A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

NASA Astrophysics Data System (ADS)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Action adaptation during natural unfolding social scenes influences action recognition and inferences made about actor beliefs.

PubMed

Keefe, Bruce D; Wincenciak, Joanna; Jellema, Tjeerd; Ward, James W; Barraclough, Nick E

2016-07-01

When observing another individual's actions, we can both recognize their actions and infer their beliefs concerning the physical and social environment. The extent to which visual adaptation influences action recognition and conceptually later stages of processing involved in deriving the belief state of the actor remains unknown. To explore this we used virtual reality (life-size photorealistic actors presented in stereoscopic three dimensions) to see how visual adaptation influences the perception of individuals in naturally unfolding social scenes at increasingly higher levels of action understanding. We presented scenes in which one actor picked up boxes (of varying number and weight), after which a second actor picked up a single box. Adaptation to the first actor's behavior systematically changed perception of the second actor. Aftereffects increased with the duration of the first actor's behavior, declined exponentially over time, and were independent of view direction. Inferences about the second actor's expectation of box weight were also distorted by adaptation to the first actor. Distortions in action recognition and actor expectations did not, however, extend across different actions, indicating that adaptation is not acting at an action-independent abstract level but rather at an action-dependent level. We conclude that although adaptation influences more complex inferences about belief states of individuals, this is likely to be a result of adaptation at an earlier action recognition stage rather than adaptation operating at a higher, more abstract level in mentalizing or simulation systems.

Individual differences in adaptive coding of face identity are linked to individual differences in face recognition ability.

PubMed

Rhodes, Gillian; Jeffery, Linda; Taylor, Libby; Hayward, William G; Ewing, Louise

2014-06-01

Despite their similarity as visual patterns, we can discriminate and recognize many thousands of faces. This expertise has been linked to 2 coding mechanisms: holistic integration of information across the face and adaptive coding of face identity using norms tuned by experience. Recently, individual differences in face recognition ability have been discovered and linked to differences in holistic coding. Here we show that they are also linked to individual differences in adaptive coding of face identity, measured using face identity aftereffects. Identity aftereffects correlated significantly with several measures of face-selective recognition ability. They also correlated marginally with own-race face recognition ability, suggesting a role for adaptive coding in the well-known other-race effect. More generally, these results highlight the important functional role of adaptive face-coding mechanisms in face expertise, taking us beyond the traditional focus on holistic coding mechanisms. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Recognition of voice commands using adaptation of foreign language speech recognizer via selection of phonetic transcriptions

NASA Astrophysics Data System (ADS)

Maskeliunas, Rytis; Rudzionis, Vytautas

2011-06-01

In recent years various commercial speech recognizers have become available. These recognizers provide the possibility to develop applications incorporating various speech recognition techniques easily and quickly. All of these commercial recognizers are typically targeted to widely spoken languages having large market potential; however, it may be possible to adapt available commercial recognizers for use in environments where less widely spoken languages are used. Since most commercial recognition engines are closed systems the single avenue for the adaptation is to try set ways for the selection of proper phonetic transcription methods between the two languages. This paper deals with the methods to find the phonetic transcriptions for Lithuanian voice commands to be recognized using English speech engines. The experimental evaluation showed that it is possible to find phonetic transcriptions that will enable the recognition of Lithuanian voice commands with recognition accuracy of over 90%.

Audiovisual cues benefit recognition of accented speech in noise but not perceptual adaptation

PubMed Central

Banks, Briony; Gowen, Emma; Munro, Kevin J.; Adank, Patti

2015-01-01

Perceptual adaptation allows humans to recognize different varieties of accented speech. We investigated whether perceptual adaptation to accented speech is facilitated if listeners can see a speaker’s facial and mouth movements. In Study 1, participants listened to sentences in a novel accent and underwent a period of training with audiovisual or audio-only speech cues, presented in quiet or in background noise. A control group also underwent training with visual-only (speech-reading) cues. We observed no significant difference in perceptual adaptation between any of the groups. To address a number of remaining questions, we carried out a second study using a different accent, speaker and experimental design, in which participants listened to sentences in a non-native (Japanese) accent with audiovisual or audio-only cues, without separate training. Participants’ eye gaze was recorded to verify that they looked at the speaker’s face during audiovisual trials. Recognition accuracy was significantly better for audiovisual than for audio-only stimuli; however, no statistical difference in perceptual adaptation was observed between the two modalities. Furthermore, Bayesian analysis suggested that the data supported the null hypothesis. Our results suggest that although the availability of visual speech cues may be immediately beneficial for recognition of unfamiliar accented speech in noise, it does not improve perceptual adaptation. PMID:26283946

Audiovisual cues benefit recognition of accented speech in noise but not perceptual adaptation.

PubMed

Banks, Briony; Gowen, Emma; Munro, Kevin J; Adank, Patti

2015-01-01

Perceptual adaptation allows humans to recognize different varieties of accented speech. We investigated whether perceptual adaptation to accented speech is facilitated if listeners can see a speaker's facial and mouth movements. In Study 1, participants listened to sentences in a novel accent and underwent a period of training with audiovisual or audio-only speech cues, presented in quiet or in background noise. A control group also underwent training with visual-only (speech-reading) cues. We observed no significant difference in perceptual adaptation between any of the groups. To address a number of remaining questions, we carried out a second study using a different accent, speaker and experimental design, in which participants listened to sentences in a non-native (Japanese) accent with audiovisual or audio-only cues, without separate training. Participants' eye gaze was recorded to verify that they looked at the speaker's face during audiovisual trials. Recognition accuracy was significantly better for audiovisual than for audio-only stimuli; however, no statistical difference in perceptual adaptation was observed between the two modalities. Furthermore, Bayesian analysis suggested that the data supported the null hypothesis. Our results suggest that although the availability of visual speech cues may be immediately beneficial for recognition of unfamiliar accented speech in noise, it does not improve perceptual adaptation.

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

The development of adaptive decision making: Recognition-based inference in children and adolescents.

PubMed

Horn, Sebastian S; Ruggeri, Azzurra; Pachur, Thorsten

2016-09-01

Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment, particularly the predictive power (validity) of recognition. Little is known about developmental differences in use of the RH. In this study, the authors examined (a) to what extent children and adolescents recruit the RH when making judgments, and (b) around what age adaptive use of the RH emerges. Primary schoolchildren (M = 9 years), younger adolescents (M = 12 years), and older adolescents (M = 17 years) made comparative judgments in task environments with either high or low recognition validity. Reliance on the RH was measured with a hierarchical multinomial model. Results indicated that primary schoolchildren already made systematic use of the RH. However, only older adolescents adaptively adjusted their strategy use between environments and were better able to discriminate between situations in which the RH led to correct versus incorrect inferences. These findings suggest that the use of simple heuristics does not progress unidirectionally across development but strongly depends on the task environment, in line with the perspective of ecological rationality. Moreover, adaptive heuristic inference seems to require experience and a developed base of domain knowledge. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

ARCH: Adaptive recurrent-convolutional hybrid networks for long-term action recognition

PubMed Central

Xin, Miao; Zhang, Hong; Wang, Helong; Sun, Mingui; Yuan, Ding

2017-01-01

Recognition of human actions from digital video is a challenging task due to complex interfering factors in uncontrolled realistic environments. In this paper, we propose a learning framework using static, dynamic and sequential mixed features to solve three fundamental problems: spatial domain variation, temporal domain polytrope, and intra- and inter-class diversities. Utilizing a cognitive-based data reduction method and a hybrid “network upon networks” architecture, we extract human action representations which are robust against spatial and temporal interferences and adaptive to variations in both action speed and duration. We evaluated our method on the UCF101 and other three challenging datasets. Our results demonstrated a superior performance of the proposed algorithm in human action recognition. PMID:29290647

Helix formation in arrestin accompanies recognition of photoactivated rhodopsin.

PubMed

Feuerstein, Sophie E; Pulvermüller, Alexander; Hartmann, Rudolf; Granzin, Joachim; Stoldt, Matthias; Henklein, Peter; Ernst, Oliver P; Heck, Martin; Willbold, Dieter; Koenig, Bernd W

2009-11-17

Binding of arrestin to photoactivated phosphorylated rhodopsin terminates the amplification of visual signals in photoreceptor cells. Currently, there is no crystal structure of a rhodopsin-arrestin complex available, although structures of unbound rhodopsin and arrestin have been determined. High-affinity receptor binding is dependent on distinct arrestin sites responsible for recognition of rhodopsin activation and phosphorylation. The loop connecting beta-strands V and VI in rod arrestin has been implicated in the recognition of active rhodopsin. We report the structure of receptor-bound arrestin peptide Arr(67-77) mimicking this loop based on solution NMR data. The peptide binds photoactivated rhodopsin in the unphosphorylated and phosphorylated form with similar affinities and stabilizes the metarhodopsin II photointermediate. A largely alpha-helical conformation of the receptor-bound peptide is observed.

Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds

NASA Astrophysics Data System (ADS)

Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert

2014-06-01

Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new

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.

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

NASA Technical Reports Server (NTRS)

Salazar, George A. (Inventor); Haynes, Dena S. (Inventor); Sommers, Marc J. (Inventor)

1998-01-01

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Face recognition using total margin-based adaptive fuzzy support vector machines.

PubMed

Liu, Yi-Hung; Chen, Yen-Ting

2007-01-01

This paper presents a new classifier called total margin-based adaptive fuzzy support vector machines (TAF-SVM) that deals with several problems that may occur in support vector machines (SVMs) when applied to the face recognition. The proposed TAF-SVM not only solves the overfitting problem resulted from the outlier with the approach of fuzzification of the penalty, but also corrects the skew of the optimal separating hyperplane due to the very imbalanced data sets by using different cost algorithm. In addition, by introducing the total margin algorithm to replace the conventional soft margin algorithm, a lower generalization error bound can be obtained. Those three functions are embodied into the traditional SVM so that the TAF-SVM is proposed and reformulated in both linear and nonlinear cases. By using two databases, the Chung Yuan Christian University (CYCU) multiview and the facial recognition technology (FERET) face databases, and using the kernel Fisher's discriminant analysis (KFDA) algorithm to extract discriminating face features, experimental results show that the proposed TAF-SVM is superior to SVM in terms of the face-recognition accuracy. The results also indicate that the proposed TAF-SVM can achieve smaller error variances than SVM over a number of tests such that better recognition stability can be obtained.

Visual adaptation dominates bimodal visual-motor action adaptation

PubMed Central

de la Rosa, Stephan; Ferstl, Ylva; Bülthoff, Heinrich H.

2016-01-01

A long standing debate revolves around the question whether visual action recognition primarily relies on visual or motor action information. Previous studies mainly examined the contribution of either visual or motor information to action recognition. Yet, the interaction of visual and motor action information is particularly important for understanding action recognition in social interactions, where humans often observe and execute actions at the same time. Here, we behaviourally examined the interaction of visual and motor action recognition processes when participants simultaneously observe and execute actions. We took advantage of behavioural action adaptation effects to investigate behavioural correlates of neural action recognition mechanisms. In line with previous results, we find that prolonged visual exposure (visual adaptation) and prolonged execution of the same action with closed eyes (non-visual motor adaptation) influence action recognition. However, when participants simultaneously adapted visually and motorically – akin to simultaneous execution and observation of actions in social interactions - adaptation effects were only modulated by visual but not motor adaptation. Action recognition, therefore, relies primarily on vision-based action recognition mechanisms in situations that require simultaneous action observation and execution, such as social interactions. The results suggest caution when associating social behaviour in social interactions with motor based information. PMID:27029781

Separation of Singing Voice from Music Accompaniment for Monaural Recordings

DTIC Science & Technology

2005-09-01

Directory: pub/tech-report/2005 File in pdf format: TR61.pdf Separation of Singing Voice from Music Accompaniment for Monaural Recordings Yipeng Li...Abstract Separating singing voice from music accompaniment is very useful in many applications, such as lyrics recognition and alignment, singer...identification, and music information retrieval. Although speech separation has been extensively studied for decades, singing voice separation has been little

Autistic traits are linked to reduced adaptive coding of face identity and selectively poorer face recognition in men but not women.

