images of real scenes, there were 60 correct decisions between target and no-target. Of the 40 target detections, there were 40 correct classifications.

  16. 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;…

  17. Application of CMOS image sensor OV9620 in number recognition system

    NASA Astrophysics Data System (ADS)

    Li, Yu-feng; Liang, Fei; Xue, Rong-kun

    2009-11-01

    An image acquisition system is introduced, which consists of a color CMOS image sensor (OV9620), SRAM (CY62148), CPLD (EPM7128AE) and DSP (TMS320VC5509A). The CPLD implements the logic and timing control to the system. SRAM stores the image data, and DSP controls the image acquisition system through the SCCB (Omni Vision Serial Camera Control Bus). The timing sequence of the CMOS image sensor OV9620 is analyzed. The imaging part and the high speed image data memory unit are designed. The system structure and its application of CMOS image sensor OV9620 in paper currency number recognition are also introduced. The hardware and software design of the image acquisition and recognition system is given. In this system, we use the template matching character recognition method to guarantee fast recognition speed and high correct recognition probability.

  18. 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

    2015-07-13

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

  19. Personal recognition using head-top image for health-monitoring system in the home.

    PubMed

    Nakajima, K; Sasaki, K

    2004-01-01

    Automatic health-monitoring systems for the smart house are being developed for the elderly. An automatic health-monitoring system needs a way of personal recognition when two or more aged persons live together. We propose a personal recognition method based on the space spectrum of the head-top image. We examined 33 head-top images from eleven subjects and achieved a personal recognition rate of 86.4 percent. When one subject with thinning hair was excluded, the personal recognition rate was 90.0 percent in 30 head-top images from ten subjects.

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

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  1. The relation of expression recognition and affective experience in facial expression processing: an event-related potential study

    PubMed Central

    Dong, Guangheng; Lu, Shenglan

    2010-01-01

    The present study investigates the relationship of expression recognition and affective experience during facial expression processing by event-related potentials (ERP). Facial expressions used in the present study can be divided into three categories: positive (happy), neutral (neutral), and negative (angry). Participants were asked to finish two kinds of facial recognition tasks: one was easy, and the other was difficult. In the easy task, significant main effects were found for different valence conditions, meaning that emotions were evoked effectively when participants recognized the expressions in facial expression processing. However, no difference was found in the difficult task, meaning that even if participants had identified the expressions correctly, no relevant emotion was evoked during the process. The findings suggest that emotional experience was not simultaneous with expression identification in facial expression processing, and the affective experience process could be suppressed in challenging cognitive tasks. The results indicate that we should pay attention to the level of cognitive load when using facial expressions as emotion-eliciting materials in emotion studies; otherwise, the emotion may not be evoked effectively. PMID:22110330

  2. 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

  3. [Non-conscious perception of emotional faces affects the visual objects recognition].

    PubMed

    Gerasimenko, N Iu; Slavutskaia, A V; Kalinin, S A; Mikhaĭlova, E S

    2013-01-01

    In 34 healthy subjects we have analyzed accuracy and reaction time (RT) during the recognition of complex visual images: pictures of animals and non-living objects. The target stimuli were preceded by brief presentation of masking non-target ones, which represented drawings of emotional (angry, fearful, happy) or neutral faces. We have revealed that in contrast to accuracy the RT depended on the emotional expression of the preceding faces. RT was significantly shorter if the target objects were paired with the angry and fearful faces as compared with the happy and neutral ones. These effects depended on the category of the target stimulus and were more prominent for objects than for animals. Further, the emotional faces' effects were determined by emotional and communication personality traits (defined by Cattell's Questionnaire) and were clearer defined in more sensitive, anxious and pessimistic introverts. The data are important for understanding the mechanisms of human visual behavior determination by non-consciously processing of emotional information.

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

    PubMed

    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.

  5. Histidines in potential substrate recognition sites affect thyroid hormone transport by monocarboxylate transporter 8 (MCT8).

    PubMed

    Braun, Doreen; Lelios, Iva; Krause, Gerd; Schweizer, Ulrich

    2013-07-01

    Mutations in monocarboxylate transporter 8 (MCT8; SLC16A2) cause the Allan-Herndon-Dudley syndrome, a severe X-linked psychomotor retardation syndrome. MCT8 belongs to the major facilitator superfamily of 12 transmembrane-spanning proteins and transports thyroid hormones across the blood-brain barrier and into neurons. How MCT8 distinguishes thyroid hormone substrates from structurally closely related compounds is not known. The goal of this study was to identify critical amino acids along the transport channel cavity, which participate in thyroid hormone recognition. The fact that T3 is bound between a His-Arg clamp in the crystal structure of the T3 receptor/T3 complex prompted us to investigate whether such a motif might potentially be relevant for T3 recognition in MCT8. We therefore replaced candidate histidines and arginines by site-directed mutagenesis and performed activity assays in MDCK-1 cells and Xenopus oocytes. Histidines were replaced by alanine, phenylalanine, and glutamine to probe for molecular properties like aromatic ring structure and H-bonding properties. It was found that some mutations in His192 and His415 significantly changed substrate transport kinetics. Arg301 at the intracellular end of the substrate channel is at an ideal distance to His415 to participate in a His-Arg clamp and mutation to alanine-abrogated hormone transport. Molecular modeling demonstrates a perfect fit of T3 poised into the substrate channel between His415 and Arg301 and observing the same geometry as in the T3 receptor.

  6. 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.

  7. Natural language understanding and speech recognition for industrial vision systems

    NASA Astrophysics Data System (ADS)

    Batchelor, Bruce G.

    1992-11-01

    The accepted method of programming machine vision systems for a new application is to incorporate sub-routines from a standard library into code, written specially for the given task. Typical programming languages that might be used here are Pascal, C, and assembly code, although other `conventional' (i.e., imperative) languages are often used instead. The representation of an algorithm to recognize a certain object, in the form of, say, a C language program is clumsy and unnatural, compared to the alternative process of describing the object itself and leaving the software to search for it. The latter method, known as declarative programming, is used extensively both when programming in Prolog and when people talk to one another in English, or other natural languages. Programs to understand a limited sub-set of a natural language can also be written conveniently in Prolog. The article considers the prospects for talking to an image processing system, using only slightly constrained English. Moderately priced speech recognition devices, which interface to a standard desk-top computer and provide a limited repertoire (200 words) as well as the ability to identify isolated words, are already available commercially. At the moment, the goal of talking in English to a computer is incompletely fulfilled. Yet, sufficient progress has been made to encourage greater effort in this direction.

  8. 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

  9. 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.

  10. Eusocial evolution and the recognition systems in social insects.

    PubMed

    Krasnec, Michelle O; Breed, Michael D

    2012-01-01

    Eusocial species, animals which live in colonies with a reproductive division of labor, typically have closed societies, in which colony members are allowed entry and nonmembers, including animals of the same species, are excluded. This implies an ability to discriminate colony members ("self") from nonmembers ("nonself"). We draw analogies between this type of discrimination and MHC-mediated cellular recognition in vertebrates. Recognition of membership in eusocial colonies is typically mediated by differences in the surface chemistry between members and nonmembers and we review studies which support this hypothesis. In rare instances, visual signals mediate recognition. We highlight the need for better understanding of which surface compounds actually mediate recognition and for further work on how differences between colony members and nonmembers are perceived.

  11. 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.

  12. A survey of affect recognition methods: audio, visual, and spontaneous expressions.

    PubMed

    Zeng, Zhihong; Pantic, Maja; Roisman, Glenn I; Huang, Thomas S

    2009-01-01

    Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions despite the fact that deliberate behaviour differs in visual appearance, audio profile, and timing from spontaneously occurring behaviour. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behaviour have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis including audiovisual fusion, linguistic and paralinguistic fusion, and multi-cue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next we examine available approaches to solving the problem of machine understanding of human affective behavior, and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.

  13. Using event related potentials to explore stages of facial affect recognition deficits in schizophrenia.

    PubMed

    Wynn, Jonathan K; Lee, Junghee; Horan, William P; Green, Michael F

    2008-07-01

    Schizophrenia patients show impairments in identifying facial affect; however, it is not known at what stage facial affect processing is impaired. We evaluated 3 event-related potentials (ERPs) to explore stages of facial affect processing in schizophrenia patients. Twenty-six schizophrenia patients and 27 normal controls participated. In separate blocks, subjects identified the gender of a face, the emotion of a face, or if a building had 1 or 2 stories. Three ERPs were examined: (1) P100 to examine basic visual processing, (2) N170 to examine facial feature encoding, and (3) N250 to examine affect decoding. Behavioral performance on each task was also measured. Results showed that schizophrenia patients' P100 was comparable to the controls during all 3 identification tasks. Both patients and controls exhibited a comparable N170 that was largest during processing of faces and smallest during processing of buildings. For both groups, the N250 was largest during the emotion identification task and smallest for the building identification task. However, the patients produced a smaller N250 compared with the controls across the 3 tasks. The groups did not differ in behavioral performance in any of the 3 identification tasks. The pattern of intact P100 and N170 suggest that patients maintain basic visual processing and facial feature encoding abilities. The abnormal N250 suggests that schizophrenia patients are less efficient at decoding facial affect features. Our results imply that abnormalities in the later stage of feature decoding could potentially underlie emotion identification deficits in schizophrenia.

  14. 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.

  15. 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

  16. 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.

  17. 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, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Recognition of...

  18. 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.

  19. The effects of gender and COMT Val158Met polymorphism on fearful facial affect recognition: a fMRI study.

    PubMed

    Kempton, Matthew J; Haldane, Morgan; Jogia, Jigar; Christodoulou, Tessa; Powell, John; Collier, David; Williams, Steven C R; Frangou, Sophia

    2009-04-01

    The functional catechol-O-methyltransferase (COMT Val108/158Met) polymorphism has been shown to have an impact on tasks of executive function, memory and attention and recently, tasks with an affective component. As oestrogen reduces COMT activity, we focused on the interaction between gender and COMT genotype on brain activations during an affective processing task. We used functional MRI (fMRI) to record brain activations from 74 healthy subjects who engaged in a facial affect recognition task; subjects viewed and identified fearful compared to neutral faces. There was no main effect of the COMT polymorphism, gender or genotypexgender interaction on task performance. We found a significant effect of gender on brain activations in the left amygdala and right temporal pole, where females demonstrated increased activations over males. Within these regions, Val/Val carriers showed greater signal magnitude compared to Met/Met carriers, particularly in females. The COMT Val108/158Met polymorphism impacts on gender-related patterns of activation in limbic and paralimbic regions but the functional significance of any oestrogen-related COMT inhibition appears modest.

  20. 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.

  1. A Noise-Robust Continuous Speech Recognition System Using Block-Based Dynamic Range Adjustment

    NASA Astrophysics Data System (ADS)

    Sun, Yiming; Miyanaga, Yoshikazu

    A new approach to speech feature estimation under noise circumstances is proposed in this paper. It is used in noise-robust continuous speech recognition (CSR). As the noise robust techniques in isolated word speech recognition, the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods have been developed. Among them, only RSA has been applied to a CSR system. This paper proposes an extended DRA for a noise-robust CSR system. In the stage of speech recognition, a continuous speech waveform is automatically assigned to a block defined by a short time length. The extended DRA is applied to these estimated blocks. The average recognition rate of the proposed method has been improved under several different noise conditions. As a result, the recognition rates are improved up to 15% in various noises with 10 dB SNR.

  2. 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…

  3. Rotation, scale and translation invariant pattern recognition system for color images

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    This work presents a color image pattern recognition system invariant to rotation, scale and translation. The system works with three 1D signatures, one for each RGB color channel. The signatures are constructed based on Fourier transform, analytic Fourier-Mellin transform and Hilbert binary rings mask. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  4. 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.

  5. 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.

  6. The Magnet view: pursuing ANCC Magnet recognition as a system or individual organization.

    PubMed

    Pinkerton, SueEllen

    2008-01-01

    Systems comprising more than one organization at some point think about whether or not to pursue Magnet recognition for each individual organization or as a system. There are several considerations when making this decision in each of the Model Components for the Magnet Recognition Program. Magnet recognition is not a checklist of achievements, but rather an enculturation of values, standards, vision, commitment, and pride. It is important to remember that each organization is different and is at a different place in their development at any one time. Making the decision to pursue system Magnet recognition should consider all important factors since if one organization in the system doesn't make the grade, the system is not Magnet recognized.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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

  12. Exploring techniques for vision based human activity recognition: methods, systems, and evaluation.

    PubMed

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

    2013-01-25

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

  13. 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.

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

    PubMed

    Cummings, Andrew J; Rennels, Jennifer L

    2014-02-01

    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.

  15. 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.

  16. 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.

  17. Extended depth-of-field iris recognition system for a workstation environment

    NASA Astrophysics Data System (ADS)

    Narayanswamy, Ramkumar; Silveira, Paulo E. X.; Setty, Harsha; Pauca, V. P.; van der Gracht, Joseph

    2005-03-01

    Iris recognition imaging is attracting considerable interest as a viable alternative for personal identification and verification in many defense and security applications. However current iris recognition systems suffer from limited depth of field, which makes usage of these systems more difficult by an untrained user. Traditionally, the depth of field is increased by reducing the imaging system aperture, which adversely impacts the light capturing power and thus the system signal-to-noise ratio (SNR). In this paper we discuss a computational imaging system, referred to as Wavefront Coded(R) imaging, for increasing the depth of field without sacrificing the SNR or the resolution of the imaging system. This system employs a especially designed Wavefront Coded lens customized for iris recognition. We present experimental results that show the benefits of this technology for biometric identification.

  18. Low-Complexity Hand Gesture Recognition System for Continuous Streams of Digits and Letters.

    PubMed

    Poularakis, Stergios; Katsavounidis, Ioannis

    2016-09-01

    In this paper, we propose a complete gesture recognition framework based on maximum cosine similarity and fast nearest neighbor (NN) techniques, which offers high-recognition accuracy and great computational advantages for three fundamental problems of gesture recognition: 1) isolated recognition; 2) gesture verification; and 3) gesture spotting on continuous data streams. To support our arguments, we provide a thorough evaluation on three large publicly available databases, examining various scenarios, such as noisy environments, limited number of training examples, and time delay in system's response. Our experimental results suggest that this simple NN-based approach is quite accurate for trajectory classification of digits and letters and could become a promising approach for implementations on low-power embedded systems.

  19. Molecular modeling studies demonstrate key mutations that could affect the ligand recognition by influenza AH1N1 neuraminidase.

    PubMed

    Ramírez-Salinas, Gema L; García-Machorro, J; Quiliano, Miguel; Zimic, Mirko; Briz, Verónica; Rojas-Hernández, Saul; Correa-Basurto, J

    2015-11-01

    The goal of this study was to identify neuraminidase (NA) residue mutants from human influenza AH1N1 using sequences from 1918 to 2012. Multiple alignment studies of complete NA sequences (5732) were performed. Subsequently, the crystallographic structure of the 1918 influenza (PDB ID: 3BEQ-A) was used as a wild-type structure and three-dimensional (3-D) template for homology modeling of the mutated selected NA sequences. The 3-D mutated NAs were refined using molecular dynamics (MD) simulations (50 ns). The refined 3-D models were used to perform docking studies using oseltamivir. Multiple sequence alignment studies showed seven representative mutations (A232V, K262R, V263I, T264V, S367L, S369N, and S369K). MD simulations applied to 3-D NAs showed that each NA had different active-site shapes according to structural surface visualization and docking results. Moreover, Cartesian principal component analyses (cPCA) show structural differences among these NA structures caused by mutations. These theoretical results suggest that the selected mutations that are located outside of the active site of NA could affect oseltamivir recognition and could be associated with resistance to oseltamivir.

  20. 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.

  1. Developing Speaker Recognition System: From Prototype to Practical Application

    NASA Astrophysics Data System (ADS)

    Fränti, Pasi; Saastamoinen, Juhani; Kärkkäinen, Ismo; Kinnunen, Tomi; Hautamäki, Ville; Sidoroff, Ilja

    In this paper, we summarize the main achievements made in the 4-year PUMS project during 2003-2007. The emphasis is on the practical implementations, how we have moved from Matlab and Praat scripting to C/C++ implemented applications in Windows, UNIX, Linux and Symbian environments, with the motivation to enhance technology transfer. We summarize how the baseline methods have been implemented in practice, how the results are utilized in forensic applications, and compare recognition results to the state-ofart and existing commercial products such as ASIS, FreeSpeech and VoiceNet.

  2. Effect of Task Duration on Voice Recognition System Performance.

    DTIC Science & Technology

    1981-09-01

    RENNTRACUCATONERS) . PRFORING ORIATIOCNMEANDTADDREN 1AG. PRORM ELEMETN RORMTS P MT GOV ACESSIN NO 3REA PIEN’ COA96TO NUMBER TITLE~~P 62721Nti S.TV---E II .~~~~6...Versus Arousal .................................... 41 iii LIST OF TABLES Page TABLE I, Mean T600 Recognition Error Rates.................... 20 TABLE Ii ...34 ~ __________ An Akai model 4000DS Mk II reel-to-reel tape recorder was connected to the Maico Audiometer and used to present stimuli to the subject. E

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

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed

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

    2015-07-23

    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.