PubMed

Rhodes, Gillian; Jeffery, Linda; Taylor, Libby; Ewing, Louise

2013-11-01

Our ability to discriminate and recognize thousands of faces despite their similarity as visual patterns relies on adaptive, norm-based, coding mechanisms that are continuously updated by experience. Reduced adaptive coding of face identity has been proposed as a neurocognitive endophenotype for autism, because it is found in autism and in relatives of individuals with autism. Autistic traits can also extend continuously into the general population, raising the possibility that reduced adaptive coding of face identity may be more generally associated with autistic traits. In the present study, we investigated whether adaptive coding of face identity decreases as autistic traits increase in an undergraduate population. Adaptive coding was measured using face identity aftereffects, and autistic traits were measured using the Autism-Spectrum Quotient (AQ) and its subscales. We also measured face and car recognition ability to determine whether autistic traits are selectively related to face recognition difficulties. We found that men who scored higher on levels of autistic traits related to social interaction had reduced adaptive coding of face identity. This result is consistent with the idea that atypical adaptive face-coding mechanisms are an endophenotype for autism. Autistic traits were also linked with face-selective recognition difficulties in men. However, there were some unexpected sex differences. In women, autistic traits were linked positively, rather than negatively, with adaptive coding of identity, and were unrelated to face-selective recognition difficulties. These sex differences indicate that autistic traits can have different neurocognitive correlates in men and women and raise the intriguing possibility that endophenotypes of autism can differ in males and females. © 2013 Elsevier Ltd. All rights reserved.

The recognition signal hypothesis for the adaptive evolution of religion : a phylogenetic test with Christian denominations.

PubMed

Matthews, Luke J

2012-06-01

Recent research on the evolution of religion has focused on whether religion is an unselected by-product of evolutionary processes or if it is instead an adaptation by natural selection. Adaptive hypotheses for religion include direct fitness benefits from improved health and indirect fitness benefits mediated by costly signals and/or cultural group selection. Herein, I propose that religious denominations achieve indirect fitness gains for members through the use of ecologically arbitrary beliefs, rituals, and moral rules that function as recognition markers of cultural inheritance analogous to kin and species recognition of genetic inheritance in biology. This recognition signal hypotheses could act in concert with either costly signaling or cultural group selection to produce evolutionarily altruistic behaviors within denominations. Using a cultural phylogenetic analysis, I show that a large set of religious behaviors among extant Christian denominations supports the prediction of the recognition signal hypothesis that characters change more frequently near historical schisms. By incorporating demographic data into the model, I show that more-distinctive denominations, as measured through dissimilar characteristics, appear to be protected from intrusion by nonmembers in mixed-denomination households, and that they may be experiencing greater biological growth of their populations even in the present day.

Comparison of speech recognition with adaptive digital and FM remote microphone hearing assistance technology by listeners who use hearing aids.

PubMed

Thibodeau, Linda

2014-06-01

The purpose of this study was to compare the benefits of 3 types of remote microphone hearing assistance technology (HAT), adaptive digital broadband, adaptive frequency modulation (FM), and fixed FM, through objective and subjective measures of speech recognition in clinical and real-world settings. Participants included 11 adults, ages 16 to 78 years, with primarily moderate-to-severe bilateral hearing impairment (HI), who wore binaural behind-the-ear hearing aids; and 15 adults, ages 18 to 30 years, with normal hearing. Sentence recognition in quiet and in noise and subjective ratings were obtained in 3 conditions of wireless signal processing. Performance by the listeners with HI when using the adaptive digital technology was significantly better than that obtained with the FM technology, with the greatest benefits at the highest noise levels. The majority of listeners also preferred the digital technology when listening in a real-world noisy environment. The wireless technology allowed persons with HI to surpass persons with normal hearing in speech recognition in noise, with the greatest benefit occurring with adaptive digital technology. The use of adaptive digital technology combined with speechreading cues would allow persons with HI to engage in communication in environments that would have otherwise not been possible with traditional wireless technology.

Familiarity or Conceptual Priming: Event-Related Potentials in Name Recognition

ERIC Educational Resources Information Center

Stenberg, Georg; Hellman, Johan; Johansson, Mikael; Rosen, Ingmar

2009-01-01

Recent interest has been drawn to the separate components of recognition memory, as studied by event-related potentials (ERPs). In ERPs, recollection is usually accompanied by a late, parietal positive deflection. An earlier, frontal component has been suggested to be a counterpart, accompanying recognition by familiarity. However, this component,…

Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

NASA Astrophysics Data System (ADS)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.

Adaptive non-local smoothing-based weberface for illumination-insensitive face recognition

NASA Astrophysics Data System (ADS)

Yao, Min; Zhu, Changming

2017-07-01

Compensating the illumination of a face image is an important process to achieve effective face recognition under severe illumination conditions. This paper present a novel illumination normalization method which specifically considers removing the illumination boundaries as well as reducing the regional illumination. We begin with the analysis of the commonly used reflectance model and then expatiate the hybrid usage of adaptive non-local smoothing and the local information coding based on Weber's law. The effectiveness and advantages of this combination are evidenced visually and experimentally. Results on Extended YaleB database show its better performance than several other famous methods.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

2017-09-01

It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Speech Recognition as a Support Service for Deaf and Hard of Hearing Students: Adaptation and Evaluation. Final Report to Spencer Foundation.

ERIC Educational Resources Information Center

Stinson, Michael; Elliot, Lisa; McKee, Barbara; Coyne, Gina

This report discusses a project that adapted new automatic speech recognition (ASR) technology to provide real-time speech-to-text transcription as a support service for students who are deaf and hard of hearing (D/HH). In this system, as the teacher speaks, a hearing intermediary, or captionist, dictates into the speech recognition system in a…

Examining recognition criterion rigidity during testing using a biased feedback technique: Evidence for adaptive criterion learning

PubMed Central

Han, Sanghoon; Dobbins, Ian G.

2009-01-01

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., “old” or “new”). Although explicit pre-test instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel, biased feedback technique designed to tacitly encourage certain errors by indicating they were correct choices. Experiment 1 demonstrated that fully correct feedback had little effect on criterion placement, whereas biased feedback during Experiments 2 and 3 yielded prominent, durable, and adaptive criterion shifts, with observers reporting they were unaware of the manipulation in Experiment 3. These data suggest recognition criteria can be easily modified during testing through a form of feedback learning that operates independent of stimulus characteristics and observer awareness of the nature of the manipulation. This mechanism may be fundamentally different than criterion shifts following explicit instructions and warnings, or shifts linked to manipulations of stimulus characteristics combined with feedback highlighting those manipulations. PMID:18604954

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.

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

NASA Astrophysics Data System (ADS)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Quantum changes in Helicobacter pylori gene expression accompany host-adaptation

PubMed Central

Wise, Michael J.; Khosravi, Yalda; Seow, Shih-Wee; Amoyo, Arlaine A.; Pettersson, Sven; Peters, Fanny; Tay, Chin-Yen; Perkins, Timothy T.; Loke, Mun-Fai; Marshall, Barry J.; Vadivelu, Jamuna

2017-01-01

Abstract Helicobacter pylori is a highly successful gastric pathogen. High genomic plasticity allows its adaptation to changing host environments. Complete genomes of H. pylori clinical isolate UM032 and its mice-adapted serial derivatives 298 and 299, generated using both PacBio RS and Illumina MiSeq sequencing technologies, were compared to identify novel elements responsible for host-adaptation. The acquisition of a jhp0562-like allele, which encodes for a galactosyltransferase, was identified in the mice-adapted strains. Our analysis implies a new β-1,4-galactosyltransferase role for this enzyme, essential for Ley antigen expression. Intragenomic recombination between babA and babB genes was also observed. Further, we expanded on the list of candidate genes whose expression patterns have been mediated by upstream homopolymer-length alterations to facilitate host adaption. Importantly, greater than four-fold reduction of mRNA levels was demonstrated in five genes. Among the down-regulated genes, three encode for outer membrane proteins, including BabA, BabB and HopD. As expected, a substantial reduction in BabA protein abundance was detected in mice-adapted strains 298 and 299 via Western analysis. Our results suggest that the expression of Ley antigen and reduced outer membrane protein expressions may facilitate H. pylori colonisation of mouse gastric epithelium. PMID:27803027

When the face fits: recognition of celebrities from matching and mismatching faces and voices.

PubMed

Stevenage, Sarah V; Neil, Greg J; Hamlin, Iain

2014-01-01

The results of two experiments are presented in which participants engaged in a face-recognition or a voice-recognition task. The stimuli were face-voice pairs in which the face and voice were co-presented and were either "matched" (same person), "related" (two highly associated people), or "mismatched" (two unrelated people). Analysis in both experiments confirmed that accuracy and confidence in face recognition was consistently high regardless of the identity of the accompanying voice. However accuracy of voice recognition was increasingly affected as the relationship between voice and accompanying face declined. Moreover, when considering self-reported confidence in voice recognition, confidence remained high for correct responses despite the proportion of these responses declining across conditions. These results converged with existing evidence indicating the vulnerability of voice recognition as a relatively weak signaller of identity, and results are discussed in the context of a person-recognition framework.

Action Recognition in a Crowded Environment

PubMed Central

Nieuwenhuis, Judith; Bülthoff, Isabelle; Barraclough, Nick; de la Rosa, Stephan

2017-01-01

So far, action recognition has been mainly examined with small point-light human stimuli presented alone within a narrow central area of the observer’s visual field. Yet, we need to recognize the actions of life-size humans viewed alone or surrounded by bystanders, whether they are seen in central or peripheral vision. Here, we examined the mechanisms in central vision and far periphery (40° eccentricity) involved in the recognition of the actions of a life-size actor (target) and their sensitivity to the presence of a crowd surrounding the target. In Experiment 1, we used an action adaptation paradigm to probe whether static or idly moving crowds might interfere with the recognition of a target’s action (hug or clap). We found that this type of crowds whose movements were dissimilar to the target action hardly affected action recognition in central and peripheral vision. In Experiment 2, we examined whether crowd actions that were more similar to the target actions affected action recognition. Indeed, the presence of that crowd diminished adaptation aftereffects in central vision as wells as in the periphery. We replicated Experiment 2 using a recognition task instead of an adaptation paradigm. With this task, we found evidence of decreased action recognition accuracy, but this was significant in peripheral vision only. Our results suggest that the presence of a crowd carrying out actions similar to that of the target affects its recognition. We outline how these results can be understood in terms of high-level crowding effects that operate on action-sensitive perceptual channels. PMID:29308177

Object Recognition using Feature- and Color-Based Methods

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Stubberud, Allen

2008-01-01

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Adapted all-numerical correlator for face recognition applications

NASA Astrophysics Data System (ADS)

Elbouz, M.; Bouzidi, F.; Alfalou, A.; Brosseau, C.; Leonard, I.; Benkelfat, B.-E.

2013-03-01

In this study, we suggest and validate an all-numerical implementation of a VanderLugt correlator which is optimized for face recognition applications. The main goal of this implementation is to take advantage of the benefits (detection, localization, and identification of a target object within a scene) of correlation methods and exploit the reconfigurability of numerical approaches. This technique requires a numerical implementation of the optical Fourier transform. We pay special attention to adapt the correlation filter to this numerical implementation. One main goal of this work is to reduce the size of the filter in order to decrease the memory space required for real time applications. To fulfil this requirement, we code the reference images with 8 bits and study the effect of this coding on the performances of several composite filters (phase-only filter, binary phase-only filter). The saturation effect has for effect to decrease the performances of the correlator for making a decision when filters contain up to nine references. Further, an optimization is proposed based for an optimized segmented composite filter. Based on this approach, we present tests with different faces demonstrating that the above mentioned saturation effect is significantly reduced while minimizing the size of the learning data base.

Flexible Piezoelectric Sensor-Based Gait Recognition.

PubMed

Cha, Youngsu; Kim, Hojoon; Kim, Doik

2018-02-05

Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Shape and Color Features for Object Recognition Search

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

2012-01-01

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

The NTID speech recognition test: NSRT(®).

PubMed

Bochner, Joseph H; Garrison, Wayne M; Doherty, Karen A

2015-07-01

The purpose of this study was to collect and analyse data necessary for expansion of the NSRT item pool and to evaluate the NSRT adaptive testing software. Participants were administered pure-tone and speech recognition tests including W-22 and QuickSIN, as well as a set of 323 new NSRT items and NSRT adaptive tests in quiet and background noise. Performance on the adaptive tests was compared to pure-tone thresholds and performance on other speech recognition measures. The 323 new items were subjected to Rasch scaling analysis. Seventy adults with mild to moderately severe hearing loss participated in this study. Their mean age was 62.4 years (sd = 20.8). The 323 new NSRT items fit very well with the original item bank, enabling the item pool to be more than doubled in size. Data indicate high reliability coefficients for the NSRT and moderate correlations with pure-tone thresholds (PTA and HFPTA) and other speech recognition measures (W-22, QuickSIN, and SRT). The adaptive NSRT is an efficient and effective measure of speech recognition, providing valid and reliable information concerning respondents' speech perception abilities.

Evaluation of Speech Recognition of Cochlear Implant Recipients Using Adaptive, Digital Remote Microphone Technology and a Speech Enhancement Sound Processing Algorithm.

PubMed

Wolfe, Jace; Morais, Mila; Schafer, Erin; Agrawal, Smita; Koch, Dawn

2015-05-01

Cochlear implant recipients often experience difficulty with understanding speech in the presence of noise. Cochlear implant manufacturers have developed sound processing algorithms designed to improve speech recognition in noise, and research has shown these technologies to be effective. Remote microphone technology utilizing adaptive, digital wireless radio transmission has also been shown to provide significant improvement in speech recognition in noise. There are no studies examining the potential improvement in speech recognition in noise when these two technologies are used simultaneously. The goal of this study was to evaluate the potential benefits and limitations associated with the simultaneous use of a sound processing algorithm designed to improve performance in noise (Advanced Bionics ClearVoice) and a remote microphone system that incorporates adaptive, digital wireless radio transmission (Phonak Roger). A two-by-two way repeated measures design was used to examine performance differences obtained without these technologies compared to the use of each technology separately as well as the simultaneous use of both technologies. Eleven Advanced Bionics (AB) cochlear implant recipients, ages 11 to 68 yr. AzBio sentence recognition was measured in quiet and in the presence of classroom noise ranging in level from 50 to 80 dBA in 5-dB steps. Performance was evaluated in four conditions: (1) No ClearVoice and no Roger, (2) ClearVoice enabled without the use of Roger, (3) ClearVoice disabled with Roger enabled, and (4) simultaneous use of ClearVoice and Roger. Speech recognition in quiet was better than speech recognition in noise for all conditions. Use of ClearVoice and Roger each provided significant improvement in speech recognition in noise. The best performance in noise was obtained with the simultaneous use of ClearVoice and Roger. ClearVoice and Roger technology each improves speech recognition in noise, particularly when used at the same time

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes

PubMed Central

Zhang, Yaoyun; Li, Hee-Jin; Wang, Jingqi; Cohen, Trevor; Roberts, Kirk; Xu, Hua

2018-01-01

Mental health is increasingly recognized an important topic in healthcare. Information concerning psychiatric symptoms is critical for the timely diagnosis of mental disorders, as well as for the personalization of interventions. However, the diversity and sparsity of psychiatric symptoms make it challenging for conventional natural language processing techniques to automatically extract such information from clinical text. To address this problem, this study takes the initiative to use and adapt word embeddings from four source domains – intensive care, biomedical literature, Wikipedia and Psychiatric Forum – to recognize symptoms in the target domain of psychiatry. We investigated four different approaches including 1) only using word embeddings of the source domain, 2) directly combining data of the source and target to generate word embeddings, 3) assigning different weights to word embeddings, and 4) retraining the word embedding model of the source domain using a corpus of the target domain. To the best of our knowledge, this is the first work of adapting multiple word embeddings of external domains to improve psychiatric symptom recognition in clinical text. Experimental results showed that the last two approaches outperformed the baseline methods, indicating the effectiveness of our new strategies to leverage embeddings from other domains. PMID:29888086

Recognizing What Matters: Value Improves Recognition by Selectively Enhancing Recollection

PubMed Central

Hennessee, Joseph P.; Castel, Alan D.; Knowlton, Barbara J.

2017-01-01

We examined the effects of value on recognition by assessing its contribution to recollection and familiarity. In three experiments, participants studied English words, each associated with a point-value they would earn for correct recognition, with the goal of maximizing their score. In Experiment 1, participants provided Remember/Know judgments. In Experiment 2 participants indicated whether items were recollected or if not, their degree of familiarity along a 6-point scale. In Experiment 3, recognition of words was accompanied by a test of memory for incidental details. Across all experiments, participants were more likely to recognize items with higher point-value. Furthermore, value appeared to primarily enhance recollection, as effects on familiarity were small and not consistent across experiments. Recollection of high-value items appears to be accompanied by fewer incidental details, suggesting that value increases focus on items at the expense of irrelevant information. PMID:28827894

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.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values

Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

PubMed

Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

2016-09-01

Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.

PubMed

Yang, Cheng-Huei; Luo, Ching-Hsing; Yang, Cheng-Hong; Chuang, Li-Yeh

2004-01-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.

Influence of music with different volumes and styles on recognition activity in humans.

PubMed

Pavlygina, R A; Sakharov, D S; Davydov, V I; Avdonkin, A V

2010-10-01

The efficiency of the recognition of masked visual images (Arabic numerals) increased when accompanied by classical (62 dB) and rock music (25 dB). These changes were accompanied by increases in the coherence of potentials in the frontal areas seen on recognition without music. Changes in intercenter EEG relationships correlated with the formation a dominant at the behavioral level. When loud music (85 dB) and music of other styles was used, these changes in behavior and the EEG were not seen; however, the coherence of potentials in the temporal and motor cortex of the right hemisphere increased and the latent periods of motor reactions of the hands decreased. These results provide evidence that the "recognition" dominant is formed when there are particular ratios of the levels of excitation in the corresponding centers, which should be considered when there is a need to increase the efficiency of recognition activity in humans.

A Self-Adaptive Dynamic Recognition Model for Fatigue Driving Based on Multi-Source Information and Two Levels of Fusion

PubMed Central

Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai

2015-01-01

To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615

A New Adaptive Structural Signature for Symbol Recognition by Using a Galois Lattice as a Classifier.

PubMed

Coustaty, M; Bertet, K; Visani, M; Ogier, J

2011-08-01

In this paper, we propose a new approach for symbol recognition using structural signatures and a Galois lattice as a classifier. The structural signatures are based on topological graphs computed from segments which are extracted from the symbol images by using an adapted Hough transform. These structural signatures-that can be seen as dynamic paths which carry high-level information-are robust toward various transformations. They are classified by using a Galois lattice as a classifier. The performance of the proposed approach is evaluated based on the GREC'03 symbol database, and the experimental results we obtain are encouraging.

Handwritten word preprocessing for database adaptation

NASA Astrophysics Data System (ADS)

Oprean, Cristina; Likforman-Sulem, Laurence; Mokbel, Chafic

2013-01-01

Handwriting recognition systems are typically trained using publicly available databases, where data have been collected in controlled conditions (image resolution, paper background, noise level,...). Since this is not often the case in real-world scenarios, classification performance can be affected when novel data is presented to the word recognition system. To overcome this problem, we present in this paper a new approach called database adaptation. It consists of processing one set (training or test) in order to adapt it to the other set (test or training, respectively). Specifically, two kinds of preprocessing, namely stroke thickness normalization and pixel intensity normalization are considered. The advantage of such approach is that we can re-use the existing recognition system trained on controlled data. We conduct several experiments with the Rimes 2011 word database and with a real-world database. We adapt either the test set or the training set. Results show that training set adaptation achieves better results than test set adaptation, at the cost of a second training stage on the adapted data. Accuracy of data set adaptation is increased by 2% to 3% in absolute value over no adaptation.

Different Neural Processes Accompany Self-Recognition in Photographs Across the Lifespan: An ERP Study Using Dizygotic Twins

PubMed Central

Butler, David L.; Mattingley, Jason B.; Cunnington, Ross; Suddendorf, Thomas

2013-01-01

Our appearance changes over time, yet we can recognize ourselves in photographs from across the lifespan. Researchers have extensively studied self-recognition in photographs and have proposed that specific neural correlates are involved, but few studies have examined self-recognition using images from different periods of life. Here we compared ERP responses to photographs of participants when they were 5–15, 16–25, and 26–45 years old. We found marked differences between the responses to photographs from these time periods in terms of the neural markers generally assumed to reflect (i) the configural processing of faces (i.e., the N170), (ii) the matching of the currently perceived face to a representation already stored in memory (i.e., the P250), and (iii) the retrieval of information about the person being recognized (i.e., the N400). There was no uniform neural signature of visual self-recognition. To test whether there was anything specific to self-recognition in these brain responses, we also asked participants to identify photographs of their dizygotic twins taken from the same time periods. Critically, this allowed us to minimize the confounding effects of exposure, for it is likely that participants have been similarly exposed to each other's faces over the lifespan. The same pattern of neural response emerged with only one exception: the neural marker reflecting the retrieval of mnemonic information (N400) differed across the lifespan for self but not for twin. These results, as well as our novel approach using twins and photographs from across the lifespan, have wide-ranging consequences for the study of self-recognition and the nature of our personal identity through time. PMID:24069151

Different neural processes accompany self-recognition in photographs across the lifespan: an ERP study using dizygotic twins.

PubMed

Butler, David L; Mattingley, Jason B; Cunnington, Ross; Suddendorf, Thomas

2013-01-01

Our appearance changes over time, yet we can recognize ourselves in photographs from across the lifespan. Researchers have extensively studied self-recognition in photographs and have proposed that specific neural correlates are involved, but few studies have examined self-recognition using images from different periods of life. Here we compared ERP responses to photographs of participants when they were 5-15, 16-25, and 26-45 years old. We found marked differences between the responses to photographs from these time periods in terms of the neural markers generally assumed to reflect (i) the configural processing of faces (i.e., the N170), (ii) the matching of the currently perceived face to a representation already stored in memory (i.e., the P250), and (iii) the retrieval of information about the person being recognized (i.e., the N400). There was no uniform neural signature of visual self-recognition. To test whether there was anything specific to self-recognition in these brain responses, we also asked participants to identify photographs of their dizygotic twins taken from the same time periods. Critically, this allowed us to minimize the confounding effects of exposure, for it is likely that participants have been similarly exposed to each other's faces over the lifespan. The same pattern of neural response emerged with only one exception: the neural marker reflecting the retrieval of mnemonic information (N400) differed across the lifespan for self but not for twin. These results, as well as our novel approach using twins and photographs from across the lifespan, have wide-ranging consequences for the study of self-recognition and the nature of our personal identity through time.

Within-person adaptivity in frugal judgments from memory.

PubMed

Filevich, Elisa; Horn, Sebastian S; Kühn, Simone

2017-12-22

Humans can exploit recognition memory as a simple cue for judgment. The utility of recognition depends on the interplay with the environment, particularly on its predictive power (validity) in a domain. It is, therefore, an important question whether people are sensitive to differences in recognition validity between domains. Strategic, intra-individual changes in the reliance on recognition have not been investigated so far. The present study fills this gap by scrutinizing within-person changes in using a frugal strategy, the recognition heuristic (RH), across two task domains that differed in recognition validity. The results showed adaptive changes in the reliance on recognition between domains. However, these changes were neither associated with the individual recognition validities nor with corresponding changes in these validities. These findings support a domain-adaptivity explanation, suggesting that people have broader intuitions about the usefulness of recognition across different domains that are nonetheless sufficiently robust for adaptive decision making. The analysis of metacognitive confidence reports mirrored and extended these results. Like RH use, confidence ratings covaried with task domain, but not with individual recognition validities. The changes in confidence suggest that people may have metacognitive access to information about global differences between task domains, but not to individual cue validities.