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

    PubMed Central

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

    2017-01-01

    The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel in the following three ways compared to previous studies. First, we use the images of human body for recognizing individuals. To overcome the limitations of previous studies on body-based person recognition that use only visible light images for recognition, we use human body images captured by two different kinds of camera, including a visible light camera and a thermal camera. The use of two different kinds of body image helps us to reduce the effects of noise, background, and variation in the appearance of a human body. Second, we apply a state-of-the art method, called convolutional neural network (CNN) among various available methods, for image features extraction in order to overcome the limitations of traditional hand-designed image feature extraction methods. Finally, with the extracted image features from body images, the recognition task is performed by measuring the distance between the input and enrolled samples. The experimental results show that the proposed method is efficient for enhancing recognition accuracy compared to systems that use only visible light or thermal images of the human body. PMID:28300783

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

    PubMed

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

    2017-03-16

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

  7. 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

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

    PubMed

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

    2016-12-01

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

  9. Systemic and intra-rhinal-cortical 17-β estradiol administration modulate object-recognition memory in ovariectomized female rats.

    PubMed

    Gervais, Nicole J; Jacob, Sofia; Brake, Wayne G; Mumby, Dave G

    2013-09-01

    Previous studies using the novel-object-preference (NOP) test suggest that estrogen (E) replacement in ovariectomized rodents can lead to enhanced novelty preference. The present study aimed to determine: 1) whether the effect of E on NOP performance is the result of enhanced preference for novelty, per se, or facilitated object-recognition memory, and 2) whether E affects NOP performance through actions it has within the perirhinal cortex/entorhinal cortex region (PRh/EC). Ovariectomized rats received either systemic chronic low 17-β estradiol (E2; ~20 pg/ml serum) replacement alone or in combination with systemic acute high administration of estradiol benzoate (EB; 10 μg), or in combination with intracranial infusions of E2 (244.8 pg/μl) or vehicle into the PRh/EC. For one of the intracranial experiments, E2 was infused either immediately before, immediately after, or 2 h following the familiarization (i.e., learning) phase of the NOP test. In light of recent evidence that raises questions about the internal validity of the NOP test as a method of indexing object-recognition memory, we also tested rats on a delayed nonmatch-to-sample (DNMS) task of object recognition following systemic and intra-PRh/EC infusions of E2. Both systemic acute and intra-PRh/EC infusions of E enhanced novelty preference, but only when administered either before or immediately following familiarization. In contrast, high E (both systemic acute and intra-PRh/EC) impaired performance on the DNMS task. The findings suggest that while E2 in the PRh/EC can enhance novelty preference, this effect is probably not due to an improvement in object-recognition abilities.

  10. 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

  11. 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.…

  12. AFRL/HECP Speaker Recognition Systems for the 2004 NIST Speaker Recognition Evaluation

    DTIC Science & Technology

    2007-11-02

    every 10 msec. For the work described here, the Entropic get-fO command was used to estimate FO and the probability of voicing. Next, one uses a peak...picker to determine the quasi-periodic instants of maximum excitation in the residual, which are assumed to correspond to glottal closures. The Entropic ...the probability of voicing were determined every 10 msec using the Entropic Signal Processing System (ESPS) get-fO command. Next, the first three

  13. Vision-based object detection and recognition system for intelligent vehicles

    NASA Astrophysics Data System (ADS)

    Ran, Bin; Liu, Henry X.; Martono, Wilfung

    1999-01-01

    Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

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

    PubMed

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

    2014-01-01

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

  15. Duality of the carbohydrate-recognition system of Pseudomonas aeruginosa-II lectin (PA-IIL).

    PubMed

    Wu, Albert M; Gong, Yu-Ping; Li, Chia-Chen; Gilboa-Garber, Nechama

    2010-06-03

    The study of Pseudomonas aeruginosa-II lectin (PA-IIL) complexes with Man derivatives as a recognition factor has been neglected since its monomer is a very weak ligand. Here, the roles of Man oligomers and complexes in PA-IIL carbohydrate-recognition were studied by both enzyme-linked lectinosorbent and inhibition assays. From the results obtained, it is proposed that high density weak -OH conformation as seen in yeast mannan is also an important PA-IIL recognition factor. This finding provides a peculiar concept of the duality of PA-IIL recognition system for LFucalpha1--> and related complexes and for high density Manalpha1--> complexes present in polymannosylated target macromolecules.

  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.

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

    PubMed

    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.

  18. 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

  19. 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

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

    PubMed

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

    2015-06-29

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

  1. 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.

  2. Patient State Recognition System for Healthcare Using Speech and Facial Expressions.

    PubMed

    Hossain, M Shamim

    2016-12-01

    Smart, interactive healthcare is necessary in the modern age. Several issues, such as accurate diagnosis, low-cost modeling, low-complexity design, seamless transmission, and sufficient storage, should be addressed while developing a complete healthcare framework. In this paper, we propose a patient state recognition system for the healthcare framework. We design the system in such a way that it provides good recognition accuracy, provides low-cost modeling, and is scalable. The system takes two main types of input, video and audio, which are captured in a multi-sensory environment. Speech and video input are processed separately during feature extraction and modeling; these two input modalities are merged at score level, where the scores are obtained from the models of different patients' states. For the experiments, 100 people were recruited to mimic a patient's states of normal, pain, and tensed. The experimental results show that the proposed system can achieve an average 98.2 % recognition accuracy.

  3. A multi-agent system simulating human splice site recognition.

    PubMed

    Vignal, L; Lisacek, F; Quinqueton, J; d'Aubenton-Carafa, Y; Thermes, C

    1999-06-15

    The present paper describes a method detecting splice sites automatically on the basis of sequence data and models of site/signal recognition supported by experimental evidences. The method is designed to simulate splicing and while doing so, track prediction failures, missing information and possibly test correcting hypotheses. Correlations between nucleotides in the splice site regions and the various elements of the acceptor region are evaluated and combined to assess compensating interactions between elements of the splicing machinery. A scanning model of the acceptor region and a model of interaction between the splicing complexes (exon definition model) are also incorporated in the detection process. Subsets of sites presenting deficiencies of several splice site elements could be identified. Further examination of these sites helps to determine lacking elements and refine models.

  4. A genotypic mutation system measuring mutations in restriction recognition sequences.

    PubMed Central

    Felley-Bosco, E; Pourzand, C; Zijlstra, J; Amstad, P; Cerutti, P

    1991-01-01

    The RFLP/PCR approach (restriction fragment length polymorphism/polymerase chain reaction) to genotypic mutation analysis described here measures mutations in restriction recognition sequences. Wild-type DNA is restricted before the resistant, mutated sequences are amplified by PCR and cloned. We tested the capacity of this experimental design to isolate a few copies of a mutated sequence of the human c-Ha-ras1 gene from a large excess of wild-type DNA. For this purpose we constructed a 272 bp fragment with 2 mutations in the PvuII recognition sequence 1727-1732 and studied the rescue by RFLP/PCR of a few copies of this 'PvuII mutant standard'. Following amplification with Taq-polymerase and cloning into lambda gt10, plaques containing wild-type sequence, PvuII mutant standard or Taq-polymerase induced bp changes were quantitated by hybridization with specific oligonucleotide probes. Our results indicate that 10 PvuII mutant standard copies can be rescued from 10(8) to 10(9) wild-type sequences. Taq polymerase errors originating from unrestricted, residual wild-type DNA were sequence dependent and consisted mostly of transversions originating at G.C bp. In contrast to a doubly mutated 'standard' the capacity to rescue single bp mutations by RFLP/PCR is limited by Taq-polymerase errors. Therefore, we assessed the capacity of our protocol to isolate a G to T transversion mutation at base pair 1698 of the MspI-site 1695-1698 of the c-Ha-ras1 gene from excess wild-type ras1 DNA. We found that 100 copies of the mutated ras1 fragment could be readily rescued from 10(8) copies of wild-type DNA. Images PMID:1676153

  5. 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.

  6. 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…

  7. An Event-Based Neurobiological Recognition System with Orientation Detector for Objects in Multiple Orientations

    PubMed Central

    Wang, Hanyu; Xu, Jiangtao; Gao, Zhiyuan; Lu, Chengye; Yao, Suying; Ma, Jianguo

    2016-01-01

    A new multiple orientation event-based neurobiological recognition system is proposed by integrating recognition and tracking function in this paper, which is used for asynchronous address-event representation (AER) image sensors. The characteristic of this system has been enriched to recognize the objects in multiple orientations with only training samples moving in a single orientation. The system extracts multi-scale and multi-orientation line features inspired by models of the primate visual cortex. An orientation detector based on modified Gaussian blob tracking algorithm is introduced for object tracking and orientation detection. The orientation detector and feature extraction block work in simultaneous mode, without any increase in categorization time. An addresses lookup table (addresses LUT) is also presented to adjust the feature maps by addresses mapping and reordering, and they are categorized in the trained spiking neural network. This recognition system is evaluated with the MNIST dataset which have played important roles in the development of computer vision, and the accuracy is increased owing to the use of both ON and OFF events. AER data acquired by a dynamic vision senses (DVS) are also tested on the system, such as moving digits, pokers, and vehicles. The experimental results show that the proposed system can realize event-based multi-orientation recognition. The work presented in this paper makes a number of contributions to the event-based vision processing system for multi-orientation object recognition. It develops a new tracking-recognition architecture to feedforward categorization system and an address reorder approach to classify multi-orientation objects using event-based data. It provides a new way to recognize multiple orientation objects with only samples in single orientation. PMID:27867346

  8. An Event-Based Neurobiological Recognition System with Orientation Detector for Objects in Multiple Orientations.

    PubMed

    Wang, Hanyu; Xu, Jiangtao; Gao, Zhiyuan; Lu, Chengye; Yao, Suying; Ma, Jianguo

    2016-01-01

    A new multiple orientation event-based neurobiological recognition system is proposed by integrating recognition and tracking function in this paper, which is used for asynchronous address-event representation (AER) image sensors. The characteristic of this system has been enriched to recognize the objects in multiple orientations with only training samples moving in a single orientation. The system extracts multi-scale and multi-orientation line features inspired by models of the primate visual cortex. An orientation detector based on modified Gaussian blob tracking algorithm is introduced for object tracking and orientation detection. The orientation detector and feature extraction block work in simultaneous mode, without any increase in categorization time. An addresses lookup table (addresses LUT) is also presented to adjust the feature maps by addresses mapping and reordering, and they are categorized in the trained spiking neural network. This recognition system is evaluated with the MNIST dataset which have played important roles in the development of computer vision, and the accuracy is increased owing to the use of both ON and OFF events. AER data acquired by a dynamic vision senses (DVS) are also tested on the system, such as moving digits, pokers, and vehicles. The experimental results show that the proposed system can realize event-based multi-orientation recognition. The work presented in this paper makes a number of contributions to the event-based vision processing system for multi-orientation object recognition. It develops a new tracking-recognition architecture to feedforward categorization system and an address reorder approach to classify multi-orientation objects using event-based data. It provides a new way to recognize multiple orientation objects with only samples in single orientation.

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

    NASA Astrophysics Data System (ADS)

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

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

  10. 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.

  11. A Chemical Sensor Pattern Recognition System Using a Self-Training Neural Network Classifier With Automated Outlier Detection

    DTIC Science & Technology

    1998-04-17

    A device and method for a pattern recognition system using a self-training neural network classifier with automated outlier detection for use in...chemical sensor array systems. The pattern recognition system uses a Probabilistic Neural Network (PNN) training computer system to develop automated

  12. 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.

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

    PubMed Central

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

    2016-01-01

    Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise. PMID:27916948

  14. 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.

  15. Localization and recognition of traffic signs for automated vehicle control systems

    NASA Astrophysics Data System (ADS)

    Zadeh, Mahmoud M.; Kasvand, T.; Suen, Ching Y.

    1998-01-01

    We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched.

  16. Object oriented image analysis based on multi-agent recognition system

    NASA Astrophysics Data System (ADS)

    Tabib Mahmoudi, Fatemeh; Samadzadegan, Farhad; Reinartz, Peter

    2013-04-01

    In this paper, the capabilities of multi-agent systems are used in order to solve object recognition difficulties in complex urban areas based on the characteristics of WorldView-2 satellite imagery and digital surface model (DSM). The proposed methodology has three main steps: pre-processing of dataset, object based image analysis and multi-agent object recognition. Classified regions obtained from object based image analysis are used as input datasets in the proposed multi-agent system in order to modify/improve results. In the first operational level of the proposed multi-agent system, various kinds of object recognition agents modify initial classified regions based on their spectral, textural and 3D structural knowledge. Then, in the second operational level, 2D structural knowledge and contextual relations are used by agents for reasoning and modification. Evaluation of the capabilities of the proposed object recognition methodology is performed on WorldView-2 imagery over Rio de Janeiro (Brazil) which has been collected in January 2010. According to the obtained results of the object based image analysis process, contextual relations and structural descriptors have high potential to modify general difficulties of object recognition. Using knowledge based reasoning and cooperative capabilities of agents in the proposed multi-agent system in this paper, most of the remaining difficulties are decreased and the accuracy of object based image analysis results is improved for about three percent.

  17. Surface imprinted thin polymer film systems with selective recognition for bovine serum albumin.

    PubMed

    Kryscio, David R; Peppas, Nicholas A

    2012-03-09

    Molecularly imprinted polymers are synthetic antibody mimics formed by the crosslinking of organic or inorganic polymers in the presence of an analyte which yields recognitive polymer networks with specific binding pockets for that biomolecule. Surface imprinted polymers were synthesized via a novel technique for the specific recognition of bovine serum albumin (BSA). Thin films of recognitive networks based on 2-(dimethylamino)ethyl methacrylate (DMAEMA) as the functional monomer and varying amounts of either N,N'-methylenebisacrylamide (MBA) or poly(ethylene glycol) (400) dimethacrylate (PEG400DMA) as the crosslinking agent were synthesized via UV free-radical polymerization and characterized. A clear and reproducible increase in recognition of the template BSA was demonstrated for these systems at 1.6-2.5 times more BSA recognized by the MIP sample relative to the control polymers. Additionally, these polymers exhibited selective recognition of the template relative to competing proteins with up to 2.9 times more BSA adsorbed than either glucose oxidase or bovine hemoglobin. These synthetic antibody mimics hold significant promise as the next generation of robust recognition elements in a wide range of bioassay and biosensor applications.

  18. Face recognition systems in monkey and human: are they the same thing?

    PubMed

    Yovel, Galit; Freiwald, Winrich A

    2013-01-01

    Primate societies are based on face recognition. Face recognition mechanisms have been studied most extensively in humans and macaque monkeys. In both species, multiple brain areas specialized for face processing have been found, and their functional properties are characterized with increasing detail, so we can now begin to address questions about similarities and differences of face-recognition systems across species with 25 million years of separate evolution. Both systems are organized into multiple face-selective cortical areas in spatial arrangements and with functional specializations, implying both hierarchical and parallel modes of information processing. Yet open questions about homologies remain. To address these, future studies employing similar techniques and experimental designs across multiple species are needed to identify a putative core primate face processing system and to understand its differentiations into the multiple branches of the primate order.

  19. Face recognition systems in monkey and human: are they the same thing?

    PubMed Central

    2013-01-01

    Primate societies are based on face recognition. Face recognition mechanisms have been studied most extensively in humans and macaque monkeys. In both species, multiple brain areas specialized for face processing have been found, and their functional properties are characterized with increasing detail, so we can now begin to address questions about similarities and differences of face-recognition systems across species with 25 million years of separate evolution. Both systems are organized into multiple face-selective cortical areas in spatial arrangements and with functional specializations, implying both hierarchical and parallel modes of information processing. Yet open questions about homologies remain. To address these, future studies employing similar techniques and experimental designs across multiple species are needed to identify a putative core primate face processing system and to understand its differentiations into the multiple branches of the primate order. PMID:23585928

  20. 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…

  1. Real-time unconstrained object recognition: a processing pipeline based on the mammalian visual system.

    PubMed

    Aguilar, Mario; Peot, Mark A; Zhou, Jiangying; Simons, Stephen; Liao, Yuwei; Metwalli, Nader; Anderson, Mark B

    2012-03-01

    The mammalian visual system is still the gold standard for recognition accuracy, flexibility, efficiency, and speed. Ongoing advances in our understanding of function and mechanisms in the visual system can now be leveraged to pursue the design of computer vision architectures that will revolutionize the state of the art in computer vision.

  2. 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…

  3. What is a nice smile like that doing in a place like this? Automatic affective responses to environments influence the recognition of facial expressions.

    PubMed

    Hietanen, Jari K; Klemettilä, Terhi; Kettunen, Jani E; Korpela, Kalevi M

    2007-09-01

    An affective priming paradigm with pictures of environmental scenes and facial expressions as primes and targets, respectively, was employed in order to investigate the role of natural (e.g., vegetation) and built elements (e.g., buildings) in eliciting rapid affective responses. In Experiment 1, images of environmental scenes were digitally manipulated to make continua of priming pictures with a gradual increase of natural elements (and a decrease of built elements). The primes were followed by presentations of facial expressions of happiness and disgust as to-be-recognized target stimuli. The recognition times of happy faces decreased and the recognition times of disgusted faces increased as the quantity of natural/built material present in the primes increased/decreased. The physical changes also influenced the evaluated restorativeness and affective valence of the primes. In Experiment 2, the primes used in Experiment 1 were manipulated in such a way that they were void of any recognizable natural or built elements but contained either similar colours or similar shapes as primes in Experiment 1. This time the results showed no effect of priming. These results were interpreted to give support for a view that the priming effect by environmental pictures is due to the primes representing environmental scenes and not due to the presence of certain low-level colour or shape information in the primes. In all, the present results provide evidence that perception of environmental scenes elicits automatic affective responses and influences recognition of facial expressions.

  4. 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.

  5. 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.

  6. 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).

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

    NASA Astrophysics Data System (ADS)

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

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

  8. Performance of a neural-network-based 3-D object recognition system

    NASA Astrophysics Data System (ADS)

    Rak, Steven J.; Kolodzy, Paul J.

    1991-08-01

    Object recognition in laser radar sensor imagery is a challenging application of neural networks. The task involves recognition of objects at a variety of distances and aspects with significant levels of sensor noise. These variables are related to sensor parameters such as sensor signal strength and angular resolution, as well as object range and viewing aspect. The effect of these parameters on a fixed recognition system based on log-polar mapped features and an unsupervised neural network classifier are investigated. This work is an attempt to quantify the design parameters of a laser radar measurement system with respect to classifying and/or identifying objects by the shape of their silhouettes. Experiments with vehicle silhouettes rotated through 90 deg-of-view angle from broadside to head-on ('out-of-plane' rotation) have been used to quantify the performance of a log-polar map/neural-network based 3-D object recognition system. These experiments investigated several key issues such as category stability, category memory compression, image fidelity, and viewing aspect. Initial results indicate a compression from 720 possible categories (8 vehicles X 90 out-of-plane rotations) to a classifier memory with approximately 30 stable recognition categories. These results parallel the human experience of studying an object from several viewing angles yet recognizing it through a wide range of viewing angles. Results are presented illustrating category formation for an eight vehicle dataset as a function of several sensor parameters. These include: (1) sensor noise, as a function of carrier-to-noise ratio; (2) pixels on the vehicle, related to angular resolution and target range; and (3) viewing aspect, as related to sensor-to-platform depression angle. This work contributes to the formation of a three- dimensional object recognition system.

  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. Speech recognition abilities of adults using cochlear implants with FM systems.

    PubMed

    Schafer, Erin C; Thibodeau, Linda M

    2004-01-01

    Speech recognition was evaluated for ten adults with normal hearing and eight adults with Nucleus cochlear implants (CIs) at several different signal-to-noise ratios (SNRs) and with three frequency modulated (FM) system arrangements: desktop, body worn, and miniature direct connect. Participants were asked to repeat Hearing in Noise Test (HINT) sentences presented with speech noise in a classroom setting and percent correct word repetition was determined. Performance was evaluated for both normal-hearing and CI participants with the desktop soundfield system. In addition, speech recognition for the CI participants was evaluated using two FM systems electrically coupled to their speech processors. When comparing the desktop sound field and the No-FM condition, only the listeners with normal hearing made significant improvements in speech recognition in noise. When comparing the performance across the three FM conditions for the CI listeners, the two electrically coupled FM systems resulted in significantly greater improvements in speech recognition in noise relative to the desktop soundfield system.

  11. Practical and cost-efficient design of fingerprint recognition system based on DSP

    NASA Astrophysics Data System (ADS)

    Ran, Chongjie; Xie, Mei

    2007-12-01

    In this paper, a practical and cost-efficient fingerprint recognition system model is proposed. It completes the functions of capturing fingerprint image, data transmission and fingerprint recognition. This system consists of six modules: Management Module (including TMS320VC5502 DSP and memories), Fingerprint Sensor Module (used to collect fingerprint image), Output Module (the interface to control electronic lock), Human-Machine Communication Module (seven-segment LED and keyboard), Debugger Interface Module (JTAG), Power Manager and Power Switchover Module. Unlike other fingerprint recognition systems, this system takes TI C5502 as core processor. It is a high-performance, low-power and fixed-point DSP and the whole system power can be supplied by batteries. The whole system can work more than 10000 times with batteries. In addition, a Power Switch Module, which can automatic switch the ways of power supply between wall adapter and batteries, is proposed in this paper. Furthermore, some software optimization makes this system practical. The design not only simplifies system's structure and reduces the cost of hardware, but also decreases the consumption of system power and resources. So, this hardware system can be used in practical applications, such as portable identification device, fingerprint lock etc. This system is mainly designed for fingerprint lock in this paper.

  12. A dynamic gesture recognition system for the Korean sign language (KSL).

    PubMed

    Kim, J S; Jang, W; Bien, Z

    1996-01-01

    The sign language is a method of communication for the deaf-mute. Articulated gestures and postures of hands and fingers are commonly used for the sign language. This paper presents a system which recognizes the Korean sign language (KSL) and translates into a normal Korean text. A pair of data-gloves are used as the sensing device for detecting motions of hands and fingers. For efficient recognition of gestures and postures, a technique of efficient classification of motions is proposed and a fuzzy min-max neural network is adopted for on-line pattern recognition.

  13. Pay for Performance. Implementation of the Performance Management and Recognition System.

    ERIC Educational Resources Information Center

    General Accounting Office, Washington, DC.

    This report describes the activities of five federal agencies as they made the transition from merit pay to the Performance Management and Recognition System (PMRS) during fiscal year 1985. It also discusses how PMRS addressed the problems identified with merit pay. In addition, the report presents information on the pay increases and performance…

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  15. Talking Back to Big Bird: Preschool Users and a Simple Speech Recognition System.

    ERIC Educational Resources Information Center

    Strommen, Erik F.; Frome, Francine S.

    1993-01-01

    Describes a study that examined the effectiveness of 1 configuration of automatic speech recognition software and hardware with 36 3 year olds and a comparison control group of 20 adults. The greater variability of children's speech is discussed; possible system modifications are considered; and future research is suggested. (18 references) (LRW)

  16. 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…

  17. Summary of the transfer of optical processing to systems: optical pattern recognition program

    NASA Astrophysics Data System (ADS)

    Lindell, Scott D.

    1995-06-01

    Martin Marietta has successfully completed a TOPS optical pattern recognition program. The program culminated in August 1994 with an automatic target recognition flight demonstration inwhich an M60A2 tank was acquired, identified, and tracked with a visible seeker from a UH-1 helicopter flying a fiber optic guided missile (FOG-M) mission profile. The flight demonstration was conducted by the US Army Missile Command (MICOM) and supported by Martin Marietta. The pattern recognition system performance for acquiring and identifying the M60A2 tank, which was positioned among an array with five other vehicle types, was 90% probability of correct identification and a 4% false identification for over 40,000 frames of imagery processed. Imagery was processed at a 15 Hz input rate with a 1 ft3, 76 W, 4 GFLOP processor performing up to 800 correlations per second.

  18. Neuro-parity pattern recognition system and method

    DOEpatents

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

    2000-01-01

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

  19. Data management in pattern recognition and image processing systems

    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. Emotion recognition system using short-term monitoring of physiological signals.

    PubMed

    Kim, K H; Bang, S W; Kim, S R

    2004-05-01

    A physiological signal-based emotion recognition system is reported. The system was developed to operate as a user-independent system, based on physiological signal databases obtained from multiple subjects. The input signals were electrocardiogram, skin temperature variation and electrodermal activity, all of which were acquired without much discomfort from the body surface, and can reflect the influence of emotion on the autonomic nervous system. The system consisted of preprocessing, feature extraction and pattern classification stages. Preprocessing and feature extraction methods were devised so that emotion-specific characteristics could be extracted from short-segment signals. Although the features were carefully extracted, their distribution formed a classification problem, with large overlap among clusters and large variance within clusters. A support vector machine was adopted as a pattern classifier to resolve this difficulty. Correct-classification ratios for 50 subjects were 78.4% and 61.8%, for the recognition of three and four categories, respectively.

  1. 3-D Object Recognition Using Combined Overhead And Robot Eye-In-Hand Vision System

    NASA Astrophysics Data System (ADS)

    Luc, Ren C.; Lin, Min-Hsiung

    1987-10-01

    A new approach for recognizing 3-D objects using a combined overhead and eye-in-hand vision system is presented. A novel eye-in-hand vision system using a fiber-optic image array is described. The significance of this approach is the fast and accurate recognition of 3-D object information compared to traditional stereo image processing. For the recognition of 3-D objects, the over-head vision system will take 2-D top view image and the eye-in-hand vision system will take side view images orthogonal to the top view image plane. We have developed and demonstrated a unique approach to integrate this 2-D information into a 3-D representation based on a new approach called "3-D Volumetric Descrip-tion from 2-D Orthogonal Projections". The Unimate PUMA 560 and TRAPIX 5500 real-time image processor have been used to test the success of the entire system.

  2. 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…

  3. [Creating language model of the forensic medicine domain for developing a autopsy recording system by automatic speech recognition].

    PubMed

    Niijima, H; Ito, N; Ogino, S; Takatori, T; Iwase, H; Kobayashi, M

    2000-11-01

    For the purpose of practical use of speech recognition technology for recording of forensic autopsy, a language model of the speech recording system, specialized for the forensic autopsy, was developed. The language model for the forensic autopsy by applying 3-gram model was created, and an acoustic model for Japanese speech recognition by Hidden Markov Model in addition to the above were utilized to customize the speech recognition engine for forensic autopsy. A forensic vocabulary set of over 10,000 words was compiled and some 300,000 sentence patterns were made to create the forensic language model, then properly mixing with a general language model to attain high exactitude. When tried by dictating autopsy findings, this speech recognition system was proved to be about 95% of recognition rate that seems to have reached to the practical usability in view of speech recognition software, though there remains rooms for improving its hardware and application-layer software.

  4. When does the visual system use viewpoint-invariant representations during recognition?

    PubMed

    Wilson, Kevin D; Farah, Martha J

    2003-05-01

    One popular model of object recognition claims that the visual system typically describes objects using view-specific representations, but that viewpoint-invariant representations are used when objects can be specified uniquely by the arrangement of parts along a single dimension. In a series of three naming experiments using novel, two-dimensional line drawings, we test this hypothesis against alternative accounts of when viewpoint-invariant representations are used during the recognition of upright and viewplane-rotated objects. Experiments 1 and 2 demonstrate that the number of dimensions along which featural information must be represented is the only stimulus feature that influences the type of representation used, consistent with the Tarr and Pinker model. Experiment 3, however, reveals that the use of viewpoint-invariant representations during recognition is not driven purely by stimulus features, and is at least partly under voluntary control. These data suggest that viewpoint-invariant representations are not automatically invoked by the visual system when the requisite stimulus features are present. Rather, our results suggest that top-down control processes, as well as bottom-up stimulus features, jointly determine the conditions under which the visual system uses viewpoint-invariant representations during visual recognition.

  5. 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.

  6. 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%.

  7. 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.

  8. Recognition and dynamics of syntectonic sediment routing systems, southern Pyrenees

    NASA Astrophysics Data System (ADS)

    Allen, P. A.; Duller, R.; Fordyce, S.; Smithells, R.; Springett, J.; Whitchurch, A.; Whittaker, A.; Carter, A.; Fedele, J.-J.

    2009-04-01

    The erosional, transportational and depositional aspects of the biogeochemical cycles involving particulate sediment and solutes are integrated in sediment routing systems. The component parts of these tectonic-geomorphic systems communicate with each other, especially in response to changes in external forcing mechanisms such as tectonic perturbations and climate change; that is, sediment routing systems are characterized by important teleconnections. We are only just beginning to understand how these teleconnections work, and what it means for the spatial and temporal scales of system behaviour. One strategy for investigating the dynamics of sediment routing systems is to link information on the denudation of upstream source regions with downstream patterns of deposition. This is most likely to be fruitful where upstream catchments are tectonically active. Sediment is released into basins whose long-term subsidence is also controlled by tectonic activity. The spatial distribution of subsidence and the magnitude of the sediment discharge from the catchment are critical factors in the dispersal of sediment of different grain size and composition away from a mountain front. We investigate the coarse clastic sediment routing systems of mid-late Eocene age (40-34 Ma) that were deposited in basins located at the boundary of the Axial Zone and the thrust belt of the South-Central Unit on the southern flank of the Pyrenees, Spain. Most of the fan deposits of interest are found in the Pobla Basin, situated north of Tremp, which benefits from outstanding exposure conditions and rigorous previous work on biostratigraphy, magnetostratigraphy and sedimentology (Mellere 1993; Beamud et al. 2003). Distinct fan depositional systems can be identified and mapped on the basis of their sediment composition, detrital thermochronology, facies and architectures, which can be related to correspondingly distinct catchment properties (size, location, exhumational history, lithologies

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

    PubMed Central

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

    2011-01-01

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

  10. 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.

  11. Dynamically reconfigurable multiprocessor system for high-order-bidirectional-associative-memory-based image recognition

    NASA Astrophysics Data System (ADS)

    Wu, Chwan-Hwa; Roland, David A.

    1991-08-01

    In this paper a high-order bidirectional associative memory (HOBAM) based image recognition system and a dynamically reconfigurable multiprocessor system that achieves real- time response are reported. The HOBAM has been utilized to recognize corrupted images of human faces (with hats, glasses, masks, and slight translation and scaling effects). In addition, the HOBAM, incorporated with edge detection techniques, has been used to recognize isolated objects within multiple-object images. Successful recognition rates have been achieved. A dynamically reconfigurable multiprocessor system and parallel software have been developed to achieve real-time response for image recognition. The system consists of Inmos transputers and crossbar switches (IMS C004). The communication links can be dynamically connected by circuit switching. This is the first time and the transputers and crossbar switches are reported to form a low-cost multiprocessor system connected by a switching network. Moreover, the switching network simplifies the design of the communication in parallel software without handling the message routing. Although the HOBAM is a fully connected network, the algorithm minimizes the amount of information that needs to be exchanged between processors using a data compression technique. The detailed design of both hardware and software are discussed in the paper. Significant speedup through parallel processing is accomplished. The architecture of the experimental system is a cost-effective design for an embedded system for neural network applications on computer vision.

  12. Molecular Recognition of Paired Receptors in the Immune System

    PubMed Central

    Kuroki, Kimiko; Furukawa, Atsushi; Maenaka, Katsumi

    2012-01-01

    Cell surface receptors are responsible for regulating cellular function on the front line, the cell membrane. Interestingly, accumulating evidence clearly reveals that the members of cell surface receptor families have very similar extracellular ligand-binding regions but opposite signaling systems, either inhibitory or stimulatory. These receptors are designated as paired receptors. Paired receptors often recognize not only physiological ligands but also non-self ligands, such as viral and bacterial products, to fight infections. In this review, we introduce several representative examples of paired receptors, focusing on two major structural superfamilies, the immunoglobulin-like and the C-type lectin-like receptors, and explain how these receptors distinguish self and non-self ligands to maintain homeostasis in the immune system. We further discuss the evolutionary aspects of these receptors as well as the potential drug targets for regulating diseases. PMID:23293633

  13. Ornament Problem Suppression in Indonesian License Plate Recognition Systems

    NASA Astrophysics Data System (ADS)

    Mahatmaputra Tedjojuwono, Samuel

    2017-03-01

    Based on the original work of fast performance algorithm in detecting Indonesian license plate, the proposed work will solve the error found in the license plate localization process caused by plate like pattern within the image, which was called the ornament problem. Although not in all cases, this problem could exist when a car has banner, regular pattern, car’s front grill, that could miss understood by the system as license plate letters. The proposed work will implement filtering systems instead of machine learning approach. The filtering methods will follows three steps: detection filter based on the number of elements in the vector, based on the letter proportion of a license plate number, and based on the distance between detected letters. This approach will maintain the fast properties of the original algorithm and will increase the accuracy of localizing the license plate within the given image.

  14. 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.

  15. 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.

  16. A primitive-based 3D object recognition system

    NASA Technical Reports Server (NTRS)

    Dhawan, Atam P.