Control of antiviral immunity by pattern recognition and the microbiome

PubMed Central

Pang, Iris K.; Iwasaki, Akiko

2013-01-01

Summary Human skin and mucosal surfaces are in constant contact with resident and invasive microbes. Recognition of microbial products by receptors of the innate immune system triggers rapid innate defense and transduces signals necessary for initiating and maintaining the adaptive immune responses. Microbial sensing by innate pattern recognition receptors is not restricted to pathogens. Rather, proper development, function, and maintenance of innate and adaptive immunity rely on continuous recognition of products derived from the microorganisms indigenous to the internal and external surfaces of mammalian host. Tonic immune activation by the resident microbiota governs host susceptibility to intestinal and extra-intestinal infections including those caused by viruses. This review highlights recent developments in innate viral recognition leading to adaptive immunity, and discusses potential link between viruses, microbiota and the host immune system. Further, we discuss the possible roles of microbiome in chronic viral infection and pathogenesis of autoimmune disease, and speculate on the benefit for probiotic therapies against such diseases. PMID:22168422

RIG-I in RNA virus recognition

PubMed Central

Kell, Alison M.; Gale, Michael

2015-01-01

Antiviral immunity is initiated upon host recognition of viral products via non-self molecular patterns known as pathogen-associated molecular patterns (PAMPs). Such recognition initiates signaling cascades that induce intracellular innate immune defenses and an inflammatory response that facilitates development of the acquired immune response. The retinoic acid-inducible gene I (RIG-I) and the RIG-I-like receptor (RLR) protein family are key cytoplasmic pathogen recognition receptors that are implicated in the recognition of viruses across genera and virus families, including functioning as major sensors of RNA viruses, and promoting recognition of some DNA viruses. RIG-I, the charter member of the RLR family, is activated upon binding to PAMP RNA. Activated RIG-I signals by interacting with the adapter protein MAVS leading to a signaling cascade that activates the transcription factors IRF3 and NF-κB. These actions induce the expression of antiviral gene products and the production of type I and III interferons that lead to an antiviral state in the infected cell and surrounding tissue. RIG-I signaling is essential for the control of infection by many RNA viruses. Recently, RIG-I crosstalk with other pathogen recognition receptors and components of the inflammasome has been described. In this review, we discuss the current knowledge regarding the role of RIG-I in recognition of a variety of virus families and its role in programming the adaptive immune response through cross-talk with parallel arms of the innate immune system, including how RIG-I can be leveraged for antiviral therapy. PMID:25749629

Visual scanning behavior is related to recognition performance for own- and other-age faces

PubMed Central

Proietti, Valentina; Macchi Cassia, Viola; dell’Amore, Francesca; Conte, Stefania; Bricolo, Emanuela

2015-01-01

It is well-established that our recognition ability is enhanced for faces belonging to familiar categories, such as own-race faces and own-age faces. Recent evidence suggests that, for race, the recognition bias is also accompanied by different visual scanning strategies for own- compared to other-race faces. Here, we tested the hypothesis that these differences in visual scanning patterns extend also to the comparison between own and other-age faces and contribute to the own-age recognition advantage. Participants (young adults with limited experience with infants) were tested in an old/new recognition memory task where they encoded and subsequently recognized a series of adult and infant faces while their eye movements were recorded. Consistent with findings on the other-race bias, we found evidence of an own-age bias in recognition which was accompanied by differential scanning patterns, and consequently differential encoding strategies, for own-compared to other-age faces. Gaze patterns for own-age faces involved a more dynamic sampling of the internal features and longer viewing time on the eye region compared to the other regions of the face. This latter strategy was extensively employed during learning (vs. recognition) and was positively correlated to discriminability. These results suggest that deeply encoding the eye region is functional for recognition and that the own-age bias is evident not only in differential recognition performance, but also in the employment of different sampling strategies found to be effective for accurate recognition. PMID:26579056

Accurate forced-choice recognition without awareness of memory retrieval.

PubMed

Voss, Joel L; Baym, Carol L; Paller, Ken A

2008-06-01

Recognition confidence and the explicit awareness of memory retrieval commonly accompany accurate responding in recognition tests. Memory performance in recognition tests is widely assumed to measure explicit memory, but the generality of this assumption is questionable. Indeed, whether recognition in nonhumans is always supported by explicit memory is highly controversial. Here we identified circumstances wherein highly accurate recognition was unaccompanied by hallmark features of explicit memory. When memory for kaleidoscopes was tested using a two-alternative forced-choice recognition test with similar foils, recognition was enhanced by an attentional manipulation at encoding known to degrade explicit memory. Moreover, explicit recognition was most accurate when the awareness of retrieval was absent. These dissociations between accuracy and phenomenological features of explicit memory are consistent with the notion that correct responding resulted from experience-dependent enhancements of perceptual fluency with specific stimuli--the putative mechanism for perceptual priming effects in implicit memory tests. This mechanism may contribute to recognition performance in a variety of frequently-employed testing circumstances. Our results thus argue for a novel view of recognition, in that analyses of its neurocognitive foundations must take into account the potential for both (1) recognition mechanisms allied with implicit memory and (2) recognition mechanisms allied with explicit memory.

Considerations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval.

PubMed

Raiche, Gilles; Blais, Jean-Guy

2009-01-01

In a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.

Process dissociation between contextual retrieval and item recognition.

PubMed

Weis, Susanne; Specht, Karsten; Klaver, Peter; Tendolkar, Indira; Willmes, Klaus; Ruhlmann, Jürgen; Elger, Christian E; Fernández, Guillén

2004-12-22

We employed a source memory task in an event related fMRI study to dissociate MTL processes associated with either contextual retrieval or item recognition. To introduce context during study, stimuli (photographs of buildings and natural landscapes) were transformed into one of four single-color-scales: red, blue, yellow, or green. In the subsequent old/new recognition memory test, all stimuli were presented as gray scale photographs, and old-responses were followed by a four-alternative source judgment referring to the color in which the stimulus was presented during study. Our results suggest a clear-cut process dissociation within the human MTL. While an activity increase accompanies successful retrieval of contextual information, an activity decrease provides a familiarity signal that is sufficient for successful item recognition.

Fractionating the Neural Substrates of Incidental Recognition Memory

ERIC Educational Resources Information Center

Greene, Ciara M.; Vidaki, Kleio; Soto, David

2015-01-01

Familiar stimuli are typically accompanied by decreases in neural response relative to the presentation of novel items, but these studies often include explicit instructions to discriminate old and new items; this creates difficulties in partialling out the contribution of top-down intentional orientation to the items based on recognition goals.…

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems.

PubMed

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

NASA Astrophysics Data System (ADS)

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Recognition Without Words: Using Taste to Explore Survival Processing

PubMed Central

Hallock, Henry L.; Garman, Heather D.; Cook, Shaun P.; Gallagher, Shawn P.

2017-01-01

Many educational demonstrations of memory and recall employ word lists and number strings; items that lend themselves to semantic organization and “chunking.” By applying taste recall to the adaptive memory paradigm, which evaluates memory from a survival-based evolutionary perspective, we have developed a simple, inexpensive exercise that defies mnemonic strategies. Most adaptive memory studies have evaluated recall of words encountered while imagining survival and non-survival scenarios. Here, we’ve left the lexical domain and hypothesized that taste memory, as measured by recognition, would be best when acquisition occurs under imagined threat of personal harm, namely poisoning. We tested participants individually while they evaluated eight teas in one of three conditions: in one, they evaluated the toxicity of the tea (survival condition), in a second, they considered the marketability of the tea and, in the third, they evaluated the bitterness of the tea. After a filler task, a surprise recognition task required the participants to taste and identify the eight original teas from a group of 16 that included eight novel teas. The survival condition led to better recognition than the bitterness condition but, surprisingly, it did not yield better recognition than the marketing condition. A second experiment employed a streamlined design more appropriate for classroom settings and failed to support the hypothesis that planning enhanced recognition in survival scenarios. This simple technique has, at least, revealed a robust levels-of-processing effect for taste recognition and invites students to consider the adaptive advantages of all forms of memory. PMID:28690433

Application of an auditory model to speech recognition.

PubMed

Cohen, J R

1989-06-01

Some aspects of auditory processing are incorporated in a front end for the IBM speech-recognition system [F. Jelinek, "Continuous speech recognition by statistical methods," Proc. IEEE 64 (4), 532-556 (1976)]. This new process includes adaptation, loudness scaling, and mel warping. Tests show that the design is an improvement over previous algorithms.

Toward open set recognition.

PubMed

Scheirer, Walter J; de Rezende Rocha, Anderson; Sapkota, Archana; Boult, Terrance E

2013-07-01

To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of "closed set" recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is "open set" recognition, where incomplete knowledge of the world is present at training time, and unknown classes can be submitted to an algorithm during testing. This paper explores the nature of open set recognition and formalizes its definition as a constrained minimization problem. The open set recognition problem is not well addressed by existing algorithms because it requires strong generalization. As a step toward a solution, we introduce a novel "1-vs-set machine," which sculpts a decision space from the marginal distances of a 1-class or binary SVM with a linear kernel. This methodology applies to several different applications in computer vision where open set recognition is a challenging problem, including object recognition and face verification. We consider both in this work, with large scale cross-dataset experiments performed over the Caltech 256 and ImageNet sets, as well as face matching experiments performed over the Labeled Faces in the Wild set. The experiments highlight the effectiveness of machines adapted for open set evaluation compared to existing 1-class and binary SVMs for the same tasks.

Key to the recognition of normapolles and some morphologically similar pollen genera

USGS Publications Warehouse

Batten, D.J.; Christopher, R.A.

1981-01-01

A dichotomous key to the recognition of 86 Normapolles and morphologically similar pollen genera is presented. The key is accompanied by line drawings of each genus and an illustrated glossary of descriptive terms. ?? 1981.

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

NASA Astrophysics Data System (ADS)

Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

Speaker-Machine Interaction in Automatic Speech Recognition. Technical Report.

ERIC Educational Resources Information Center

Makhoul, John I.

The feasibility and limitations of speaker adaptation in improving the performance of a "fixed" (speaker-independent) automatic speech recognition system were examined. A fixed vocabulary of 55 syllables is used in the recognition system which contains 11 stops and fricatives and five tense vowels. The results of an experiment on speaker…

Multi-subject subspace alignment for non-stationary EEG-based emotion recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Liu, Xin; Liu, Dan; Bai, Ou

2018-01-01

Emotion recognition based on EEG signals is a critical component in Human-Machine collaborative environments and psychiatric health diagnoses. However, EEG patterns have been found to vary across subjects due to user fatigue, different electrode placements, and varying impedances, etc. This problem renders the performance of EEG-based emotion recognition highly specific to subjects, requiring time-consuming individual calibration sessions to adapt an emotion recognition system to new subjects. Recently, domain adaptation (DA) strategies have achieved a great deal success in dealing with inter-subject adaptation. However, most of them can only adapt one subject to another subject, which limits their applicability in real-world scenarios. To alleviate this issue, a novel unsupervised DA strategy called Multi-Subject Subspace Alignment (MSSA) is proposed in this paper, which takes advantage of subspace alignment solution and multi-subject information in a unified framework to build personalized models without user-specific labeled data. Experiments on a public EEG dataset known as SEED verify the effectiveness and superiority of MSSA over other state of the art methods for dealing with multi-subject scenarios.

Activity recognition of assembly tasks using body-worn microphones and accelerometers.

PubMed

Ward, Jamie A; Lukowicz, Paul; Tröster, Gerhard; Starner, Thad E

2006-10-01

In order to provide relevant information to mobile users, such as workers engaging in the manual tasks of maintenance and assembly, a wearable computer requires information about the user's specific activities. This work focuses on the recognition of activities that are characterized by a hand motion and an accompanying sound. Suitable activities can be found in assembly and maintenance work. Here, we provide an initial exploration into the problem domain of continuous activity recognition using on-body sensing. We use a mock "wood workshop" assembly task to ground our investigation. We describe a method for the continuous recognition of activities (sawing, hammering, filing, drilling, grinding, sanding, opening a drawer, tightening a vise, and turning a screwdriver) using microphones and three-axis accelerometers mounted at two positions on the user's arms. Potentially "interesting" activities are segmented from continuous streams of data using an analysis of the sound intensity detected at the two different locations. Activity classification is then performed on these detected segments using linear discriminant analysis (LDA) on the sound channel and hidden Markov models (HMMs) on the acceleration data. Four different methods at classifier fusion are compared for improving these classifications. Using user-dependent training, we obtain continuous average recall and precision rates (for positive activities) of 78 percent and 74 percent, respectively. Using user-independent training (leave-one-out across five users), we obtain recall rates of 66 percent and precision rates of 63 percent. In isolation, these activities were recognized with accuracies of 98 percent, 87 percent, and 95 percent for the user-dependent, user-independent, and user-adapted cases, respectively.