    1988-01-01

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

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

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

  19. 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

  20. Optical sensing systems based on biomolecular recognition of recombinant proteins

    NASA Astrophysics Data System (ADS)

    Salins, Lyndon L.; Schauer-Vukasinovic, Vesna; Daunert, Sylvia

    1998-05-01

    SIte-directed mutagenesis and the associated site-specific fluorescent labeling of proteins can be used to rationally design reagentless fluorescent molecular senors. The phosphate binding protein (PBP) and calmodulin (CaM) bind to phosphate and calcium in a highly specific manner. These ions induce a hinge motion in the proteins, and the resultant conformational change constitutes the basis of the sensor development. By labeling each protein at a specific site with environment-sensitive fluorescent probes, these conformational changes can be monitored and related to the amount of analyte ion present. In this study, the polymerase chain reaction was used to construct mutants of PBP and CaM that have a single cysteine at positions 197 and 109, respectively. Each protein was site-specifically labeled through the sulfhydryl group of the introduced cysteine residue at a single location with an environment-sensitive fluorescent probe. Characterization of the steady-state fluorescence indicated an enhancement of signal intensity upon binding of the analyte ion. Highly sensitive and selective and selective sensing systems for phosphate and calcium were obtained by using this approach.

  1. Security and matching of partial fingerprint recognition systems

    NASA Astrophysics Data System (ADS)

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

    2004-08-01

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

  2. 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

  3. 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

  4. Development of coffee maker service robot using speech and face recognition systems using POMDP

    NASA Astrophysics Data System (ADS)

    Budiharto, Widodo; Meiliana; Santoso Gunawan, Alexander Agung

    2016-07-01

    There are many development of intelligent service robot in order to interact with user naturally. This purpose can be done by embedding speech and face recognition ability on specific tasks to the robot. In this research, we would like to propose Intelligent Coffee Maker Robot which the speech recognition is based on Indonesian language and powered by statistical dialogue systems. This kind of robot can be used in the office, supermarket or restaurant. In our scenario, robot will recognize user's face and then accept commands from the user to do an action, specifically in making a coffee. Based on our previous work, the accuracy for speech recognition is about 86% and face recognition is about 93% in laboratory experiments. The main problem in here is to know the intention of user about how sweetness of the coffee. The intelligent coffee maker robot should conclude the user intention through conversation under unreliable automatic speech in noisy environment. In this paper, this spoken dialog problem is treated as a partially observable Markov decision process (POMDP). We describe how this formulation establish a promising framework by empirical results. The dialog simulations are presented which demonstrate significant quantitative outcome.

  5. 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.

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

    PubMed

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

    2016-01-01

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

  7. A system for large-scale automatic traffic sign recognition and mapping

    NASA Astrophysics Data System (ADS)

    Chigorin, A.; Konushin, A.

    2013-10-01

    We present a system for the large-scale automatic traffic signs recognition and mapping and experimentally justify design choices made for different components of the system. Our system works with more than 140 different classes of traffic signs and does not require labor-intensive labelling of a large amount of training data due to the training on synthetically generated images. We evaluated our system on the large dataset of Russian traffic signs and made this dataset publically available to encourage future comparison.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. BDNF Val66Met polymorphism significantly affects d' in verbal recognition memory at short and long delays.

    PubMed

    Goldberg, Terry E; Iudicello, Jennifer; Russo, Christine; Elvevåg, Brita; Straub, Richard; Egan, Michael F; Weinberger, Daniel R

    2008-01-01

    A functional polymorphism at the val66met locus in the BDNF gene has significant effects on the pro-form of the protein in intracellular trafficking and activity-dependent, but not constitutive, secretion. These differences are thought to underlie several findings in humans related to this polymorphism, including markers of neuronal viability, BOLD activation in medial temporal lobe regions, and some aspects of behavior. However, many important questions remain about the impact of BDNF on various mnemonic subprocesses at the behavioral level. In this study, we examined the impact of the val/met polymorphism in a verbal recognition memory paradigm involving manipulation of depth of encoding and differential delays for recall and analyses of hits for previously presented target words and correct rejections of foils. Twenty-four human val homozygous individuals and 24 met carrier individuals comprised the sample. All were healthy controls. IQ between the groups was equivalent. In the encoding phase of the study, words were presented and encoded either by a decision as to whether they were living or nonliving ("deep") or if they contained the letter "A" (shallow). After this phase, recognition was tested immediately, half an hour, and 24h later. BDNF genotype had significant effects on hits and discriminability (d'), accounting for at least 10% of the variance, but not on correct rejections or beta. BDNF did not interact with level of encoding, nor did it interact with delay. In sum, BDNF genotypes impacted "hits" in a recognition memory paradigm, findings consistent with the general notion that BDNF plays a prominent role in memory subprocesses thought to engage the medial temporal lobe.

  13. 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

  14. The pros and cons of implementing PACS and speech recognition systems.

    PubMed

    Hayt, D B; Alexander, S

    2001-09-01

    The installation and implementation of a hospitalwide image management system and a speech recognition dictation system has had a dramatic and positive impact on radiology report turnaround times at Elmhurst Hospital Center, a 543-bed municipal teaching hospital located in New York City's Borough of Queens. The "lost film" problem has been eliminated. As a result, the percentage of unreported examinations has dropped from 25% to less than 1%. These performance improvements have significantly benefited the entire medical staff. With the successful implementation of a HL-7 standards-based radiology information system (RIS), a speech recognition dictation system, around-the-clock staffing of Board Certified radiologists, and a picture archiving and communication system (PACS), report turnaround time improved dramatically. Eighty-six percent of all examinations now are reported formally within a 12-hour period compared with a 3% average before implementation of the changes. However, with the use of the PACS and speech recognition technologies, new problems have arisen within the radiology department. These technologies, designed to enhance communications capabilities, also have significantly reduced the amount of clinician/radiologist dialogue. Easy and rapid access to patient images and reports has had a detrimental effect on that face-to-face consultations with clinicians, which were commonplace before PACS, and now have almost completely disappeared. The radiologist/clinician interchanges, which occurred frequently before a final report was dictated, often resulted in better understanding of the clinical problem and, hence, a more meaningful final report. Although a conferencing feature to facilitate communication exists within the PACS, it is not utilized by the clinicians. The dilemma is that as information about patients is made more available to the hospital staff, less information is provided about patients to the radiologists. Although the speech recognition

  15. 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…

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

    PubMed

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

    2014-09-03

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

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

    PubMed

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

    2016-10-01

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

  18. Using optical wavelet packet transform to improve the performance of an optoelectronic iris recognition system

    NASA Astrophysics Data System (ADS)

    Cai, De; Tan, Qiaofeng; Yan, Yingbai; Jin, Guofan; He, Qingsheng

    2005-01-01

    Iris, one important biometric feature, has unique advantages: it has complex texture and is almost unchanged for the lifespan. So iris recognition has been widely studied for intelligent personal identification. Most of researchers use wavelets as iris feature extractor. And their systems obtain high accuracy. But wavelet transform is time consuming, so the problem is to enhance the useful information but still keep high processing speed. This is the reason we propose an opto-electronic system for iris recognition because of high parallelism of optics. In this system, we use eigen-images generated corresponding to optimally chosen wavelet packets to compress the iris image bank. After optical correlation between eigen-images and input, the statistic features are extracted. Simulation shows that wavelet packets preprocessing of the input images results in higher identification rate. And this preprocessing can be fulfilled by optical wavelet packet transform (OWPT), a new optical transform introduced by us. To generate the approximations of 2-D wavelet packet basis functions for implementing OWPT, mother wavelet, which has scaling functions, is utilized. Using the cascade algorithm and 2-D separable wavelet transform scheme, an optical wavelet packet filter is constructed based on the selected best bases. Inserting this filter makes the recognition performance better.

  19. Syntax-directed content analysis of videotext: application to a map detection recognition system

    NASA Astrophysics Data System (ADS)

    Aradhye, Hrishikesh; Herson, James A.; Myers, Gregory

    2003-01-01

    Video is an increasingly important and ever-growing source of information to the intelligence and homeland defense analyst. A capability to automatically identify the contents of video imagery would enable the analyst to index relevant foreign and domestic news videos in a convenient and meaningful way. To this end, the proposed system aims to help determine the geographic focus of a news story directly from video imagery by detecting and geographically localizing political maps from news broadcasts, using the results of videotext recognition in lieu of a computationally expensive, scale-independent shape recognizer. Our novel method for the geographic localization of a map is based on the premise that the relative placement of text superimposed on a map roughly corresponds to the geographic coordinates of the locations the text represents. Our scheme extracts and recognizes videotext, and iteratively identifies the geographic area, while allowing for OCR errors and artistic freedom. The fast and reliable recognition of such maps by our system may provide valuable context and supporting evidence for other sources, such as speech recognition transcripts. The concepts of syntax-directed content analysis of videotext presented here can be extended to other content analysis systems.

  20. 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.

  1. 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.

  2. 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.

  3. Dual chiral recognition system involving cyclodextrin derivatives in capillary electrophoresis II. Enhancement of enantioselectivity.

    PubMed

    Jakubetz, H; Juza, M; Schurig, V

    1998-05-01

    The enantiomer separation of hexobarbital was investigated by open tubular electrochromatography (OTEC) using the chiral stationary phase (CSP) CHIRASIL-DEX (a permethylated beta-cyclodextrin covalently linked to a dimethylpolysiloxane) and by cyclodextrin-electrokinetic chromatogaphy (CD-EKC) using anionic beta-cyclodextrin-sulfo-n-propyl ether (SPE-beta-CD) and cationic beta-cyclodextrin-2-hydroxy-3-trimethylammoniumpropyl ether chloride (HTAP-beta-CD) added to the running buffer. By employing two chiral selectors, the enantiomer separation of hexobarbital was then studied simultaneously by OTEC with CHIRASIL-DEX and by CD-EKC with either SPE-beta-CD or HTAP-beta-CD in the dual chiral recognition mode. In conjunction with CHIRASIL-DEX, anionic SPE-beta-CD decreased the chiral separation factor alpha due to compensation of enantioselectivity whereas the cationic additive HTAP-beta-CD increased the chiral separation factor alpha due to enhancement of enantioselectivity. It is concluded that CHIRASIL-DEX imparts an opposite enantioselectivity to the enantiomers of hexobarbital as compared to the charged CDs SPE-beta-CD and HTAP-beta-CD. Unusual peak broadening phenomena are observed in the dual chiral recognition system comprised of CHIRASIL-DEX and HTAP-beta-CD. The possible consequences of accidental dual chiral recognition systems caused by wall stacking effects of the mobile phase additives onto the inner surface of the capillary column are discussed.

  4. 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

  5. Automatic target recognition with image/video understanding systems based on network-symbolic models

    NASA Astrophysics Data System (ADS)

    Kuvich, Gary

    2004-09-01

    In past decades, the solution to ATR problem has been thought of as a solution to the Pattern Recognition problem. The reasons that Pattern Recognition problem has never been solved successfully and reliably for real-world images are more serious than lack of appropriate ideas. Vision is a part of a larger system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. Vision mechanisms cannot be completely understood apart from the informational processes related to knowledge and intelligence. A reliable solution to the ATR problem is possible only within the solution of a more generic Image Understanding Problem. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, converts visual information into relational Network-Symbolic structures, avoiding precise computations of 3-D models. Logic of visual scenes can be captured in Network-Symbolic models and used for disambiguation of visual information. Network-Symbolic Transformations make possible invariant recognition of a real-world object as exemplar of a class. This allows for creating ATR systems, reliable in field conditions.

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

    PubMed

    Müller, L; Weinert, D

    2016-11-01

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

  7. 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.

  8. A commercial large-vocabulary discrete speech recognition system: DragonDictate.

    PubMed

    Mandel, M A

    1992-01-01

    DragonDictate is currently the only commercially available general-purpose, large-vocabulary speech recognition system. It uses discrete speech and is speaker-dependent, adapting to the speaker's voice and language model with every word. Its acoustic adaptability is based in a three-level phonology and a stochastic model of production. The phonological levels are phonemes, augmented triphones (phonemes-in-context or PICs), and steady-state spectral slices that are concatenated to approximate the spectra of these PICs (phonetic elements or PELs) and thus of words. Production is treated as a hidden Markov process, which the recognizer has to identify from its output, the spoken word. Findings of practical value to speech recognition are presented from research on six European languages.

  9. 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.

  10. 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.

  11. 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.

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

    PubMed

    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.

  13. 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

  14. Emotion recognition from physiological signals.

    PubMed

    Gouizi, K; Bereksi Reguig, F; Maaoui, C

    2011-01-01

    Emotion recognition is one of the great challenges in human-human and human-computer interaction. Accurate emotion recognition would allow computers to recognize human emotions and therefore react accordingly. In this paper, an approach for emotion recognition based on physiological signals is proposed. Six basic emotions: joy, sadness, fear, disgust, neutrality and amusement are analysed using physiological signals. These emotions are induced through the presentation of International Affecting Picture System (IAPS) pictures to the subjects. The physiological signals of interest in this analysis are: electromyogram signal (EMG), respiratory volume (RV), skin temperature (SKT), skin conductance (SKC), blood volume pulse (BVP) and heart rate (HR). These are selected to extract characteristic parameters, which will be used for classifying the emotions. The SVM (support vector machine) technique is used for classifying these parameters. The experimental results show that the proposed methodology provides in general a recognition rate of 85% for different emotional states.

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

    NASA Astrophysics Data System (ADS)

    Lhamon, Michael Earl

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

  16. Synthesis of hybrid systems of pattern recognition on the basis of procedure of consecutive correction of decision functions

    NASA Astrophysics Data System (ADS)

    Lapko, V. A.; Lapko, A. V.; Yuronen, Yu P.

    2016-11-01

    Hybrid systems of pattern recognition in the conditions of large volumes of the training selections and not stationarity of classification objects are offered. Asymptotic properties of their decision function are investigated.

  17. A preliminary study on improving the recognition of esophageal speech using a hybrid system based on statistical voice conversion.

    PubMed

    Lachhab, Othman; Di Martino, Joseph; Elhaj, Elhassane Ibn; Hammouch, Ahmed

    2015-01-01

    In this paper, we propose a hybrid system based on a modified statistical GMM voice conversion algorithm for improving the recognition of esophageal speech. This hybrid system aims to compensate for the distorted information present in the esophageal acoustic features by using a voice conversion method. The esophageal speech is converted into a "target" laryngeal speech using an iterative statistical estimation of a transformation function. We did not apply a speech synthesizer for reconstructing the converted speech signal, given that the converted Mel cepstral vectors are used directly as input of our speech recognition system. Furthermore the feature vectors are linearly transformed by the HLDA (heteroscedastic linear discriminant analysis) method to reduce their size in a smaller space having good discriminative properties. The experimental results demonstrate that our proposed system provides an improvement of the phone recognition accuracy with an absolute increase of 3.40 % when compared with the phone recognition accuracy obtained with neither HLDA nor voice conversion.

  18. Neural systems supporting the control of affective and cognitive conflicts.

    PubMed

    Ochsner, Kevin N; Hughes, Brent; Robertson, Elaine R; Cooper, Jeffrey C; Gabrieli, John D E

    2009-09-01

    Although many studies have examined the neural bases of controlling cognitive responses, the neural systems for controlling conflicts between competing affective responses remain unclear. To address the neural correlates of affective conflict and their relationship to cognitive conflict, the present study collected whole-brain fMRI data during two versions of the Eriksen flanker task. For these tasks, participants indicated either the valence (affective task) or the semantic category (cognitive task) of a central target word while ignoring flanking words that mapped onto either the same (congruent) or a different (incongruent) response as the target. Overall, contrasts of incongruent > congruent trials showed that bilateral dorsal ACC, posterior medial frontal cortex, and dorsolateral pFC were active during both kinds of conflict, whereas rostral medial pFC and left ventrolateral pFC were differentially active during affective or cognitive conflict, respectively. Individual difference analyses showed that separate regions of rostral cingulate/ventromedial pFC and left ventrolateral pFC were positively correlated with the magnitude of response time interference. Taken together, the findings that controlling affective and cognitive conflicts depends upon both common and distinct systems have important implications for understanding the organization of control systems in general and their potential dysfunction in clinical disorders.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Chao, Tien-Hsin; Liu, Hua Kuang

    1987-12-01

    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.

  1. 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.

  2. A RFID authentication protocol based on infinite dimension pseudo random number generator for image recognition system

    NASA Astrophysics Data System (ADS)

    Tong, Qiaoling; Zou, Xuecheng; Tong, Hengqing

    2009-10-01

    Radio Frequency Identification (RFID) technology has been widely used in the image recognition system. However, the feature of the RFID system may bring out security threatens. In this paper, we analyze the existing RFID authentication protocols and state an infinite dimension pseudo random number generator to strengthen the protocol security. Then an authentication protocol based on infinite dimension pseudo random number generator is proposed. Compared to the traditional protocols, our method could resist various attack approaches, and protect the tag information and the location privacy of the tag holder efficiently.

  3. Human likeness: cognitive and affective factors affecting adoption of robot-assisted learning systems

    NASA Astrophysics Data System (ADS)

    Yoo, Hosun; Kwon, Ohbyung; Lee, Namyeon

    2016-07-01

    With advances in robot technology, interest in robotic e-learning systems has increased. In some laboratories, experiments are being conducted with humanoid robots as artificial tutors because of their likeness to humans, the rich possibilities of using this type of media, and the multimodal interaction capabilities of these robots. The robot-assisted learning system, a special type of e-learning system, aims to increase the learner's concentration, pleasure, and learning performance dramatically. However, very few empirical studies have examined the effect on learning performance of incorporating humanoid robot technology into e-learning systems or people's willingness to accept or adopt robot-assisted learning systems. In particular, human likeness, the essential characteristic of humanoid robots as compared with conventional e-learning systems, has not been discussed in a theoretical context. Hence, the purpose of this study is to propose a theoretical model to explain the process of adoption of robot-assisted learning systems. In the proposed model, human likeness is conceptualized as a combination of media richness, multimodal interaction capabilities, and para-social relationships; these factors are considered as possible determinants of the degree to which human cognition and affection are related to the adoption of robot-assisted learning systems.

  4. 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

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

    PubMed

    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.

  6. 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.

  7. 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 operationalize the…

  8. 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…

  9. Using Student Support Systems to Increase Cognitive and Affective Outcomes.

    ERIC Educational Resources Information Center

    Soled, Suzanne Wegener; Bosma, Jennifer F.

    1992-01-01

    Student support systems (small groups of students who meet to learn), help combat the problem of large student-to-teacher ratios and increase cognitive and affective outcomes. Small groups allow large amounts of participation and interaction, rapid error correction, individualized practice, and self-paced work that actively involves students in…

  10. 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.

  11. How hippocampus and cortex contribute to recognition memory: revisiting the complementary learning systems model.

    PubMed

    Norman, Kenneth A

    2010-11-01

    We describe how the Complementary Learning Systems neural network model of recognition memory (Norman and O'Reilly (2003) Psychol Rev 104:611-646) can shed light on current debates regarding hippocampal and cortical contributions to recognition memory. We review simulation results illustrating three critical differences in how (according to the model) hippocampus and cortex contribute to recognition memory, all of which derive from the hippocampus' use of pattern separated representations. Pattern separation makes the hippocampus especially well-suited for discriminating between studied items and related lures; it makes the hippocampus especially poorly suited for computing global match; and it imbues the hippocampal ROC curve with a Y-intercept > 0. We also describe a key boundary condition on these differences: When the average level of similarity between items in an experiment is very high, hippocampal pattern separation can fail, at which point the hippocampal model will start to behave like the cortical model. We describe the implications of these simulation results for extant debates over how to describe hippocampal versus cortical contributions and how to measure these contributions.

  12. Performance of Language-Coordinated Collective Systems: A Study of Wine Recognition and Description

    PubMed Central

    Zubek, Julian; Denkiewicz, Michał; Dębska, Agnieszka; Radkowska, Alicja; Komorowska-Mach, Joanna; Litwin, Piotr; Stępień, Magdalena; Kucińska, Adrianna; Sitarska, Ewa; Komorowska, Krystyna; Fusaroli, Riccardo; Tylén, Kristian; Rączaszek-Leonardi, Joanna

    2016-01-01

    Most of our perceptions of and engagements with the world are shaped by our immersion in social interactions, cultural traditions, tools and linguistic categories. In this study we experimentally investigate the impact of two types of language-based coordination on the recognition and description of complex sensory stimuli: that of red wine. Participants were asked to taste, remember and successively recognize samples of wines within a larger set in a two-by-two experimental design: (1) either individually or in pairs, and (2) with or without the support of a sommelier card—a cultural linguistic tool designed for wine description. Both effectiveness of recognition and the kinds of errors in the four conditions were analyzed. While our experimental manipulations did not impact recognition accuracy, bias-variance decomposition of error revealed non-trivial differences in how participants solved the task. Pairs generally displayed reduced bias and increased variance compared to individuals, however the variance dropped significantly when they used the sommelier card. The effect of sommelier card reducing the variance was observed only in pairs, individuals did not seem to benefit from the cultural linguistic tool. Analysis of descriptions generated with the aid of sommelier cards shows that pairs were more coherent and discriminative than individuals. The findings are discussed in terms of global properties and dynamics of collective systems when constrained by different types of cultural practices. PMID:27729875

  13. Fuzzy learning vector quantization neural network and its application for artificial odor recognition system

    NASA Astrophysics Data System (ADS)

    Kusumoputro, Benyamin; Budiarto, Hary; Jatmiko, Wisnu

    2000-03-01

    In this paper, a kind of fuzzy algorithm for learning vector quantization is developed and used as pattern classifiers with a supervised learning paradigm in artificial odor discrimination system. In this type of FLVQ, the neuron activation is derived through fuzziness of the input data, so that the neural system could deal with the statistical of the measurement error directly. During learning,the similarity between the training vector and the reference vectors are calculated, and the winning reference vector is updated in two ways. Firstly, by shifting the central position of the fuzzy reference vector toward or away from the input vector, and secondly, by modifying its fuzziness. Two types of fuzziness modifications are used, i.e., a constant modification factor and a variable modification factor. This type of FLVQ is different in nature with FALVQ, and in this paper, the performance of FNLVQ network is compared with that of FALVQ in artificial odor recognition system. Experimental results show that both FALVQ and FNLVQ provided high recognition probability in determining various learn-category of odors, however, the FNLVQ neural system has the ability to recognize the unlearn-category of odor that could not recognized by FALVQ neural system.

  14. Prediction of Period-Doubling Bifurcation Based on Dynamic Recognition and Its Application to Power Systems

    NASA Astrophysics Data System (ADS)

    Chen, Danfeng; Wang, Cong

    In this paper, a bifurcation prediction approach is proposed based on dynamic recognition and further applied to predict the period-doubling bifurcation (PDB) of power systems. Firstly, modeling of the internal dynamics of nonlinear systems is obtained through deterministic learning (DL), and the modeling results are applied for constructing the dynamic training pattern database. Specifically, training patterns are chosen according to the hierarchical structured knowledge representation based on the qualitative property of dynamical systems, which is capable of arranging the dynamical models into a specific order in the pattern database. Then, a dynamic recognition-based bifurcation prediction approach is suggested. As a result, perturbations implying PDB on the testing patterns can be predicted through the minimum dynamic error between the training patterns and testing patterns by recalling the knowledge restored in the pattern database. Finally, the second-order single-machine to infinite bus power system model is introduced to check the effectiveness of this prediction approach, which implies PDB under small periodic parameter perturbations. The key point that determines the prediction effect mainly lies in two methods: (1) accurate approximation of the unknown system dynamics through DL guarantees the feasibility of the prediction process; (2) the qualitative property of PDB and the generalization ability of DL algorithm ensure the validity of the selected training patterns. Simulations are included to illustrate the effectiveness of the proposed approach.

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

    PubMed Central

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

    2016-01-01

    Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596

  16. 8-Oxoguanine Affects DNA Backbone Conformation in the EcoRI Recognition Site and Inhibits Its Cleavage by the Enzyme

    PubMed Central

    Kiryutin, Alexey S.; Kasymov, Rustem D.; Petrova, Darya V.; Endutkin, Anton V.; Popov, Alexander V.; Yurkovskaya, Alexandra V.; Fedechkin, Stanislav O.; Brockerman, Jacob A.; Zharkov, Dmitry O.; Smirnov, Serge L.

    2016-01-01

    8-oxoguanine is one of the most abundant and impactful oxidative DNA lesions. However, the reasons underlying its effects, especially those not directly explained by the altered base pairing ability, are poorly understood. We report the effect of the lesion on the action of EcoRI, a widely used restriction endonuclease. Introduction of 8-oxoguanine inside, or adjacent to, the GAATTC recognition site embedded within the Drew—Dickerson dodecamer sequence notably reduced the EcoRI activity. Solution NMR revealed that 8-oxoguanine in the DNA duplex causes substantial alterations in the sugar—phosphate backbone conformation, inducing a BI→BII transition. Moreover, molecular dynamics of the complex suggested that 8-oxoguanine, although does not disrupt the sequence-specific contacts formed by the enzyme with DNA, shifts the distribution of BI/BII backbone conformers. Based on our data, we propose that the disruption of enzymatic cleavage can be linked with the altered backbone conformation and dynamics in the free oxidized DNA substrate and, possibly, at the protein—DNA interface. PMID:27749894

  17. 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.

  18. [Pleasure, pain and affectivity in the nervous system].

    PubMed

    Houdart, R

    1999-01-01

    Affectivity plays an essential role in human life. It gives life its quality, and is responsible for what human beings have always considered to be main endeavor happiness. Still, looking for its description or organisation, in physiology or neurology, treatises is fruitless; there only one of its components is described pain, with no mention of pleasure. We wish to show, here, first, that pain and pleasure, depend of a same function, of which they are, of sorts, both extremities, and which in nothing but the most primitive function of the nervous system, and secondly, that this function in one of the components of an "affectivity center", which has its organisation in the limbic system. This center, integrating all the informations that arrives to the nervous system, triggers to each of them neuro-vegetative and neuro-hormonal informations that are "felt" by the organism, and thus transforms the information in a subjective feeling.

  19. RNA-guided complex from a bacterial immune system enhances target recognition through seed sequence interactions.

    PubMed

    Wiedenheft, Blake; van Duijn, Esther; Bultema, Jelle B; Bultema, Jelle; Waghmare, Sakharam P; Waghmare, Sakharam; Zhou, Kaihong; Barendregt, Arjan; Westphal, Wiebke; Heck, Albert J R; Heck, Albert; Boekema, Egbert J; Boekema, Egbert; Dickman, Mark J; Dickman, Mark; Doudna, Jennifer A

    2011-06-21

    Prokaryotes have evolved multiple versions of an RNA-guided adaptive immune system that targets foreign nucleic acids. In each case, transcripts derived from clustered regularly interspaced short palindromic repeats (CRISPRs) are thought to selectively target invading phage and plasmids in a sequence-specific process involving a variable cassette of CRISPR-associated (cas) genes. The CRISPR locus in Pseudomonas aeruginosa (PA14) includes four cas genes that are unique to and conserved in microorganisms harboring the Csy-type (CRISPR system yersinia) immune system. Here we show that the Csy proteins (Csy1-4) assemble into a 350 kDa ribonucleoprotein complex that facilitates target recognition by enhancing sequence-specific hybridization between the CRISPR RNA and complementary target sequences. Target recognition is enthalpically driven and localized to a "seed sequence" at the 5' end of the CRISPR RNA spacer. Structural analysis of the complex by small-angle X-ray scattering and single particle electron microscopy reveals a crescent-shaped particle that bears striking resemblance to the architecture of a large CRISPR-associated complex from Escherichia coli, termed Cascade. Although similarity between these two complexes is not evident at the sequence level, their unequal subunit stoichiometry and quaternary architecture reveal conserved structural features that may be common among diverse CRISPR-mediated defense systems.

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

    PubMed

    Lossef, S V; Schwartz, L H

    1990-09-01

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

  1. Recognition Of Partially Occluded Workpieces By A Knowledge-Based System

    NASA Astrophysics Data System (ADS)

    Serpico, S. B.; Vernazza, G.; Dellepiane, S.; Angela, P.

    1987-01-01

    A knowledge-based system is presented that is oriented toward partially occluded 2-D workpiece recognition in TV camera images. The generalized Hough transform is employed to extract elementary edge patterns. Intrinsic and relational information regarding elementary patterns is computed and then stored inside a net of frames. A similar net of frames is employed for workpiece model representation, for an easy matching with the previous net. A set of production rules provide the heuristics to find hints for locating focus-of-attention regions, while other production rules specify modalities for applying a hypothesis-generation-and-test process. Experimental results on a set of 20 workpieces are reported.

  2. Pattern recognition, attention, and information bottlenecks in the primate visual system

    NASA Astrophysics Data System (ADS)

    Van Essen, David; Olshausen, Bruno A.; Anderson, Clifford H.; Gallant, J. T.

    1991-07-01

    In its evolution, the primate visual system has developed impressive capabilities for recognizing complex patterns in natural images. This process involves many stages of analysis and a variety of information processing strategies. This paper concentrates on the importance of 'information bottlenecks,' which restrict the amount of information that can be handled at different stages of analysis. These steps are crucial for reducing the overwhelming computational complexity associated with recognizing countless objects from arbitrary viewing angles, distances, and perspectives. The process of directed visual attention is an especially important information bottleneck because of its flexibility in determining how information is routed to high-level pattern recognition centers.

  3. 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.

  4. 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.

  5. Pattern recognition system invariant to rotation and scale to identify color images

    NASA Astrophysics Data System (ADS)

    Coronel-Beltrán, Angel

    2014-10-01

    This work presents a pattern recognition digital system based on nonlinear correlations. The correlation peak values given by the system were analyzed by the peak-to-correlation energy (PCE) metric to determine the optimal value of the non-linear coefficient kin the k-law. The system was tested with 18 different color images of butterflies; each image was rotated from 0° to 180° with increments of 1° and scaled ±25% with increments of 1% and to take advantage of the color property of the images the RGB model was employed. The boxplot statistical analysis of the mean with ±2*EE (standard errors) for the PCE values set that the system invariant to rotation and scale has a confidence level at least of 95.4%.

  6. Chronic intracerebroventricular exposure to beta-amyloid(1-40) impairs object recognition but does not affect spontaneous locomotor activity or sensorimotor gating in the rat.

    PubMed

    Nag, S; Tang, F; Yee, B K

    2001-01-01

    This study examined the cognitive effects of chronic in vivo exposure to beta-amyloid(1-40) via the intracerebroventricular route on two distinct paradigms. The first test evaluated a form of early attentional control referred to as sensorimotor gating in which an antecedent weak prepulse stimulus modulates the reactivity to a subsequent startle-eliciting stimulus. The second test utilized the spontaneous preference for a novel object over that of a familiar one in rats as a measure of object recognition memory. We found that beta-amyloid exposure leads to a severe deficit in the object memory test but spares sensorimotor gating. Moreover, unlike the water maze deficit induced by beta-amyloid (Nag et al., in preparation), the deficit on object recognition was resistant to amelioration by systemic physostigmine treatment at a dose of 0.06 mg/kg per day intraperitoneally. The present results add to previous reports that beta-amyloid exposure can lead to deficits on hippocampal lesion sensitive tasks, suggesting that dysfunction of the rhinal cortices in addition to that of the septohippocampal system is implicated in beta-amyloid-induced behavioral impairments. It therefore lends support to the hypothesis that beta-amyloid exposure can lead to severe impairment across multiple memory systems.

  7. 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.

  8. A presence-based context-aware chronic stress recognition system.

    PubMed

    Peternel, Klemen; Pogačnik, Matevž; Tavčar, Rudi; Kos, Andrej

    2012-11-16

    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.

  9. 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.

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

    PubMed Central

    Wu, Minglin; Zhang, Sheng; Dong, Yuhan

    2016-01-01

    In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. PMID:27775625

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

    PubMed

    Wu, Minglin; Zhang, Sheng; Dong, Yuhan

    2016-10-20

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

  12. Brain systems for assessing the affective value of faces

    PubMed Central

    Said, Christopher P.; Haxby, James V.; Todorov, Alexander

    2011-01-01

    Cognitive neuroscience research on facial expression recognition and face evaluation has proliferated over the past 15 years. Nevertheless, large questions remain unanswered. In this overview, we discuss the current understanding in the field, and describe what is known and what remains unknown. In §2, we describe three types of behavioural evidence that the perception of traits in neutral faces is related to the perception of facial expressions, and may rely on the same mechanisms. In §3, we discuss cortical systems for the perception of facial expressions, and argue for a partial segregation of function in the superior temporal sulcus and the fusiform gyrus. In §4, we describe the current understanding of how the brain responds to emotionally neutral faces. To resolve some of the inconsistencies in the literature, we perform a large group analysis across three different studies, and argue that one parsimonious explanation of prior findings is that faces are coded in terms of their typicality. In §5, we discuss how these two lines of research—perception of emotional expressions and face evaluation—could be integrated into a common, cognitive neuroscience framework. PMID:21536552

  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. 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.

  15. 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

  16. 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.

  17. [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

  18. 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.

  19. System Design of Real Time Vehicle Type Recognition Based on Video for Windows (AVI) Files

    NASA Astrophysics Data System (ADS)

    Zhan, Wei; Luo, Zhiqing

    In this system, with technology of motion detection, the data frames include vehicle digital image can be detected automatically from a Video for Windows (AVI) File, at the same time, vehicle type will be recognized and displayed automatically. The system's process consists of five steps: Read the AVI file and decompose it into digital image frames; Motion detection; Vehicle digital image processing; Counting number of black pixels included in vehicle body contour and project on car image; Module of vehicle type classification. In particular, algorithm of vehicle recognition through counting number of black pixels included in vehicle body contour is one innovation algorithm. Experiment on actual AVI files shows: the system design is simple and effective.

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

    PubMed

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

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

  1. 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.