Adaptive metric learning with deep neural networks for video-based facial expression recognition

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

Action recognition is sensitive to the identity of the actor.

PubMed

Ferstl, Ylva; Bülthoff, Heinrich; de la Rosa, Stephan

2017-09-01

Recognizing who is carrying out an action is essential for successful human interaction. The cognitive mechanisms underlying this ability are little understood and have been subject of discussions in embodied approaches to action recognition. Here we examine one solution, that visual action recognition processes are at least partly sensitive to the actor's identity. We investigated the dependency between identity information and action related processes by testing the sensitivity of neural action recognition processes to clothing and facial identity information with a behavioral adaptation paradigm. Our results show that action adaptation effects are in fact modulated by both clothing information and the actor's facial identity. The finding demonstrates that neural processes underlying action recognition are sensitive to identity information (including facial identity) and thereby not exclusively tuned to actions. We suggest that such response properties are useful to help humans in knowing who carried out an action. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

The Role of Higher Level Adaptive Coding Mechanisms in the Development of Face Recognition

ERIC Educational Resources Information Center

Pimperton, Hannah; Pellicano, Elizabeth; Jeffery, Linda; Rhodes, Gillian

2009-01-01

DevDevelopmental improvements in face identity recognition ability are widely documented, but the source of children's immaturity in face recognition remains unclear. Differences in the way in which children and adults visually represent faces might underlie immaturities in face recognition. Recent evidence of a face identity aftereffect (FIAE),…

Goal-seeking neural net for recall and recognition

NASA Astrophysics Data System (ADS)

Omidvar, Omid M.

1990-07-01

Neural networks have been used to mimic cognitive processes which take place in animal brains. The learning capability inherent in neural networks makes them suitable candidates for adaptive tasks such as recall and recognition. The synaptic reinforcements create a proper condition for adaptation, which results in memorization, formation of perception, and higher order information processing activities. In this research a model of a goal seeking neural network is studied and the operation of the network with regard to recall and recognition is analyzed. In these analyses recall is defined as retrieval of stored information where little or no matching is involved. On the other hand recognition is recall with matching; therefore it involves memorizing a piece of information with complete presentation. This research takes the generalized view of reinforcement in which all the signals are potential reinforcers. The neuronal response is considered to be the source of the reinforcement. This local approach to adaptation leads to the goal seeking nature of the neurons as network components. In the proposed model all the synaptic strengths are reinforced in parallel while the reinforcement among the layers is done in a distributed fashion and pipeline mode from the last layer inward. A model of complex neuron with varying threshold is developed to account for inhibitory and excitatory behavior of real neuron. A goal seeking model of a neural network is presented. This network is utilized to perform recall and recognition tasks. The performance of the model with regard to the assigned tasks is presented.

Recognition of Similar Shaped Handwritten Marathi Characters Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Jane, Archana P.; Pund, Mukesh A.

2012-03-01

The growing need have handwritten Marathi character recognition in Indian offices such as passport, railways etc has made it vital area of a research. Similar shape characters are more prone to misclassification. In this paper a novel method is provided to recognize handwritten Marathi characters based on their features extraction and adaptive smoothing technique. Feature selections methods avoid unnecessary patterns in an image whereas adaptive smoothing technique form smooth shape of charecters.Combination of both these approaches leads to the better results. Previous study shows that, no one technique achieves 100% accuracy in handwritten character recognition area. This approach of combining both adaptive smoothing & feature extraction gives better results (approximately 75-100) and expected outcomes.

Spatial and temporal adaptations that accompany increasing catching performance during learning.

PubMed

Mazyn, Liesbeth I N; Lenoir, Matthieu; Montagne, Gilles; Savelsbergh, Geert J P

2007-11-01

The authors studied changes in performance and kinematics during the acquisition of a 1-handed catch. Participants were 8 women who took an intensive 2-week training program during which they evolved from poor catchers to subexpert catchers. An increased temporal consistency, shift in spatial location of ball-hand contact away from the body, and higher peak velocity of the transport of the hand toward the ball accompanied their improvement in catching performance. Moreover, novice catchers first adjusted spatial characteristics of the catch to the task constraints and fine-tuned temporal features only later during learning. A principal components analysis on a large set of kinematic variables indicated that a successful catch depends on (a) forward displacement of the hand and (b) the dynamics of the hand closure, thereby providing a kinematic underpinning for the traditional transport-manipulation dissociation in the grasping and catching literature.

Structural Basis for Conserved Regulation and Adaptation of the Signal Recognition Particle Targeting Complex.

PubMed

Wild, Klemens; Bange, Gert; Motiejunas, Domantas; Kribelbauer, Judith; Hendricks, Astrid; Segnitz, Bernd; Wade, Rebecca C; Sinning, Irmgard

2016-07-17

The signal recognition particle (SRP) is a ribonucleoprotein complex with a key role in targeting and insertion of membrane proteins. The two SRP GTPases, SRP54 (Ffh in bacteria) and FtsY (SRα in eukaryotes), form the core of the targeting complex (TC) regulating the SRP cycle. The architecture of the TC and its stimulation by RNA has been described for the bacterial SRP system while this information is lacking for other domains of life. Here, we present the crystal structures of the GTPase heterodimers of archaeal (Sulfolobus solfataricus), eukaryotic (Homo sapiens), and chloroplast (Arabidopsis thaliana) SRP systems. The comprehensive structural comparison combined with Brownian dynamics simulations of TC formation allows for the description of the general blueprint and of specific adaptations of the quasi-symmetric heterodimer. Our work defines conserved external nucleotide-binding sites for SRP GTPase activation by RNA. Structural analyses of the GDP-bound, post-hydrolysis states reveal a conserved, magnesium-sensitive switch within the I-box. Overall, we provide a general model for SRP cycle regulation by RNA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

NASA Astrophysics Data System (ADS)

Heracleous, Panikos; Kaino, Tomomi; Saruwatari, Hiroshi; Shikano, Kiyohiro

2006-12-01

We present the use of stethoscope and silicon NAM (nonaudible murmur) microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible) speech, but also very quietly uttered speech (nonaudible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc.) for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a[InlineEquation not available: see fulltext.] word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Recent progress in invariant pattern recognition

NASA Astrophysics Data System (ADS)

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

1996-12-01

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

Cross-sensor iris recognition through kernel learning.

PubMed

Pillai, Jaishanker K; Puertas, Maria; Chellappa, Rama

2014-01-01

Due to the increasing popularity of iris biometrics, new sensors are being developed for acquiring iris images and existing ones are being continuously upgraded. Re-enrolling users every time a new sensor is deployed is expensive and time-consuming, especially in applications with a large number of enrolled users. However, recent studies show that cross-sensor matching, where the test samples are verified using data enrolled with a different sensor, often lead to reduced performance. In this paper, we propose a machine learning technique to mitigate the cross-sensor performance degradation by adapting the iris samples from one sensor to another. We first present a novel optimization framework for learning transformations on iris biometrics. We then utilize this framework for sensor adaptation, by reducing the distance between samples of the same class, and increasing it between samples of different classes, irrespective of the sensors acquiring them. Extensive evaluations on iris data from multiple sensors demonstrate that the proposed method leads to improvement in cross-sensor recognition accuracy. Furthermore, since the proposed technique requires minimal changes to the iris recognition pipeline, it can easily be incorporated into existing iris recognition systems.

Adaptive Learning and Pruning Using Periodic Packet for Fast Invariance Extraction and Recognition

NASA Astrophysics Data System (ADS)

Chang, Sheng-Jiang; Zhang, Bian-Li; Lin, Lie; Xiong, Tao; Shen, Jin-Yuan

2005-02-01

A new learning scheme using a periodic packet as the neuronal activation function is proposed for invariance extraction and recognition of handwritten digits. Simulation results show that the proposed network can extract the invariant feature effectively and improve both the convergence and the recognition rate.

Cough Recognition Based on Mel Frequency Cepstral Coefficients and Dynamic Time Warping

NASA Astrophysics Data System (ADS)

Zhu, Chunmei; Liu, Baojun; Li, Ping

Cough recognition provides important clinical information for the treatment of many respiratory diseases, but the assessment of cough frequency over a long period of time remains unsatisfied for either clinical or research purpose. In this paper, according to the advantage of dynamic time warping (DTW) and the characteristic of cough recognition, an attempt is made to adapt DTW as the recognition algorithm for cough recognition. The process of cough recognition based on mel frequency cepstral coefficients (MFCC) and DTW is introduced. Experiment results of testing samples from 3 subjects show that acceptable performances of cough recognition are obtained by DTW with a small training set.

The Recognition Heuristic: A Review of Theory and Tests

PubMed Central

Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

The recognition heuristic: a review of theory and tests.

PubMed

Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference).

Practical Considerations about Expected A Posteriori Estimation in Adaptive Testing: Adaptive A Priori, Adaptive Correction for Bias, and Adaptive Integration Interval.

ERIC Educational Resources Information Center

Raiche, Gilles; Blais, Jean-Guy

In a computerized adaptive test (CAT), it would be desirable to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Decreasing the number of items is accompanied, however, by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. G. Raiche (2000) has…

Galectins as self/non-self recognition receptors in innate and adaptive immunity: an unresolved paradox

PubMed Central

Vasta, Gerardo R.; Ahmed, Hafiz; Nita-Lazar, Mihai; Banerjee, Aditi; Pasek, Marta; Shridhar, Surekha; Guha, Prasun; Fernández-Robledo, José A.

2012-01-01

Galectins are characterized by their binding affinity for β-galactosides, a unique binding site sequence motif, and wide taxonomic distribution and structural conservation in vertebrates, invertebrates, protista, and fungi. Since their initial description, galectins were considered to bind endogenous (“self”) glycans and mediate developmental processes and cancer. In the past few years, however, numerous studies have described the diverse effects of galectins on cells involved in both innate and adaptive immune responses, and the mechanistic aspects of their regulatory roles in immune homeostasis. More recently, however, evidence has accumulated to suggest that galectins also bind exogenous (“non-self”) glycans on the surface of potentially pathogenic microbes, parasites, and fungi, suggesting that galectins can function as pattern recognition receptors (PRRs) in innate immunity. Thus, a perplexing paradox arises by the fact that galectins also recognize lactosamine-containing glycans on the host cell surface during developmental processes and regulation of immune responses. According to the currently accepted model for non-self recognition, PRRs recognize pathogens via highly conserved microbial surface molecules of wide distribution such as LPS or peptidoglycan (pathogen-associated molecular patterns; PAMPs), which are absent in the host. Hence, this would not apply to galectins, which apparently bind similar self/non-self molecular patterns on host and microbial cells. This paradox underscores first, an oversimplification in the use of the PRR/PAMP terminology. Second, and most importantly, it reveals significant gaps in our knowledge about the diversity of the host galectin repertoire, and the subcellular targeting, localization, and secretion. Furthermore, our knowledge about the structural and biophysical aspects of their interactions with the host and microbial carbohydrate moieties is fragmentary, and warrants further investigation. PMID:22811679

Fifty years of progress in speech and speaker recognition

NASA Astrophysics Data System (ADS)

Furui, Sadaoki

2004-10-01

Speech and speaker recognition technology has made very significant progress in the past 50 years. The progress can be summarized by the following changes: (1) from template matching to corpus-base statistical modeling, e.g., HMM and n-grams, (2) from filter bank/spectral resonance to Cepstral features (Cepstrum + DCepstrum + DDCepstrum), (3) from heuristic time-normalization to DTW/DP matching, (4) from gdistanceh-based to likelihood-based methods, (5) from maximum likelihood to discriminative approach, e.g., MCE/GPD and MMI, (6) from isolated word to continuous speech recognition, (7) from small vocabulary to large vocabulary recognition, (8) from context-independent units to context-dependent units for recognition, (9) from clean speech to noisy/telephone speech recognition, (10) from single speaker to speaker-independent/adaptive recognition, (11) from monologue to dialogue/conversation recognition, (12) from read speech to spontaneous speech recognition, (13) from recognition to understanding, (14) from single-modality (audio signal only) to multi-modal (audio/visual) speech recognition, (15) from hardware recognizer to software recognizer, and (16) from no commercial application to many practical commercial applications. Most of these advances have taken place in both the fields of speech recognition and speaker recognition. The majority of technological changes have been directed toward the purpose of increasing robustness of recognition, including many other additional important techniques not noted above.

Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers

NASA Astrophysics Data System (ADS)

Caballero Morales, Santiago Omar; Cox, Stephen J.

2009-12-01

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform poorly on dysarthric speakers. In this work, rather than adapting the acoustic models, we model the errors made by the speaker and attempt to correct them. For this task, two techniques have been developed: (1) a set of "metamodels" that incorporate a model of the speaker's phonetic confusion matrix into the ASR process; (2) a cascade of weighted finite-state transducers at the confusion matrix, word, and language levels. Both techniques attempt to correct the errors made at the phonetic level and make use of a language model to find the best estimate of the correct word sequence. Our experiments show that both techniques outperform standard adaptation techniques.

Recognition of emotion from body language among patients with unipolar depression

PubMed Central

Loi, Felice; Vaidya, Jatin G.; Paradiso, Sergio

2013-01-01

Major depression may be associated with abnormal perception of emotions and impairment in social adaptation. Emotion recognition from body language and its possible implications to social adjustment have not been examined in patients with depression. Three groups of participants (51 with depression; 68 with history of depression in remission; and 69 never depressed healthy volunteers) were compared on static and dynamic tasks of emotion recognition from body language. Psychosocial adjustment was assessed using the Social Adjustment Scale Self-Report (SAS-SR). Participants with current depression showed reduced recognition accuracy for happy stimuli across tasks relative to remission and comparison participants. Participants with depression tended to show poorer psychosocial adaptation relative to remission and comparison groups. Correlations between perception accuracy of happiness and scores on the SAS-SR were largely not significant. These results indicate that depression is associated with reduced ability to appraise positive stimuli of emotional body language but emotion recognition performance is not tied to social adjustment. These alterations do not appear to be present in participants in remission suggesting state-like qualities. PMID:23608159

The Relationships among Facial Emotion Recognition, Social Skills, and Quality of Life.

ERIC Educational Resources Information Center

Simon, Elliott W.; And Others

1995-01-01

Forty-six institutionalized adults with mild or moderate mental retardation were administered the Vineland Adaptive Behavior Scales (socialization domain), a subjective measure of quality of life, and a facial emotion recognition test. Facial emotion recognition, quality of life, and social skills appeared to be independent of one another. Facial…

Liquid lens: advances in adaptive optics

NASA Astrophysics Data System (ADS)

Casey, Shawn Patrick

2010-12-01

'Liquid lens' technologies promise significant advancements in machine vision and optical communications systems. Adaptations for machine vision, human vision correction, and optical communications are used to exemplify the versatile nature of this technology. Utilization of liquid lens elements allows the cost effective implementation of optical velocity measurement. The project consists of a custom image processor, camera, and interface. The images are passed into customized pattern recognition and optical character recognition algorithms. A single camera would be used for both speed detection and object recognition.

Contributions of feature shapes and surface cues to the recognition and neural representation of facial identity.

PubMed

Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W

2016-10-01

A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relating the Content and Confidence of Recognition Judgments

PubMed Central

Selmeczy, Diana; Dobbins, Ian G.

2014-01-01

The Remember/Know procedure, developed by Tulving (1985) to capture the distinction between the conscious correlates of episodic and semantic retrieval, has spurned considerable research and debate. However, only a handful of reports have examined the recognition content beyond this dichotomous simplification. To address this, we collected participants’ written justifications in support of ordinary old/new recognition decisions accompanied by confidence ratings using a 3-point scale (high/medium/low). Unlike prior research, we did not provide the participants with any descriptions of Remembering or Knowing and thus, if the justifications mapped well onto theory, they would do so spontaneously. Word frequency analysis (unigrams, bigrams, and trigrams), independent ratings, and machine learning techniques (Support Vector Machine - SVM) converged in demonstrating that the linguistic content of high and medium confidence recognition differs in a manner consistent with dual process theories of recognition. For example, the use of ‘I remember’, particularly when combined with temporal or perceptual information (e.g., ‘when’, ‘saw’, ‘distinctly’), was heavily associated with high confidence recognition. Conversely, participants also used the absence of remembering for personally distinctive materials as support for high confidence new reports (‘would have remembered’). Thus, participants afford a special status to the presence or absence of remembering and use this actively as a basis for high confidence during recognition judgments. Additionally, the pattern of classification successes and failures of a SVM was well anticipated by the Dual Process Signal Detection model of recognition and inconsistent with a single process, strictly unidimensional approach. “One might think that memory should have something to do with remembering, and remembering is a conscious experience.”(Tulving, 1985, p. 1) PMID:23957366

Reversal deterioration of renal function accompanied with primary hypothyrodism.

PubMed

Dragović, Tamara

2012-02-01

Hypothyroidism is often accompanied with decline of kidney function, or inability to maintain electrolyte balance. These changes are usually overlooked in everyday practice. Early recognition of this association eliminates unnecessary diagnostic procedures that postpone the adequate treatment. Two patients with elevated serum creatinine levels due to primary autoimmune hypothyroidism, with complete recovery of creatinine clearance after thyroid hormone substitution therapy are presented. The first patient was a young male whose laboratory tests suggested acute renal failure, and the delicate clinical presentation of reduced thyroid function. The second patient was an elderly woman with a history of a long-term signs and symptoms attributed to ageing, including the deterioration of renal function, with consequently delayed diagnosis of hypothyroidism. Serum thyrotropin and thyroxin levels measurement should be done in all cases of renal failure with undefined renal desease, even if the typical clinical presentation of hypothyroidism is absent. Thyroid hormone assays sholud also be performed in all patients with chronic kidney disease whose kidney function is rapidly worsening.

19 CFR 148.4 - Accompanying articles.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Accompanying articles. 148.4 Section 148.4 Customs... (CONTINUED) PERSONAL DECLARATIONS AND EXEMPTIONS General Provisions § 148.4 Accompanying articles. (a) Generally. Articles shall be considered as accompanying a passenger or brought in by him if the articles...

19 CFR 148.4 - Accompanying articles.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Accompanying articles. 148.4 Section 148.4 Customs... (CONTINUED) PERSONAL DECLARATIONS AND EXEMPTIONS General Provisions § 148.4 Accompanying articles. (a) Generally. Articles shall be considered as accompanying a passenger or brought in by him if the articles...

19 CFR 148.4 - Accompanying articles.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Accompanying articles. 148.4 Section 148.4 Customs... (CONTINUED) PERSONAL DECLARATIONS AND EXEMPTIONS General Provisions § 148.4 Accompanying articles. (a) Generally. Articles shall be considered as accompanying a passenger or brought in by him if the articles...

19 CFR 148.4 - Accompanying articles.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Accompanying articles. 148.4 Section 148.4 Customs... (CONTINUED) PERSONAL DECLARATIONS AND EXEMPTIONS General Provisions § 148.4 Accompanying articles. (a) Generally. Articles shall be considered as accompanying a passenger or brought in by him if the articles...

19 CFR 148.4 - Accompanying articles.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Accompanying articles. 148.4 Section 148.4 Customs... (CONTINUED) PERSONAL DECLARATIONS AND EXEMPTIONS General Provisions § 148.4 Accompanying articles. (a) Generally. Articles shall be considered as accompanying a passenger or brought in by him if the articles...

Familiarity and face emotion recognition in patients with schizophrenia.

PubMed

Lahera, Guillermo; Herrera, Sara; Fernández, Cristina; Bardón, Marta; de los Ángeles, Victoria; Fernández-Liria, Alberto

2014-01-01

To assess the emotion recognition in familiar and unknown faces in a sample of schizophrenic patients and healthy controls. Face emotion recognition of 18 outpatients diagnosed with schizophrenia (DSM-IVTR) and 18 healthy volunteers was assessed with two Emotion Recognition Tasks using familiar faces and unknown faces. Each subject was accompanied by 4 familiar people (parents, siblings or friends), which were photographed by expressing the 6 Ekman's basic emotions. Face emotion recognition in familiar faces was assessed with this ad hoc instrument. In each case, the patient scored (from 1 to 10) the subjective familiarity and affective valence corresponding to each person. Patients with schizophrenia not only showed a deficit in the recognition of emotions on unknown faces (p=.01), but they also showed an even more pronounced deficit on familiar faces (p=.001). Controls had a similar success rate in the unknown faces task (mean: 18 +/- 2.2) and the familiar face task (mean: 17.4 +/- 3). However, patients had a significantly lower score in the familiar faces task (mean: 13.2 +/- 3.8) than in the unknown faces task (mean: 16 +/- 2.4; p<.05). In both tests, the highest number of errors was with emotions of anger and fear. Subjectively, the patient group showed a lower level of familiarity and emotional valence to their respective relatives (p<.01). The sense of familiarity may be a factor involved in the face emotion recognition and it may be disturbed in schizophrenia. © 2013.

Semantic and visual determinants of face recognition in a prosopagnosic patient.

PubMed

Dixon, M J; Bub, D N; Arguin, M

1998-05-01

Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

PubMed

Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

2014-06-01

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

Patterns of genome evolution that have accompanied host adaptation in Salmonella

PubMed Central

Langridge, Gemma C.; Fookes, Maria; Connor, Thomas R.; Feltwell, Theresa; Feasey, Nicholas; Parsons, Bryony N.; Seth-Smith, Helena M. B.; Barquist, Lars; Stedman, Anna; Humphrey, Tom; Wigley, Paul; Peters, Sarah E.; Maskell, Duncan J.; Corander, Jukka; Chabalgoity, Jose A.; Barrow, Paul; Parkhill, Julian; Dougan, Gordon; Thomson, Nicholas R.

2015-01-01

Many bacterial pathogens are specialized, infecting one or few hosts, and this is often associated with more acute disease presentation. Specific genomes show markers of this specialization, which often reflect a balance between gene acquisition and functional gene loss. Within Salmonella enterica subspecies enterica, a single lineage exists that includes human and animal pathogens adapted to cause infection in different hosts, including S. enterica serovar Enteritidis (multiple hosts), S. Gallinarum (birds), and S. Dublin (cattle). This provides an excellent evolutionary context in which differences between these pathogen genomes can be related to host range. Genome sequences were obtained from ∼60 isolates selected to represent the known diversity of this lineage. Examination and comparison of the clades within the phylogeny of this lineage revealed signs of host restriction as well as evolutionary events that mark a path to host generalism. We have identified the nature and order of events for both evolutionary trajectories. The impact of functional gene loss was predicted based upon position within metabolic pathways and confirmed with phenotyping assays. The structure of S. Enteritidis is more complex than previously known, as a second clade of S. Enteritidis was revealed that is distinct from those commonly seen to cause disease in humans or animals, and that is more closely related to S. Gallinarum. Isolates from this second clade were tested in a chick model of infection and exhibited a reduced colonization phenotype, which we postulate represents an intermediate stage in pathogen–host adaptation. PMID:25535353

Levels-of-Processing Effect on Frontotemporal Function in Schizophrenia During Word Encoding and Recognition

PubMed Central

Ragland, J. Daniel; Gur, Ruben C.; Valdez, Jeffrey N.; Loughead, James; Elliott, Mark; Kohler, Christian; Kanes, Stephen; Siegel, Steven J.; Moelter, Stephen T.; Gur, Raquel E.