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

    PubMed Central

    Liu, Xinhua; Mei, Huafeng; Lu, Huachang; Kuang, Hailan; Ma, Xiaolin

    2017-01-01

    Recognizing how a vehicle is steered and then alerting drivers in real time is of utmost importance to the vehicle and driver’s safety, since fatal accidents are often caused by dangerous vehicle maneuvers, such as rapid turns, fast lane-changes, etc. Existing solutions using video or in-vehicle sensors have been employed to identify dangerous vehicle maneuvers, but these methods are subject to the effects of the environmental elements or the hardware is very costly. In the mobile computing era, smartphones have become key tools to develop innovative mobile context-aware systems. In this paper, we present a recognition system for dangerous vehicle steering based on the low-cost sensors found in a smartphone: i.e., the gyroscope and the accelerometer. To identify vehicle steering maneuvers, we focus on the vehicle’s angular velocity, which is characterized by gyroscope data from a smartphone mounted in the vehicle. Three steering maneuvers including turns, lane-changes and U-turns are defined, and a vehicle angular velocity matching algorithm based on Fast Dynamic Time Warping (FastDTW) is adopted to recognize the vehicle steering. The results of extensive experiments show that the average accuracy rate of the presented recognition reaches 95%, which implies that the proposed smartphone-based method is suitable for recognizing dangerous vehicle steering maneuvers. PMID:28335540

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

    PubMed

    Liu, Xinhua; Mei, Huafeng; Lu, Huachang; Kuang, Hailan; Ma, Xiaolin

    2017-03-20

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

  4. [Neurological disease and facial recognition].

    PubMed

    Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

    2012-07-01

    To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

  5. Major neurotransmitter systems in dorsal hippocampus and basolateral amygdala control social recognition memory

    PubMed Central

    Garrido Zinn, Carolina; Clairis, Nicolas; Silva Cavalcante, Lorena Evelyn; Furini, Cristiane Regina Guerino; de Carvalho Myskiw, Jociane; Izquierdo, Ivan

    2016-01-01

    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

  6. [Fluorosis of coal burning affects the male reproductive system].

    PubMed

    Li, Jun-Feng; Feng, Jin; Xiao, Yue-Hai; Sun, Fa

    2014-01-01

    Fluorosis of coal burning is a new type of endemic fluorosis in China, which affects the male reproductive system. Furthermore, the content of fluoride in the semen, sperm mortality, sperm concentration and the incidence of infertility are higher in severe fluorosis areas than in mild- and non-fluorosis areas, so are the levels of serum follicle-stimulating hormone and luteinizing hormone. However, the levels of inhibin B, serum testosterone and estradiol show different degrees of reduction in severe fluorosis areas. Accordingly, fluorosis of coal burning, just like other endemic fluorosis, may affect the structure of male reproductive organs, the generation of sperm and reproductive endocrinology, resulting in the decline of men's reproductive ability.

  7. 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

  8. How does obesity affect the endocrine system? A narrative review.

    PubMed

    Poddar, M; Chetty, Y; Chetty, V T

    2017-03-15

    Obesity is a chronic, relapsing medical condition that results from an imbalance of energy expenditure and consumption. It is a leading cause of preventable illness, disability and premature death. The causes of obesity are multifactorial and include behavioural, socioeconomic, genetic, environmental and psychosocial factors. Rarely are endocrine diseases, e.g., hypothyroidism or Cushing's syndrome, the cause of obesity. What is less understood is how obesity affects the endocrine system. In this review, we will discuss the impact of obesity on multiple endocrine systems, including the hypothalamic-pituitary axis, changes in vitamin D homeostasis, gender steroids and thyroid hormones. We will also examine the renin angiotensin aldosterone system and insulin pathophysiology associated with obesity. We will provide a general overview of the biochemical changes that can be seen in patients with obesity, review possible aetiologies of these changes and briefly consider current guidelines on their management. This review will not discuss endocrine causes of obesity.

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

    PubMed

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

    2008-01-01

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

  10. 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.

  11. An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization

    PubMed Central

    Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

    2016-01-01

    In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms. PMID:27809230

  12. Automated, long-range, night/day, active-SWIR face recognition system

    NASA Astrophysics Data System (ADS)

    Lemoff, Brian E.; Martin, Robert B.; Sluch, Mikhail; Kafka, Kristopher M.; Dolby, Andrew; Ice, Robert

    2014-06-01

    Covert, long-range, night/day identification of stationary human subjects using face recognition has been previously demonstrated using the active-SWIR Tactical Imager for Night/Day Extended-Range Surveillance (TINDERS) system. TINDERS uses an invisible, eye-safe, SWIR laser illuminator to produce high-quality facial imagery under conditions ranging from bright sunlight to total darkness. The recent addition of automation software to TINDERS has enabled the autonomous identification of moving subjects at distances greater than 100 m. Unlike typical cooperative, short range face recognition scenarios, where positive identification requires only a single face image, the SWIR wavelength, long distance, and uncontrolled conditions mean that positive identification requires fusing the face matching results from multiple captured images of a single subject. Automation software is required to initially detect a person, lock on and track the person as they move, and select video frames containing high-quality frontal face images for processing. Fusion algorithms are required to combine the matching results from multiple frames to produce a high-confidence match. These automation functions will be described, and results showing automated identification of moving subjects, night and day, at multiple distances will be presented.

  13. 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.

  14. Dispatcher Recognition of Stroke Using the National Academy Medical Priority Dispatch System

    PubMed Central

    Buck, Brian H; Starkman, Sidney; Eckstein, Marc; Kidwell, Chelsea S; Haines, Jill; Huang, Rainy; Colby, Daniel; Saver, Jeffrey L

    2009-01-01

    Background Emergency Medical Dispatchers (EMDs) play an important role in optimizing stroke care if they are able to accurately identify calls regarding acute cerebrovascular disease. This study was undertaken to assess the diagnostic accuracy of the current national protocol guiding dispatcher questioning of 911 callers to identify stroke, QA Guide v 11.1 of the National Academy Medical Priority Dispatch System (MPDS). Methods We identified all Los Angeles Fire Department paramedic transports of patients to UCLA Medical Center during the 12 month period from January to December 2005 in a prospectively maintained database. Dispatcher-assigned MPDS codes for each of these patient transports were abstracted from the paramedic run sheets and compared to final hospital discharge diagnosis. Results Among 3474 transported patients, 96 (2.8%) had a final diagnosis of stroke or transient ischemic attack. Dispatchers assigned a code of potential stroke to 44.8% of patients with a final discharge diagnosis of stroke or TIA. Dispatcher identification of stroke showed a sensitivity of 0.41, specificity of 0.96, positive predictive value of 0.45, and negative predictive value of 0.95. Conclusions Dispatcher recognition of stroke calls using the widely employed MPDS algorithm is suboptimal, with failure to identify more than half of stroke patients as likely stroke. Revisions to the current national dispatcher structured interview and complaint identification algorithm for stroke may facilitate more accurate recognition of stroke by EMDs. PMID:19390065

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

    DOE PAGES

    Upadhyayula, Venkata K. K.; Ghoshroy, Soumitra; Nair, Vinod S.; ...

    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

  16. An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization.

    PubMed

    Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

    2016-10-31

    In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms.

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

    PubMed

    Ottaviani, E; Valensin, S; Franceschi, C

    1998-04-16

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

  18. 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…

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Design and Function of Supramolecular Recognition Systems Based on Guest-Targeting Probe-Modified Cyclodextrin Receptors for ATP.

    PubMed

    Fujita, Kyohhei; Fujiwara, Shoji; Yamada, Tatsuru; Tsuchido, Yuji; Hashimoto, Takeshi; Hayashita, Takashi

    2017-01-20

    In this study, we have developed a rational design strategy to obtain highly selective supramolecular recognition systems of cyclodextrins (CyDs) on the basis of the lock and key principle. We designed and synthesized dipicolylamine (dpa)-modified γ-CyD-Cu(2+) complexes possessing an azobenzene unit (Cu·1-γ-CyD) and examined how they recognized phosphoric acid derivatives in water. The results revealed that Cu·1-γ-CyD recognized ATP with high selectivity over other phosphoric acid derivatives. The significant blue shift in the UV-vis spectra and (1)H NMR analysis suggested that the selective ATP recognition was based on the multipoint interactions between the adenine moiety of ATP and both the CyD cavity and the azobenzene unit in addition to the recognition of phosphoric moieties by the Cu-dpa complex site. Our unique receptor made it capable of distinguishing ATP from AMP and ADP, revealing the discrimination of even a length of one phosphoric group. This study demonstrates that, compared to conventional recognition systems of CyDs, this multipoint recognition system confers a higher degree of selectivity for certain organic molecules, such as ATP, over their similar derivatives.

  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. 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

  6. Characterization of an acromesomelic dysplasia, Grebe type case: novel mutation affecting the recognition motif at the processing site of GDF5.

    PubMed

    Martinez-Garcia, Monica; Garcia-Canto, Eva; Fenollar-Cortes, Maria; Aytes, Antonio Perez; Trujillo-Tiebas, María José

    2016-09-01

    Acromesomelic dysplasia, Grebe type is a very rare skeletal dysplasia characterized by severe dwarfism with marked micromelia and deformation of the upper and lower limbs, with a proximodistal gradient of severity. CDMP1 gene mutations have been associated with Grebe syndrome, Hunter-Thompson syndrome, Du Pan syndrome and brachydactyly type C. The proband is a 4-year-old boy, born of consanguineous Pakistani parents. Radiographic imaging revealed features typical of Grebe syndrome: severe shortening of the forearms with an acromesomelic pattern following a proximodistal gradient, with distal parts more severely affected than medial parts; hypoplastic hands, with the phalangeal zone more affected than the metacarpal zone; and severe hypoplastic tibial/femoral zones in both limbs. After molecular analyses, the p.Arg377Trp variant in a homozygous pattern was identified in the CDMP1 gene in the affected child. In silico and structural analyses predicted the p.Arg377Trp amino acid change to be pathogenic. Of the 34 mutations described in the CDMP1 gene, four different missense mutations have been associated with Grebe syndrome. The CDMP1 gene encodes growth differentiation factor 5 (GDF5), which plays a role in regulation of limb patterning, joint formation and distal bone growth. Homozygous mutations in the mature domain of GDF5 result in severe limb malformations such as the Grebe type or the Hunter-Thompson type of acromesomelic chondrodysplasia. The p.Arg377Trp mutation is located within the recognition motif at the processing site of GDF5 where the sequence RRKRR changes to WRKRR. The genotype-phenotype correlation allowed not only confirmation of the clinical diagnosis but also appropriate genetic counselling to be offered to this family.

  7. Autoimmune disorders affecting both the central and peripheral nervous system.

    PubMed

    Kamm, Christoph; Zettl, Uwe K

    2012-01-01

    Various case series of patients with autoimmune demyelinating disease affecting both the central and peripheral nervous system (CNS and PNS), either sequentially or simultaneously, have been reported for decades, but their frequency is considerably lower than that of the "classical" neurological autoimmune diseases affecting only either CNS or PNS, such as multiple sclerosis (MS), chronic inflammatory demyelinating polyneuropathy (CIDP) or Guillain-Barré-Syndrome (GBS), and attempts to define or even recognize the former as a clinical entity have remained elusive. Frequently, demyelination started with CNS involvement with subsequent PNS pathology, in some cases with a relapsing-remitting course. Three potential mechanisms for the autoimmune etiology of these conditions can be discussed: (I) They could be caused by a common autoimmunological reactivity against myelin antigens or epitopes present in both the central and peripheral nervous system; (II) They could be due to a higher general susceptibility to autoimmune disease, which in some cases may have been caused or exacerbated by immunomodulatory treatment, e.g. b-interferon; (III) Their co-occurrence might be coincidental. Another example of an autoimmune disease variably involving the central or peripheral nervous system or both is the overlapping and continuous clinical spectrum of Fisher syndrome (FS), as a variant of GBS, and Bickerstaff brainstem encephalitis (BBE). Recent data from larger patient cohorts with demonstration of common autoantibodies, antecedent infections, and results of detailed clinical, neuroimaging and neurophysiological investigations suggest that these three conditions are not separate disorders, but rather form a continuous spectrum with variable central and peripheral nervous system involvement. We herein review clinical and paraclinical data and therapeutic options of these disorders and discuss potential underlying common vs. divergent immunopathogenic mechanisms.

  8. 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.

  9. An optimal sensing strategy of a proximity sensor system for recognition and localization of polyhedral objects

    NASA Technical Reports Server (NTRS)

    Lee, Sukhan; Hahn, Hern S.

    1990-01-01

    An algorithm is presented for the recognition and localization of thre-dimensional polyhedral objects based on an optical proximity sensor system capable of measuring the depth and orientation of a local area of an object surface. Emphasis is given to the determination of an optimal sensor trajectory or an optimal probing, for efficient discrimination among all the possible interpretations. The determination of an optimal sensor trajectory for the next probing consists of the selection of optimal beam orientations based on the surface normal vector distribution of the multiple interpretation image (MII) and the selection of an optimal probing plane by projecting the MII onto the projection plane perpendicular to a selected beam orientation and deriving the optimal path on the projection plane. The selection of optimal beam orientation and probing plane is based on the measure of discrimination power of a cluster of surfaces of an MII. Simulation results are shown.

  10. A study of fuzzy logic ensemble system performance on face recognition problem

    NASA Astrophysics Data System (ADS)

    Polyakova, A.; Lipinskiy, L.

    2017-02-01

    Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

  11. 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

  12. Combining users' activity survey and simulators to evaluate human activity recognition systems.

    PubMed

    Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

    2015-04-08

    Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant.

  13. Speech recognition interface to a hospital information system using a self-designed visual basic program: initial experience.

    PubMed

    Callaway, Edward C; Sweet, Clifford F; Siegel, Eliot; Reiser, John M; Beall, Douglas P

    2002-03-01

    Speech recognition (SR) in the radiology department setting is viewed as a method of decreasing overhead expenses by reducing or eliminating transcription services and improving care by reducing report turnaround times incurred by transcription backlogs. The purpose of this study was to show the ability to integrate off-the-shelf speech recognition software into a Hospital Information System in 3 types of military medical facilities using the Windows programming language Visual Basic 6.0 (Microsoft, Redmond, WA). Report turnaround times and costs were calculated for a medium-sized medical teaching facility, a medium-sized nonteaching facility, and a medical clinic. Results of speech recognition versus contract transcription services were assessed between July and December, 2000. In the teaching facility, 2042 reports were dictated on 2 computers equipped with the speech recognition program, saving a total of US dollars 3319 in transcription costs. Turnaround times were calculated for 4 first-year radiology residents in 4 imaging categories. Despite requiring 2 separate electronic signatures, we achieved an average reduction in turnaround time from 15.7 hours to 4.7 hours. In the nonteaching facility, 26600 reports were dictated with average turnaround time improving from 89 hours for transcription to 19 hours for speech recognition saving US dollars 45500 over the same 6 months. The medical clinic generated 5109 reports for a cost savings of US dollars 10650. Total cost to implement this speech recognition was approximately US dollars 3000 per workstation, mostly for hardware. It is possible to design and implement an affordable speech recognition system without a large-scale expensive commercial solution.

  14. A distributed automatic target recognition system using multiple low resolution sensors

    NASA Astrophysics Data System (ADS)

    Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

    2008-04-01

    In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

  15. '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

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

    PubMed

    Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

    2014-07-02

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

  17. 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

  18. Rearing environment affects development of the immune system in neonates.

    PubMed

    Inman, C F; Haverson, K; Konstantinov, S R; Jones, P H; Harris, C; Smidt, H; Miller, B; Bailey, M; Stokes, C

    2010-06-01

    Early-life exposure to appropriate microbial flora drives expansion and development of an efficient immune system. Aberrant development results in increased likelihood of allergic disease or increased susceptibility to infection. Thus, factors affecting microbial colonization may also affect the direction of immune responses in later life. There is a need for a manipulable animal model of environmental influences on the development of microbiota and the immune system during early life. We assessed the effects of rearing under low- (farm, sow) and high-hygiene (isolator, milk formula) conditions on intestinal microbiota and immune development in neonatal piglets, because they can be removed from the mother in the first 24 h for rearing under controlled conditions and, due to placental structure, neither antibody nor antigen is transferred in utero. Microbiota in both groups was similar between 2 and 5 days. However, by 12-28 days, piglets reared on the mother had more diverse flora than siblings reared in isolators. Dendritic cells accumulated in the intestinal mucosa in both groups, but more rapidly in isolator piglets. Importantly, the minority of 2-5-day-old farm piglets whose microbiota resembled that of an older (12-28-day-old) pig also accumulated dendritic cells earlier than the other farm-reared piglets. Consistent with dendritic cell control of T cell function, the effects on T cells occurred at later time-points, and mucosal T cells from high-hygiene, isolator pigs made less interleukin (IL)-4 while systemic T cells made more IL-2. Neonatal piglets may be a valuable model for studies of the effects of interaction between microbiota and immune development on allergy.

  19. 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.

  20. 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.