2015-01-01

Objective Patients with schizophrenia improve episodic memory accuracy when given organizational strategies through levels-of-processing paradigms. This study tested if improvement is accompanied by normalized frontotemporal function. Method Event-related blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) was used to measure activation during shallow (perceptual) and deep (semantic) word encoding and recognition in 14 patients with schizophrenia and 14 healthy comparison subjects. Results Despite slower and less accurate overall word classification, the patients showed normal levels-of-processing effects, with faster and more accurate recognition of deeply processed words. These effects were accompanied by left ventrolateral prefrontal activation during encoding in both groups, although the thalamus, hippocampus, and lingual gyrus were overactivated in the patients. During word recognition, the patients showed overactivation in the left frontal pole and had a less robust right prefrontal response. Conclusions Evidence of normal levels-of-processing effects and left prefrontal activation suggests that patients with schizophrenia can form and maintain semantic representations when they are provided with organizational cues and can improve their word encoding and retrieval. Areas of overactivation suggest residual inefficiencies. Nevertheless, the effect of teaching organizational strategies on episodic memory and brain function is a worthwhile topic for future interventional studies. PMID:16199830

Levels-of-processing effect on frontotemporal function in schizophrenia during word encoding and recognition.

PubMed

Ragland, J Daniel; Gur, Ruben C; Valdez, Jeffrey N; Loughead, James; Elliott, Mark; Kohler, Christian; Kanes, Stephen; Siegel, Steven J; Moelter, Stephen T; Gur, Raquel E

2005-10-01

Patients with schizophrenia improve episodic memory accuracy when given organizational strategies through levels-of-processing paradigms. This study tested if improvement is accompanied by normalized frontotemporal function. Event-related blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) was used to measure activation during shallow (perceptual) and deep (semantic) word encoding and recognition in 14 patients with schizophrenia and 14 healthy comparison subjects. Despite slower and less accurate overall word classification, the patients showed normal levels-of-processing effects, with faster and more accurate recognition of deeply processed words. These effects were accompanied by left ventrolateral prefrontal activation during encoding in both groups, although the thalamus, hippocampus, and lingual gyrus were overactivated in the patients. During word recognition, the patients showed overactivation in the left frontal pole and had a less robust right prefrontal response. Evidence of normal levels-of-processing effects and left prefrontal activation suggests that patients with schizophrenia can form and maintain semantic representations when they are provided with organizational cues and can improve their word encoding and retrieval. Areas of overactivation suggest residual inefficiencies. Nevertheless, the effect of teaching organizational strategies on episodic memory and brain function is a worthwhile topic for future interventional studies.

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

PubMed

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

2004-02-01

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

Toward More Accurate Iris Recognition Using Cross-Spectral Matching.

PubMed

Nalla, Pattabhi Ramaiah; Kumar, Ajay

2017-01-01

Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs, which continue to acquire millions of iris images to establish identity among billions. However, with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields model to significantly improve cross-domain iris recognition. The proposed domain adaptation framework based on the naive Bayes nearest neighbor classification uses a real-valued feature representation, which is capable of learning domain knowledge. Our approach to estimate corresponding visible iris patterns from the synthesis of iris patches in the near infrared iris images achieves outperforming results for the cross-spectral iris recognition. In this paper, a new class of bi-spectral iris recognition system that can simultaneously acquire visible and near infra-red images with pixel-to-pixel correspondences is proposed and evaluated. This paper presents experimental results from three publicly available databases; PolyU cross-spectral iris image database, IIITD CLI and UND database, and achieve outperforming results for the cross-sensor and cross-spectral iris matching.

Event identification by acoustic signature recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dress, W.B.; Kercel, S.W.

1995-07-01

Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and futuremore » applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.« less

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

NASA Astrophysics Data System (ADS)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image

An improved finger-vein recognition algorithm based on template matching

NASA Astrophysics Data System (ADS)

Liu, Yueyue; Di, Si; Jin, Jian; Huang, Daoping

2016-10-01

Finger-vein recognition has became the most popular biometric identify methods. The investigation on the recognition algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein recognition algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.

Finger vein recognition based on finger crease location

NASA Astrophysics Data System (ADS)

Lu, Zhiying; Ding, Shumeng; Yin, Jing

2016-07-01

Finger vein recognition technology has significant advantages over other methods in terms of accuracy, uniqueness, and stability, and it has wide promising applications in the field of biometric recognition. We propose using finger creases to locate and extract an object region. Then we use linear fitting to overcome the problem of finger rotation in the plane. The method of modular adaptive histogram equalization (MAHE) is presented to enhance image contrast and reduce computational cost. To extract the finger vein features, we use a fusion method, which can obtain clear and distinguishable vein patterns under different conditions. We used the Hausdorff average distance algorithm to examine the recognition performance of the system. The experimental results demonstrate that MAHE can better balance the recognition accuracy and the expenditure of time compared with three other methods. Our resulting equal error rate throughout the total procedure was 3.268% in a database of 153 finger vein images.

Action recognition in depth video from RGB perspective: A knowledge transfer manner

NASA Astrophysics Data System (ADS)

Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

2018-03-01

Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

Facial emotion recognition, socio-occupational functioning and expressed emotions in schizophrenia versus bipolar disorder.

PubMed

Thonse, Umesh; Behere, Rishikesh V; Praharaj, Samir Kumar; Sharma, Podila Sathya Venkata Narasimha

2018-06-01

Facial emotion recognition deficits have been consistently demonstrated in patients with severe mental disorders. Expressed emotion is found to be an important predictor of relapse. However, the relationship between facial emotion recognition abilities and expressed emotions and its influence on socio-occupational functioning in schizophrenia versus bipolar disorder has not been studied. In this study we examined 91 patients with schizophrenia and 71 with bipolar disorder for psychopathology, socio occupational functioning and emotion recognition abilities. Primary caregivers of 62 patients with schizophrenia and 49 with bipolar disorder were assessed on Family Attitude Questionnaire to assess their expressed emotions. Patients of schizophrenia and bipolar disorder performed similarly on the emotion recognition task. Patients with schizophrenia group experienced higher critical comments and had a poorer socio-occupational functioning as compared to patients with bipolar disorder. Poorer socio-occupational functioning in patients with schizophrenia was significantly associated with greater dissatisfaction in their caregivers. In patients with bipolar disorder, poorer emotion recognition scores significantly correlated with poorer adaptive living skills and greater hostility and dissatisfaction in their caregivers. The findings of our study suggest that emotion recognition abilities in patients with bipolar disorder are associated with negative expressed emotions leading to problems in adaptive living skills. Copyright © 2018 Elsevier B.V. All rights reserved.

Cognitive impairments accompanying rodent mild traumatic brain injury involve p53-dependent neuronal cell death and are ameliorated by the tetrahydrobenzothiazole PFT-α.

PubMed

Rachmany, Lital; Tweedie, David; Rubovitch, Vardit; Yu, Qian-Sheng; Li, Yazhou; Wang, Jia-Yi; Pick, Chaim G; Greig, Nigel H

2013-01-01

With parallels to concussive mild traumatic brain injury (mTBI) occurring in humans, anesthetized mice subjected to a single 30 g weight drop mTBI event to the right parietal cortex exhibited significant diffuse neuronal degeneration that was accompanied by delayed impairments in recognition and spatial memory. To elucidate the involvement of reversible p53-dependent apoptosis in this neuronal loss and associated cognitive deficits, mice were subjected to experimental mTBI followed by the systemic administration of the tetrahydrobenzothiazole p53 inactivator, PFT-α, or vehicle. Neuronal loss was quantified immunohistochemically at 72 hr. post-injury by the use of fluoro-Jade B and NeuN within the dentate gyrus on both sides of the brain, and recognition and spatial memory were assessed by novel object recognition and Y-maze paradigms at 7 and 30 days post injury. Systemic administration of a single dose of PFT-α 1 hr. post-injury significantly ameliorated both neuronal cell death and cognitive impairments, which were no different from sham control animals. Cellular studies on human SH-SY5Y cells and rat primary neurons challenged with glutamate excitotoxicity and H2O2 induced oxidative stress, confirmed the ability of PFT-α and a close analog to protect against these TBI associated mechanisms mediating neuronal loss. These studies suggest that p53-dependent apoptotic mechanisms underpin the neuronal and cognitive losses accompanying mTBI, and that these are potentially reversible by p53 inactivation.

Astrocytes contribute to gamma oscillations and recognition memory.

PubMed

Lee, Hosuk Sean; Ghetti, Andrea; Pinto-Duarte, António; Wang, Xin; Dziewczapolski, Gustavo; Galimi, Francesco; Huitron-Resendiz, Salvador; Piña-Crespo, Juan C; Roberts, Amanda J; Verma, Inder M; Sejnowski, Terrence J; Heinemann, Stephen F

2014-08-12

Glial cells are an integral part of functional communication in the brain. Here we show that astrocytes contribute to the fast dynamics of neural circuits that underlie normal cognitive behaviors. In particular, we found that the selective expression of tetanus neurotoxin (TeNT) in astrocytes significantly reduced the duration of carbachol-induced gamma oscillations in hippocampal slices. These data prompted us to develop a novel transgenic mouse model, specifically with inducible tetanus toxin expression in astrocytes. In this in vivo model, we found evidence of a marked decrease in electroencephalographic (EEG) power in the gamma frequency range in awake-behaving mice, whereas neuronal synaptic activity remained intact. The reduction in cortical gamma oscillations was accompanied by impaired behavioral performance in the novel object recognition test, whereas other forms of memory, including working memory and fear conditioning, remained unchanged. These results support a key role for gamma oscillations in recognition memory. Both EEG alterations and behavioral deficits in novel object recognition were reversed by suppression of tetanus toxin expression. These data reveal an unexpected role for astrocytes as essential contributors to information processing and cognitive behavior.

Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations From Extreme Learning.

PubMed

Betthauser, Joseph L; Hunt, Christopher L; Osborn, Luke E; Masters, Matthew R; Levay, Gyorgy; Kaliki, Rahul R; Thakor, Nitish V

2018-04-01

Myoelectric signals can be used to predict the intended movements of an amputee for prosthesis control. However, untrained effects like limb position changes influence myoelectric signal characteristics, hindering the ability of pattern recognition algorithms to discriminate among motion classes. Despite frequent and long training sessions, these deleterious conditional influences may result in poor performance and device abandonment. We present a robust sparsity-based adaptive classification method that is significantly less sensitive to signal deviations resulting from untrained conditions. We compare this approach in the offline and online contexts of untrained upper-limb positions for amputee and able-bodied subjects to demonstrate its robustness compared against other myoelectric classification methods. We report significant performance improvements () in untrained limb positions across all subject groups. The robustness of our suggested approach helps to ensure better untrained condition performance from fewer training conditions. This method of prosthesis control has the potential to deliver real-world clinical benefits to amputees: better condition-tolerant performance, reduced training burden in terms of frequency and duration, and increased adoption of myoelectric prostheses.

Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Pohl, Rudiger F.

2009-01-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

The cingulo-opercular network provides word-recognition benefit.

PubMed

Vaden, Kenneth I; Kuchinsky, Stefanie E; Cute, Stephanie L; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2013-11-27

Recognizing speech in difficult listening conditions requires considerable focus of attention that is often demonstrated by elevated activity in putative attention systems, including the cingulo-opercular network. We tested the prediction that elevated cingulo-opercular activity provides word-recognition benefit on a subsequent trial. Eighteen healthy, normal-hearing adults (10 females; aged 20-38 years) performed word recognition (120 trials) in multi-talker babble at +3 and +10 dB signal-to-noise ratios during a sparse sampling functional magnetic resonance imaging (fMRI) experiment. Blood oxygen level-dependent (BOLD) contrast was elevated in the anterior cingulate cortex, anterior insula, and frontal operculum in response to poorer speech intelligibility and response errors. These brain regions exhibited significantly greater correlated activity during word recognition compared with rest, supporting the premise that word-recognition demands increased the coherence of cingulo-opercular network activity. Consistent with an adaptive control network explanation, general linear mixed model analyses demonstrated that increased magnitude and extent of cingulo-opercular network activity was significantly associated with correct word recognition on subsequent trials. These results indicate that elevated cingulo-opercular network activity is not simply a reflection of poor performance or error but also supports word recognition in difficult listening conditions.

Error Rates in Users of Automatic Face Recognition Software

PubMed Central

White, David; Dunn, James D.; Schmid, Alexandra C.; Kemp, Richard I.