  1. 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

  2. Human abdomen recognition using camera and force sensor in medical robot system for automatic ultrasound scan.

    PubMed

    Bin Mustafa, Ammar Safwan; Ishii, Takashi; Matsunaga, Yoshiki; Nakadate, Ryu; Ishii, Hiroyuki; Ogawa, Kouji; Saito, Akiko; Sugawara, Motoaki; Niki, Kiyomi; Takanishi, Atsuo

    2013-01-01

    Physicians use ultrasound scans to obtain real-time images of internal organs, because such scans are safe and inexpensive. However, people in remote areas face difficulties to be scanned due to aging society and physician's shortage. Hence, it is important to develop an autonomous robotic system to perform remote ultrasound scans. Previously, we developed a robotic system for automatic ultrasound scan focusing on human's liver. In order to make it a completely autonomous system, we present in this paper a way to autonomously localize the epigastric region as the starting position for the automatic ultrasound scan. An image processing algorithm marks the umbilicus and mammary papillae on a digital photograph of the patient's abdomen. Then, we made estimation for the location of the epigastric region using the distances between these landmarks. A supporting algorithm distinguishes rib position from epigastrium using the relationship between force and displacement. We implemented these algorithms with the automatic scanning system into an apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator. Tests on 14 healthy male subjects showed the apparatus located the epigastric region with a success rate of 94%. The results suggest that image recognition was effective in localizing a human body part.

  3. An automated system for the recognition of various specific rat behaviours.

    PubMed

    van Dam, Elsbeth A; van der Harst, Johanneke E; ter Braak, Cajo J F; Tegelenbosch, Ruud A J; Spruijt, Berry M; Noldus, Lucas P J J

    2013-09-15

    The automated measurement of rodent behaviour is crucial to advance research in neuroscience and pharmacology. Rats and mice are used as models for human diseases; their behaviour is studied to discover and develop new drugs for psychiatric and neurological disorders and to establish the effect of genetic variation on behavioural changes. Such behaviour is primarily labelled by humans. Manual annotation is labour intensive, error-prone and subject to individual interpretation. We present a system for automated behaviour recognition (ABR) that recognises the rat behaviours 'drink', 'eat', 'sniff', 'groom', 'jump', 'rear unsupported', 'rear wall', 'rest', 'twitch' and 'walk'. The ABR system needs no on-site training; the only inputs needed are the sizes of the cage and the animal. This is a major advantage over other systems that need to be trained with hand-labelled data before they can be used in a new experimental setup. Furthermore, ABR uses an overhead camera view, which is more practical in lab situations and facilitates high-throughput testing more easily than a side-view setup. ABR has been validated by comparison with manual behavioural scoring by an expert. For this, animals were treated with two types of psychopharmaca: a stimulant drug (Amphetamine) and a sedative drug (Diazepam). The effects of drug treatment on certain behavioural categories were measured and compared for both analysis methods. Statistical analysis showed that ABR found similar behavioural effects as the human observer. We conclude that our ABR system represents a significant step forward in the automated observation of rodent behaviour.

  4. An interactive VR system based on full-body tracking and gesture recognition

    NASA Astrophysics Data System (ADS)

    Zeng, Xia; Sang, Xinzhu; Chen, Duo; Wang, Peng; Guo, Nan; Yan, Binbin; Wang, Kuiru

    2016-10-01

    Most current virtual reality (VR) interactions are realized with the hand-held input device which leads to a low degree of presence. There is other solutions using sensors like Leap Motion to recognize the gestures of users in order to interact in a more natural way, but the navigation in these systems is still a problem, because they fail to map the actual walking to virtual walking only with a partial body of the user represented in the synthetic environment. Therefore, we propose a system in which users can walk around in the virtual environment as a humanoid model, selecting menu items and manipulating with the virtual objects using natural hand gestures. With a Kinect depth camera, the system tracks the joints of the user, mapping them to a full virtual body which follows the move of the tracked user. The movements of the feet can be detected to determine whether the user is in walking state, so that the walking of model in the virtual world can be activated and stopped by means of animation control in Unity engine. This method frees the hands of users comparing to traditional navigation way using hand-held device. We use the point cloud data getting from Kinect depth camera to recognize the gestures of users, such as swiping, pressing and manipulating virtual objects. Combining the full body tracking and gestures recognition using Kinect, we achieve our interactive VR system in Unity engine with a high degree of presence.

  5. 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

  6. 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

  7. 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

  8. 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

  9. [Alternative tactile system: C-fibers coding the affective aspect].

    PubMed

    Hua, Qing-Ping; Luo, Fei

    2007-10-01

    It has been accepted that human tactile sensation is mediated exclusively by large myelinated (Abeta) fibres. Nevertheless, recent studies indicated a dual mechanoceptive innervation of the skin in various mammals. Besides the known A fibers, the skin is also innervated by slow-conducting, low-threshold, small unmyelinated (C) afferents. These unmyelinated fibers respond vigorously to innocuous skin deformation, but poorly to rapid skin movement. They project to outer lamina II of spinal cord, and form synapse with the secondary sensory neurons. The latter then project to insular cortex via spinothalamic tracts. Functional magnetic resonance imaging (fMRI) studies showed that a slowly moving tactile stimulus along hairy skin produced a strong activation of the insular cortex. Pleasant touch has also been demonstrated to activate orbitofrontal cortex adjacent to areas responding to pleasant taste and smell. Overall, the response characteristics and activated brain regions suggest that they are related with the limbic system and affective aspect rather than tactile discriminative function.

  10. 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.

  11. A Smart Capsule System for Automated Detection of Intestinal Bleeding Using HSL Color Recognition

    PubMed Central

    Liu, Hongying; Yan, Xueping; Jia, Ziru; Pi, Xitian

    2016-01-01

    There are no ideal means for the diagnosis of intestinal bleeding diseases as of now, particularly in the small intestine. This study investigated an intelligent intestinal bleeding detection capsule system based on color recognition. After the capsule is swallowed, the bleeding detection module (containing a color-sensitive adsorptive film that changes color when absorbing intestinal juice,) is used to identify intestinal bleeding features. A hue-saturation-light color space method can be applied to detect bleeding according to the range of H and S values of the film color. Once bleeding features are recognized, a wireless transmission module is activated immediately to send an alarm signal to the outside; an in vitro module receives the signal and sends an alarm. The average power consumption of the entire capsule system is estimated to be about 2.1mW. Owing to its simplicity, reliability, and effectiveness, this system represents a new approach to the clinical diagnosis of intestinal bleeding diseases. PMID:27902728

  12. A vision-based automated guided vehicle system with marker recognition for indoor use.

    PubMed

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-08-07

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

  13. 24/7 security system: 60-FPS color EMCCD camera with integral human recognition

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

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

  14. Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

    PubMed Central

    2010-01-01

    Background In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme. Results The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges. Conclusions The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways. PMID:20470404

  15. 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.

  16. Loneliness and the social monitoring system: Emotion recognition and eye gaze in a real-life conversation.

    PubMed

    Lodder, Gerine M A; Scholte, Ron H J; Goossens, Luc; Engels, Rutger C M E; Verhagen, Maaike

    2016-02-01

    Based on the belongingness regulation theory (Gardner et al., 2005, Pers. Soc. Psychol. Bull., 31, 1549), this study focuses on the relationship between loneliness and social monitoring. Specifically, we examined whether loneliness relates to performance on three emotion recognition tasks and whether lonely individuals show increased gazing towards their conversation partner's faces in a real-life conversation. Study 1 examined 170 college students (Mage = 19.26; SD = 1.21) who completed an emotion recognition task with dynamic stimuli (morph task) and a micro(-emotion) expression recognition task. Study 2 examined 130 college students (Mage = 19.33; SD = 2.00) who completed the Reading the Mind in the Eyes Test and who had a conversation with an unfamiliar peer while their gaze direction was videotaped. In both studies, loneliness was measured using the UCLA Loneliness Scale version 3 (Russell, 1996, J. Pers. Assess., 66, 20). The results showed that loneliness was unrelated to emotion recognition on all emotion recognition tasks, but that it was related to increased gaze towards their conversation partner's faces. Implications for the belongingness regulation system of lonely individuals are discussed.

  17. A text input system developed by using lips image recognition based LabVIEW for the seriously disabled.

    PubMed

    Chen, S C; Shao, C L; Liang, C K; Lin, S W; Huang, T H; Hsieh, M C; Yang, C H; Luo, C H; Wuo, C M

    2004-01-01

    In this paper, we present a text input system for the seriously disabled by using lips image recognition based on LabVIEW. This system can be divided into the software subsystem and the hardware subsystem. In the software subsystem, we adopted the technique of image processing to recognize the status of mouth-opened or mouth-closed depending the relative distance between the upper lip and the lower lip. In the hardware subsystem, parallel port built in PC is used to transmit the recognized result of mouth status to the Morse-code text input system. Integrating the software subsystem with the hardware subsystem, we implement a text input system by using lips image recognition programmed in LabVIEW language. We hope the system can help the seriously disabled to communicate with normal people more easily.

  18. 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.

  19. 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

  20. The impact of sensitive KIT D816V detection on recognition of indolent Systemic Mastocytosis.

    PubMed

    De Matteis, Giovanna; Zanotti, Roberta; Colarossi, Sabrina; De Benedittis, Caterina; Garcia-Montero, Andrès; Bonifacio, Massimiliano; Sartori, Marta; Aprili, Fiorenza; Caruso, Beatrice; Paviati, Elisa; Carli, Giuseppe; Perbellini, Omar; Zamò, Alberto; Bonadonna, Patrizia; Pizzolo, Giovanni; Guidi, Giancesare; Martinelli, Giovanni; Soverini, Simona

    2015-03-01

    Patients with Systemic Mastocytosis (SM) need a highly sensitive diagnostic test for D816V detection of the KIT receptor gene. Along with histology/cytology and flow cytometry evaluation, bone marrow (BM) from 110 consecutive adult patients referred with a suspicion of SM to Multidisciplinary Outpatient Clinic for Mastocytosis in Verona were tested both by Amplification Refractory Mutation System Reverse Transcriptase quantitative real time Polymerase Chain Reaction (ARMS-RT-qPCR) and RT-PCR+Restriction Fragment Length Polymorphism (RFLP) followed by Denaturing-High Performance Liquid Chromatography (D-HPLC) and Sanger sequencing. ARMS-RT-qPCR identified D816V mutation in 77 patients, corresponding to 100% of cases showing CD25(+) mast cells (MCs) whereas RT-PCR+RFLP/D-HPLC+sequencing revealed D816V mutations in 47 patients. According to the 2008 WHO criteria 75 SM, 1 Cutaneous Mastocytosis (CM), 1 monoclonal MC activation syndrome (MMAS), and 1 SM Associated with Haematologic Non-Mast Cell Disorder (SM-AHNMD) were diagnosed. Seventeen out 75 SM patients (23%) would have not satisfied sufficient WHO criteria on the basis of the sole RT-PCR+RFLP: these patients had significantly lower serum tryptase levels and amount of CD25(+) MCs. Therefore, ARMS-RT-qPCR might result particularly useful, in patients that do not fulfil major BM histological criterion, for the recognition of indolent SM with a very low MC burden.

  1. 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

  2. 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.

  3. Contribution of pheromones processed by the main olfactory system to mate recognition in female mammals.

    PubMed

    Baum, Michael J

    2012-01-01

    Until recently it was widely believed that the ability of female mammals (with the likely exception of women) to identify and seek out a male breeding partner relied on the detection of non-volatile male pheromones by the female's vomeronasal organ (VNO) and their subsequent processing by a neural circuit that includes the accessory olfactory bulb (AOB), vomeronasal amygdala, and hypothalamus. Emperical data are reviewed in this paper that demonstrate the detection of volatile pheromones by the main olfactory epithelium (MOE) of female mice which, in turn, leads to the activation of a population of glomeruli and abutting mitral cells in the main olfactory bulb (MOB). Anatomical results along with functional neuroanatomical data demonstrate that some of these MOB mitral cells project to the vomeronasal amygdala. These particular MOB mitral cells were selectively activated (i.e., expressed Fos protein) by exposure to male as opposed to female urinary volatiles. A similar selectivity to opposite sex urinary volatiles was also seen in mitral cells of the AOB of female mice. Behavioral data from female mouse, ferret, and human are reviewed that implicate the main olfactory system, in some cases interacting with the accessory olfactory system, in mate recognition.

  4. Development of Vision Based Multiview Gait Recognition System with MMUGait Database

    PubMed Central

    Ng, Hu; Tan, Wooi-Haw; Tong, Hau-Lee

    2014-01-01

    This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases. PMID:25143972

  5. Aptamers as promising molecular recognition elements for diagnostics and therapeutics in the central nervous system.

    PubMed

    McConnell, Erin M; Holahan, Matthew R; DeRosa, Maria C

    2014-12-01

    Oligonucleotide aptamers are short, synthetic, single-stranded DNA or RNA able to recognize and bind to a multitude of targets ranging from small molecules to cells. Aptamers have emerged as valuable tools for fundamental research, clinical diagnosis, and therapy. Due to their small size, strong target affinity, lack of immunogenicity, and ease of chemical modification, aptamers are an attractive alternative to other molecular recognition elements, such as antibodies. Although it is a challenging environment, the central nervous system and related molecular targets present an exciting potential area for aptamer research. Aptamers hold promise for targeted drug delivery, diagnostics, and therapeutics. Here we review recent advances in aptamer research for neurotransmitter and neurotoxin targets, demyelinating disease and spinal cord injury, cerebrovascular disorders, pathologies related to protein aggregation (Alzheimer's, Parkinson's, and prions), brain cancer (glioblastomas and gliomas), and regulation of receptor function. Challenges and limitations posed by the blood brain barrier are described. Future perspectives for the application of aptamers to the central nervous system are also discussed.

  6. An application of artificial immune recognition system for prediction of diabetes following gestational diabetes.

    PubMed

    Lin, Hung-Chun; Su, Chao-Ton; Wang, Pa-Chun

    2011-06-01

    Diabetes mellitus (DM) is a disease prevalent in population and is not easily perceived in its initial stage but may sway a patient very seriously in later stage. In accordance with the estimation of World Health Organization (WHO), there will be 370 million diabetics which are 5.4% of the global people in 2030, so it becomes more and more important to predict whether a pregnant woman has or is likely to acquire diabetes. This study is conducted with the use of the machine learning-Artificial Immune Recognition System (AIRS)-to assist doctors in predicting pregnant women who have premonition of type 2 diabetes. AIRS is proposed by Andrew Watkins in 2001 and it makes use of the metaphor of the vertebrate immune system to recognize antigens, select clone, and memorize cells. Additionally, AIRS includes a mechanism, limited resource, to restrain the number of memory cells from increasing uncontrollably. It has also showed positive results on problems in which it was applied. The objective of this study is to investigate the feasibility in using AIRS to predict gestational diabetes mellitus (GDM) subsequent DM. The dataset of diabetes has imbalanced data, but the overall classification recall could still reach 62.8%, which is better than the traditional method, logistic regression, and the technique which is thought as one of the powerful classification approaches, support vector machines (SVM).

  7. 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

  8. 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.

  9. 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%.

  10. Multimodal eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  11. Multivariate interactive digital analysis system /MIDAS/ - A new fast multispectral recognition system

    NASA Technical Reports Server (NTRS)

    Kriegler, F.; Marshall, R.; Lampert, S.; Gordon, M.; Cornell, C.; Kistler, R.

    1973-01-01

    The MIDAS system is a prototype, multiple-pipeline digital processor mechanizing the multivariate-Gaussian, maximum-likelihood decision algorithm operating at 200,000 pixels/second. It incorporates displays and film printer equipment under control of a general purpose midi-computer and possesses sufficient flexibility that operational versions of the equipment may be subsequently specified as subsets of the system.

  12. Design of a Virtual Reality System for Affect Analysis in Facial Expressions (VR-SAAFE); application to schizophrenia.

    PubMed

    Bekele, Esubalew; Bian, Dayi; Peterman, Joel; Park, Sohee; Sarkar, Nilanjan

    2016-07-14

    Schizophrenia is a life-long, debilitating psychotic disorder with poor outcome that affects about 1% of the population. Although pharmacotherapy can alleviate some of the acute psychotic symptoms, residual social impairments present a significant barrier that prevents successful rehabilitation. With limited resources and access to social skills training opportunities, innovative technology has emerged as a potentially powerful tool for intervention. In this paper, we present a novel virtual reality (VR)-based system for understanding facial emotion processing impairments that may lead to poor social outcome in schizophrenia. We henceforth call it a VR System for Affect Analysis in Facial Expressions (VR-SAAFE). This system integrates a VR-based task presentation platform that can minutely control facial expressions of an avatar with or without accompanying verbal interaction, with an eye-tracker to quantitatively measure a participants real-time gaze and a set of physiological sensors to infer his/her affective states to allow in-depth understanding of the emotion recognition mechanism of patients with schizophrenia based on quantitative metrics. A usability study with 12 patients with schizophrenia and 12 healthy controls was conducted to examine processing of the emotional faces. Preliminary results indicated that there were significant differences in the way patients with schizophrenia processed and responded towards the emotional faces presented in the VR environment compared with healthy control participants. The preliminary results underscore the utility of such a VR-based system that enables precise and quantitative assessment of social skill deficits in patients with schizophrenia.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Building Responsive Health Systems to Help Communities Affected by Migration: An International Delphi Consensus.

    PubMed

    Pottie, Kevin; Hui, Charles; Rahman, Prinon; Ingleby, David; Akl, Elie A; Russell, Grant; Ling, Li; Wickramage, Kolitha; Mosca, Davide; Brindis, Claire D

    2017-02-03

    Persons affected by migration require health systems that are responsive and adaptable to the needs of both disadvantaged migrants and non-migrant populations. The objective of this study is to support health systems for populations affected by migration.

  19. 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.

  20. 3D face recognition system using cylindrical hidden-layer neural network: spatial domain and its eigenspace domain

    NASA Astrophysics Data System (ADS)

    Kusumoputro, Benyamin; Pangabean, Martha Y.; Rachman, Leila F.

    2001-09-01

    In this paper, a 3-D face recognition system is developed using a modified neural network. This modified neural network is constructed by substituting each of neuron in its hidden layer of conventional multilayer perceptron with a circular-structure of neurons. This neural system is then called as cylindrical-structure of hidden layer neural network (CHL-NN). The neural system is then applied on a real 3-D face image database that consists of 5 Indonesian persons. The images are taken under four different expressions such as neutral, smile, laugh and free expression. The 2-D images is taken from the human face images by gradually changing visual points, which is done by successively varies the camera position from - 90 to +90 with an interval of 15 degree. The experimental result has shown that the average recognition rate of 60% could be achieved when we used the image in its spatial domain. Improvement of the system is then developed, by transforming the image in its spatial domain into its eigenspace domain. Karhunen Loeve transformation technique is used, and each image in the spatial domain is represented as a point in the eigenspace domain. Fisherface method is then utilized as a feature extraction on the eigenspace domain, and using the same database and experimental procedure, the recognition rate of the system could be increased into 84% in average.

  1. 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.

  2. On-Line Pattern Analysis and Recognition System. OLPARS VI. Programmer and System Maintenance Manual,

    DTIC Science & Technology

    1982-06-18

    and not a FORTRAN I/C package, is that some FCRTRAN I/O packages abort a program when the input cannot be interpreted properly. This is totally...GIN(X, Y, CHAR) where all of GIN’s arguements are of integer type. X and Y are the terminal horizontal and vertical coordinates, respectively. CEAR...this initialization routine can be called automatically for the user. When the operating system has special interrupt functions to abort programs

  3. Trend recognition and failure prediction of the attitude determination and control system of the Space Station Freedom

    NASA Astrophysics Data System (ADS)

    Nelson, Kyle S.; Hadden, George D.

    An approach to automated trend recognition and failure prediction in the health parameter data of spacecraft is described. The approach, State-Based Feature Recognition (SBER), combines intelligent data filtering with state machines to detect the presence of features (trends and impending failures) in the health parameter data of spacecraft. SBFR, when implemented in a space-based or ground-based monitoring system, can increase spacecraft autonomy and decrease technician workload. An implemented, prototype Space Station Freedom (SSF) Maintenance and Diagnostic System (SSFMDS) that demonstrates the applicability of SBFR to trend detection and failure prediction will be described. SBFR allows features to be tracked, using specialized state machines, as they develop in a time-independent manner, allowing both short term and long term features to be detected. Each state machine operates independently of the other machines, making simultaneous feature tracking possible.

  4. NOD2 and Toll-Like Receptors Are Nonredundant Recognition Systems of Mycobacterium tuberculosis

    PubMed Central

    2005-01-01

    Infection with Mycobacterium tuberculosis is one of the leading causes of death worldwide. Recognition of M. tuberculosis by pattern recognition receptors is crucial for activation of both innate and adaptive immune responses. In the present study, we demonstrate that nucleotide-binding oligomerization domain 2 (NOD2) and Toll-like receptors (TLRs) are two nonredundant recognition mechanisms of M. tuberculosis. CHO cell lines transfected with human TLR2 or TLR4 were responsive to M. tuberculosis. TLR2 knock-out mice displayed more than 50% defective cytokine production after stimulation with mycobacteria, whereas TLR4-defective mice also released 30% less cytokines compared to controls. Similarly, HEK293T cells transfected with NOD2 responded to stimulation with M. tuberculosis. The important role of NOD2 for the recognition of M. tuberculosis was demonstrated in mononuclear cells of individuals homozygous for the 3020insC NOD2 mutation, who showed an 80% defective cytokine response after stimulation with M. tuberculosis. Finally, the mycobacterial TLR2 ligand 19-kDa lipoprotein and the NOD2 ligand muramyl dipeptide synergized for the induction of cytokines, and this synergism was lost in cells defective in either TLR2 or NOD2. Together, these results demonstrate that NOD2 and TLR pathways are nonredundant recognition mechanisms of M. tuberculosis that synergize for the induction of proinflammatory cytokines. PMID:16322770

  5. 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

  6. 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

  7. Type I-E CRISPR-cas systems discriminate target from non-target DNA through base pairing-independent PAM recognition.

    PubMed

    Westra, Edze R; Semenova, Ekaterina; Datsenko, Kirill A; Jackson, Ryan N; Wiedenheft, Blake; Severinov, Konstantin; Brouns, Stan J J

    2013-01-01

    Discriminating self and non-self is a universal requirement of immune systems. Adaptive immune systems in prokaryotes are centered around repetitive loci called CRISPRs (clustered regularly interspaced short palindromic repeat), into which invader DNA fragments are incorporated. CRISPR transcripts are processed into small RNAs that guide CRISPR-associated (Cas) proteins to invading nucleic acids by complementary base pairing. However, to avoid autoimmunity it is essential that these RNA-guides exclusively target invading DNA and not complementary DNA sequences (i.e., self-sequences) located in the host's own CRISPR locus. Previous work on the Type III-A CRISPR system from Staphylococcus epidermidis has demonstrated that a portion of the CRISPR RNA-guide sequence is involved in self versus non-self discrimination. This self-avoidance mechanism relies on sensing base pairing between the RNA-guide and sequences flanking the target DNA. To determine if the RNA-guide participates in self versus non-self discrimination in the Type I-E system from Escherichia coli we altered base pairing potential between the RNA-guide and the flanks of DNA targets. Here we demonstrate that Type I-E systems discriminate self from non-self through a base pairing-independent mechanism that strictly relies on the recognition of four unchangeable PAM sequences. In addition, this work reveals that the first base pair between the guide RNA and the PAM nucleotide immediately flanking the target sequence can be disrupted without affecting the interference phenotype. Remarkably, this indicates that base pairing at this position is not involved in foreign DNA recognition. Results in this paper reveal that the Type I-E mechanism of avoiding self sequences and preventing autoimmunity is fundamentally different from that employed by Type III-A systems. We propose the exclusive targeting of PAM-flanked sequences to be termed a target versus non-target discrimination mechanism.

  8. The emotion recognition system based on autoregressive model and sequential forward feature selection of electroencephalogram signals.

    PubMed

    Hatamikia, Sepideh; Maghooli, Keivan; Nasrabadi, Ali Motie

    2014-07-01

    Electroencephalogram (EEG) is one of the useful biological signals to distinguish different brain diseases and mental states. In recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from EEG signals. In this research, we introduce an emotion recognition system using autoregressive (AR) model, sequential forward feature selection (SFS) and K-nearest neighbor (KNN) classifier using EEG signals during emotional audio-visual inductions. The main purpose of this paper is to investigate the performance of AR features in the classification of emotional states. To achieve this goal, a distinguished AR method (Burg's method) based on Levinson-Durbin's recursive algorithm is used and AR coefficients are extracted as feature vectors. In the next step, two different feature selection methods based on SFS algorithm and Davies-Bouldin index are used in order to decrease the complexity of computing and redundancy of features; then, three different classifiers include KNN, quadratic discriminant analysis and linear discriminant analysis are used to discriminate two and three different classes of valence and arousal levels. The proposed method is evaluated with EEG signals of available database for emotion analysis using physiological signals, which are recorded from 32 participants during 40 1 min audio visual inductions. According to the results, AR features are efficient to recognize emotional states from EEG signals, and KNN performs better than two other classifiers in discriminating of both two and three valence/arousal classes. The results also show that SFS method improves accuracies by almost 10-15% as compared to Davies-Bouldin based feature selection. The best accuracies are %72.33 and %74.20 for two classes of valence and arousal and %61.10 and %65.16 for three classes, respectively.

  9. 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.

  10. 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.

  11. Neural systems for recognition of emotional prosody: a 3-D lesion study.

    PubMed

    Adolphs, Ralph; Damasio, Hanna; Tranel, Daniel

    2002-03-01

    Which brain regions are associated with recognition of emotional prosody? Are these distinct from those for recognition of facial expression? These issues were investigated by mapping the overlaps of co-registered lesions from 66 brain-damaged participants as a function of their performance in rating basic emotions. It was found that recognizing emotions from prosody draws on the right frontoparietal operculum, the bilateral frontal pole, and the left frontal operculum. Recognizing emotions from prosody and facial expressions draws on the right frontoparietal cortex, which may be important in reconstructing aspects of the emotion signaled by the stimulus. Furthermore, there were regions in the left and right temporal lobes that contributed disproportionately to recognition of emotion from faces or prosody, respectively.

  12. Using pattern recognition as a method for predicting extreme events in natural and socio-economic systems

    NASA Astrophysics Data System (ADS)

    Intriligator, M.

    2011-12-01

    Vladimir (Volodya) Keilis-Borok has pioneered the use of pattern recognition as a technique for analyzing and forecasting developments in natural as well as socio-economic systems. Keilis-Borok's work on predicting earthquakes and landslides using this technique as a leading geophysicist has been recognized around the world. Keilis-Borok has also been a world leader in the application of pattern recognition techniques to the analysis and prediction of socio-economic systems. He worked with Allan Lichtman of American University in using such techniques to predict presidential elections in the U.S. Keilis-Borok and I have worked together with others on the use of pattern recognition techniques to analyze and to predict socio-economic systems. We have used this technique to study the pattern of macroeconomic indicators that would predict the end of an economic recession in the U.S. We have also worked with officers in the Los Angeles Police Department to use this technique to predict surges of homicides in Los Angeles.

  13. Could positive affect help engineer robot control systems?

    PubMed

    Quirin, Markus; Hertzberg, Joachim; Kuhl, Julius; Stephan, Achim

    2011-11-01

    Emotions have long been seen as counteracting rational thought, but over the last decades, they have been viewed as adaptive processes to optimize human (but also animal) behaviour. In particular, positive affect appears to be a functional aspect of emotions closely related to that. We argue that positive affect as understood in Kuhl's PSI model of the human cognitive architecture appears to have an interpretation in state-of-the-art hybrid robot control architectures, which might help tackle some open questions in the field.

  14. A Model-Based System For Object Recognition In Aerial Scenes

    NASA Astrophysics Data System (ADS)

    Cullen, M. F.; Hord, R. M.; Miller, S. F.

    1987-03-01

    Preliminary results of a system that uses model descriptions of objects to predict and match features derived from aerial images are presented. The system is organized into several phases: 1) processing of image scenes to obtain image primitives, 2) goal-oriented sorting of primitives into classes of related features, 3) prediction of the location of object model features in the image, and 4) matching image features to the model predicted features. The matching approach is centered upon a compatibility figure of merit between a set of image features and model features chosen to direct the search. The search process utilizes an iterative hypothesis generation and verication cycle. A "search matrix" is con-structed from image features and model features according to a first approximation of compatibility based upon orientation. Currently, linear features are used as primitives. Input to the matching algorithm is in the form of line segments extracted from an image scene via edge operatiors and a Hough transform technique for grouping. Additional processing is utilized to derive closed boundaries and complete edge descriptions. Line segments are then sorted into specific classes such that, on a higher level, a priori knowledge about a particular scene can be used to control the priority of line segments in the search process. Additional knowledge about the object model under consideration is utilized to construct the search matrix with the classes of line segments most likely containing the model description. It is shown that these techniques result in a, reduction in the size of the object recognition search space and hence in the time to locate the object in the image. The current system is implemented on a Symbolics LispTM machine. While experimentation continues, we have rewritten and tested the search process and several image processing functions for parallel implementation on a Connection Machine TM computer. It is shown that several orders of magnitude faster

  15. 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.

  16. Score-level fusion of two-dimensional and three-dimensional palmprint for personal recognition systems

    NASA Astrophysics Data System (ADS)

    Chaa, Mourad; Boukezzoula, Naceur-Eddine; Attia, Abdelouahab

    2017-01-01

    Two types of scores extracted from two-dimensional (2-D) and three-dimensional (3-D) palmprint for personal recognition systems are merged, introducing a local image descriptor for 2-D palmprint-based recognition systems, named bank of binarized statistical image features (B-BSIF). The main idea of B-BSIF is that the extracted histograms from the binarized statistical image features (BSIF) code images (the results of applying the different BSIF descriptor size with the length 12) are concatenated into one to produce a large feature vector. 3-D palmprint contains the depth information of the palm surface. The self-quotient image (SQI) algorithm is applied for reconstructing illumination-invariant 3-D palmprint images. To extract discriminative Gabor features from SQI images, Gabor wavelets are defined and used. Indeed, the dimensionality reduction methods have shown their ability in biometrics systems. Given this, a principal component analysis (PCA)+linear discriminant analysis (LDA) technique is employed. For the matching process, the cosine Mahalanobis distance is applied. Extensive experiments were conducted on a 2-D and 3-D palmprint database with 10,400 range images from 260 individuals. Then, a comparison was made between the proposed algorithm and other existing methods in the literature. Results clearly show that the proposed framework provides a higher correct recognition rate. Furthermore, the best results were obtained by merging the score of B-BSIF descriptor with the score of the SQI+Gabor wavelets+PCA+LDA method, yielding an equal error rate of 0.00% and a recognition rate of rank-1=100.00%.

  17. Recombinant proteinase 3 produced in different expression systems: recognition by anti-PR3 antibodies.

    PubMed

    van der Geld, Y M; Oost-Kort, W; Limburg, P C; Specks, U; Kallenberg, C G

    2000-10-20

    Anti-neutrophil cytoplasm autoantibodies (ANCA) directed against proteinase 3 (PR3) are highly sensitive and specific markers for Wegener's granulomatosis (WG). Consequently, antigen-specific assays for detection of PR3-ANCA are helpful for the diagnosis and follow-up of patients with WG. Purification of PR3 is laborious and requires large amounts of granulocytes. Therefore, several attempts have been made to produce recombinant PR3 that is recognized by PR3-ANCA. The purpose of this study was to compare the recognition of different recombinant forms of PR3 (rPR3) by anti-PR3 antibodies. Recombinant PR3 produced in E. coli (rcPR3), P. pastoris (rpPR3), insect cells using the baculovirus system (rbPR3), the human mast cell line, HMC-1 (HMC-1/PR3-S176A), or the human epithelial cell line, 293 (Delta-rPR3-S176A) as well as purified neutrophil PR3 (nPR3) were used. Recognition of these rPR3s by anti-PR3 antibodies was determined by direct and capture ELISA with 19 PR3-ANCA sera, 13 anti-PR3 mAbs and a rabbit serum raised against human PR3. In the capture ELISA rabbit anti-PR3 strongly bound nPR3 and all rPR3 products. By capture ELISA rcPR3 and rpPR3 were recognized by 11 (57%) and 13 (68%) of the 19 PR3-ANCA sera, respectively, whereas rbPR3, HMC-1/PR3-S176A, Delta-rPR3-S176A and nPR3 were recognized by all PR3-ANCA sera. By direct ELISA rabbit anti-PR3 strongly bound nPR3 and all tested rPR3 products. Using the direct ELISA none of the PR3-ANCA sera recognized rcPR3, whereas rpPR3 and rbPR3 were recognized by two (11%) and 17 (89%) of the 19 PR3-ANCA sera, respectively. All 13 anti-PR3 mAbs recognized nPR3 in the direct as well as in the capture ELISA. The rcPR3 was recognized by two mAbs in the capture ELISA but by none of the mAbs in the direct ELISA. The rpPR3 was recognized by seven mAbs in the capture ELISA and only by two mAbs in the direct ELISA. All but one of the anti-PR3 mAbs recognized rbPR3, whereas HMC-1/PR3-S176A and Delta-rPR3-S176A were recognized by

  18. A System Dynamics Analysis of the Factors Affecting Combat Readiness

    DTIC Science & Technology

    1980-06-01

    experimental model approach to improving systems is the third foundation of system dynamics. The last foundation is the use of the digital computer to conduct...completion rate is a third order delay of the rated supplement requalification rate (RSRR). This delay represents the time period which is required...the relationships which exist in the combat readiness system, the third objective could be accomplished. The construction of a dynamic systems and

  19. 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.

  20. 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…