2015-01-01

In recent years, wide deployment of automatic face recognition systems has been accompanied by substantial gains in algorithm performance. However, benchmarking tests designed to evaluate these systems do not account for the errors of human operators, who are often an integral part of face recognition solutions in forensic and security settings. This causes a mismatch between evaluation tests and operational accuracy. We address this by measuring user performance in a face recognition system used to screen passport applications for identity fraud. Experiment 1 measured target detection accuracy in algorithm-generated ‘candidate lists’ selected from a large database of passport images. Accuracy was notably poorer than in previous studies of unfamiliar face matching: participants made over 50% errors for adult target faces, and over 60% when matching images of children. Experiment 2 then compared performance of student participants to trained passport officers–who use the system in their daily work–and found equivalent performance in these groups. Encouragingly, a group of highly trained and experienced “facial examiners” outperformed these groups by 20 percentage points. We conclude that human performance curtails accuracy of face recognition systems–potentially reducing benchmark estimates by 50% in operational settings. Mere practise does not attenuate these limits, but superior performance of trained examiners suggests that recruitment and selection of human operators, in combination with effective training and mentorship, can improve the operational accuracy of face recognition systems. PMID:26465631

Gravitational adaptation of animals

NASA Technical Reports Server (NTRS)

Smith, A. H.; Burton, R. R.

1982-01-01

The effect of gravitational adaptation is studied in a group of five Leghorn cocks which had become physiologically adapted to 2 G after 162 days of centrifugation. After this period of adaptation, they are periodically exposed to a 2 G field, accompanied by five previously unexposed hatch-mates, and the degree of retained acceleration adaptation is estimated from the decrease in lymphocyte frequency after 24 hr at 2 G. Results show that the previously adapted birds exhibit an 84% greater lymphopenia than the unexposed birds, and that the lymphocyte frequency does not decrease to a level below that found at the end of 162 days at 2 G. In addition, the capacity for adaptation to chronic acceleration is found to be highly heritable. An acceleration tolerant strain of birds shows lesser mortality during chronic acceleration, particularly in intermediate fields, although the result of acceleration selection is largely quantitative (a greater number of survivors) rather than qualitative (behavioral or physiological changes).

Multifeature-based high-resolution palmprint recognition.

PubMed

Dai, Jifeng; Zhou, Jie

2011-05-01

Palmprint is a promising biometric feature for use in access control and forensic applications. Previous research on palmprint recognition mainly concentrates on low-resolution (about 100 ppi) palmprints. But for high-security applications (e.g., forensic usage), high-resolution palmprints (500 ppi or higher) are required from which more useful information can be extracted. In this paper, we propose a novel recognition algorithm for high-resolution palmprint. The main contributions of the proposed algorithm include the following: 1) use of multiple features, namely, minutiae, density, orientation, and principal lines, for palmprint recognition to significantly improve the matching performance of the conventional algorithm. 2) Design of a quality-based and adaptive orientation field estimation algorithm which performs better than the existing algorithm in case of regions with a large number of creases. 3) Use of a novel fusion scheme for an identification application which performs better than conventional fusion methods, e.g., weighted sum rule, SVMs, or Neyman-Pearson rule. Besides, we analyze the discriminative power of different feature combinations and find that density is very useful for palmprint recognition. Experimental results on the database containing 14,576 full palmprints show that the proposed algorithm has achieved a good performance. In the case of verification, the recognition system's False Rejection Rate (FRR) is 16 percent, which is 17 percent lower than the best existing algorithm at a False Acceptance Rate (FAR) of 10(-5), while in the identification experiment, the rank-1 live-scan partial palmprint recognition rate is improved from 82.0 to 91.7 percent.

An adaptive Hidden Markov Model for activity recognition based on a wearable multi-sensor device

USDA-ARS?s Scientific Manuscript database

Human activity recognition is important in the study of personal health, wellness and lifestyle. In order to acquire human activity information from the personal space, many wearable multi-sensor devices have been developed. In this paper, a novel technique for automatic activity recognition based o...

Adaptive Hybrid Picture Coding. Volume 2.

DTIC Science & Technology

1985-02-01

ooo5 V.a Measurement Vector ..eho..............57 V.b Size Variable o .entroi* Vector .......... .- 59 V * c Shape Vector .Ř 0-60o oe 6 I V~d...the Program for the Adaptive Line of Sight Method .i.. 18.. o ... .... .... 1 B Details of the Feature Vector FormationProgram .. o ...oo..-....- .122 C ...shape recognition is analogous to recognition of curves in space. Therefore, well known concepts and theorems from differential geometry can be 34 . o

Recognition intent and visual word recognition.

PubMed

Wang, Man-Ying; Ching, Chi-Le

2009-03-01

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

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Iris double recognition based on modified evolutionary neural network

NASA Astrophysics Data System (ADS)

Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

2017-11-01

Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

Control of adaptive immunity by the innate immune system.

PubMed

Iwasaki, Akiko; Medzhitov, Ruslan

2015-04-01

Microbial infections are recognized by the innate immune system both to elicit immediate defense and to generate long-lasting adaptive immunity. To detect and respond to vastly different groups of pathogens, the innate immune system uses several recognition systems that rely on sensing common structural and functional features associated with different classes of microorganisms. These recognition systems determine microbial location, viability, replication and pathogenicity. Detection of these features by recognition pathways of the innate immune system is translated into different classes of effector responses though specialized populations of dendritic cells. Multiple mechanisms for the induction of immune responses are variations on a common design principle wherein the cells that sense infections produce one set of cytokines to induce lymphocytes to produce another set of cytokines, which in turn activate effector responses. Here we discuss these emerging principles of innate control of adaptive immunity.

Development of visuo-haptic transfer for object recognition in typical preschool and school-aged children.

PubMed

Purpura, Giulia; Cioni, Giovanni; Tinelli, Francesca

2018-07-01

Object recognition is a long and complex adaptive process and its full maturation requires combination of many different sensory experiences as well as cognitive abilities to manipulate previous experiences in order to develop new percepts and subsequently to learn from the environment. It is well recognized that the transfer of visual and haptic information facilitates object recognition in adults, but less is known about development of this ability. In this study, we explored the developmental course of object recognition capacity in children using unimodal visual information, unimodal haptic information, and visuo-haptic information transfer in children from 4 years to 10 years and 11 months of age. Participants were tested through a clinical protocol, involving visual exploration of black-and-white photographs of common objects, haptic exploration of real objects, and visuo-haptic transfer of these two types of information. Results show an age-dependent development of object recognition abilities for visual, haptic, and visuo-haptic modalities. A significant effect of time on development of unimodal and crossmodal recognition skills was found. Moreover, our data suggest that multisensory processes for common object recognition are active at 4 years of age. They facilitate recognition of common objects, and, although not fully mature, are significant in adaptive behavior from the first years of age. The study of typical development of visuo-haptic processes in childhood is a starting point for future studies regarding object recognition in impaired populations.

Differences in intersaccadic adaptation transfer between inward and outward adaptation.

PubMed

Schnier, Fabian; Lappe, Markus

2011-09-01

Saccadic adaptation is a mechanism to increase or decrease the amplitude gain of subsequent saccades, if a saccade is not on target. Recent research has shown that the mechanism of gain increasing, or outward adaptation, and the mechanism of gain decreasing, or inward adaptation, rely on partly different processes. We investigate how outward and inward adaptation of reactive saccades transfer to other types of saccades, namely scanning, overlap, memory-guided, and gap saccades. Previous research has shown that inward adaptation of reactive saccades transfers only partially to these other saccade types, suggesting differences in the control mechanisms between these saccade categories. We show that outward adaptation transfers stronger to scanning and overlap saccades than inward adaptation, and that the strength of transfer depends on the duration for which the saccade target is visible before saccade onset. Furthermore, we show that this transfer is mainly driven by an increase in saccade duration, which is apparent for all saccade categories. Inward adaptation, in contrast, is accompanied by a decrease in duration and in peak velocity, but only the peak velocity decrease transfers from reactive saccades to other saccade categories, i.e., saccadic duration remains constant or even increases for test saccades of the other categories. Our results, therefore, show that duration and peak velocity are independent parameters of saccadic adaptation and that they are differently involved in the transfer of adaptation between saccade categories. Furthermore, our results add evidence that inward and outward adaptation are different processes.

Experimental evidence for chick discrimination without recognition in a brood parasite host.

PubMed

Grim, Tomás

2007-02-07

Recognition is considered a critical basis for discriminatory behaviours in animals. Theoretically, recognition and discrimination of parasitic chicks are not predicted to evolve in hosts of brood parasitic birds that evict nest-mates. Yet, an earlier study showed that host reed warblers (Acrocephalus scirpaceus) of an evicting parasite, the common cuckoo (Cuculus canorus), can avoid the costs of prolonged care for unrelated young by deserting the cuckoo chick before it fledges. Desertion was not based on specific recognition of the parasite because hosts accept any chick cross-fostered into their nests. Thus, the mechanism of this adaptive host response remains enigmatic. Here, I show experimentally that the cue triggering this 'discrimination without recognition' behaviour is the duration of parental care. Neither the intensity of brood care nor the presence of a single-chick in the nest could explain desertions. Hosts responded similarly to foreign chicks, whether heterospecific or experimental conspecifics. The proposed mechanism of discrimination strikingly differs from those found in other parasite-host systems because hosts do not need an internal recognition template of the parasite's appearance to effectively discriminate. Thus, host defences against parasitic chicks may be based upon mechanisms qualitatively different from those operating against parasitic eggs. I also demonstrate that this discriminatory mechanism is non-costly in terms of recognition errors. Comparative data strongly suggest that parasites cannot counter-evolve any adaptation to mitigate effects of this host defence. These findings have crucial implications for the process and end-result of host-parasite arms races and our understanding of the cognitive basis of discriminatory mechanisms in general.

Peptide-specific recognition of human cytomegalovirus strains controls adaptive natural killer cells.

PubMed

Hammer, Quirin; Rückert, Timo; Borst, Eva Maria; Dunst, Josefine; Haubner, André; Durek, Pawel; Heinrich, Frederik; Gasparoni, Gilles; Babic, Marina; Tomic, Adriana; Pietra, Gabriella; Nienen, Mikalai; Blau, Igor Wolfgang; Hofmann, Jörg; Na, Il-Kang; Prinz, Immo; Koenecke, Christian; Hemmati, Philipp; Babel, Nina; Arnold, Renate; Walter, Jörn; Thurley, Kevin; Mashreghi, Mir-Farzin; Messerle, Martin; Romagnani, Chiara

2018-05-01

Natural killer (NK) cells are innate lymphocytes that lack antigen-specific rearranged receptors, a hallmark of adaptive lymphocytes. In some people infected with human cytomegalovirus (HCMV), an NK cell subset expressing the activating receptor NKG2C undergoes clonal-like expansion that partially resembles anti-viral adaptive responses. However, the viral ligand that drives the activation and differentiation of adaptive NKG2C + NK cells has remained unclear. Here we found that adaptive NKG2C + NK cells differentially recognized distinct HCMV strains encoding variable UL40 peptides that, in combination with pro-inflammatory signals, controlled the population expansion and differentiation of adaptive NKG2C + NK cells. Thus, we propose that polymorphic HCMV peptides contribute to shaping of the heterogeneity of adaptive NKG2C + NK cell populations among HCMV-seropositive people.

When Does Less Yield More? The Impact of Severity upon Implicit Recognition in Pure Alexia

ERIC Educational Resources Information Center

Roberts, Daniel J.; Lambon Ralph, Matthew A.; Woollams, Anna M.

2010-01-01

Pure alexia (PA) is characterised by strong effects of word length on reading times and is sometimes accompanied by an overt letter-by-letter (LBL) reading strategy. Past studies have reported "implicit recognition" in some individual PA patients. This is a striking finding because such patients are able to perform semantic classification and…

Cancer cell-selective promoter recognition accompanies antitumor effect by glucocorticoid receptor-targeted gold nanoparticle

NASA Astrophysics Data System (ADS)

Sau, Samaresh; Agarwalla, Pritha; Mukherjee, Sudip; Bag, Indira; Sreedhar, Bojja; Pal-Bhadra, Manika; Patra, Chitta Ranjan; Banerjee, Rajkumar

2014-05-01

Nanoparticles, such as gold nanoparticles (GNP), upon convenient modifications perform multi tasks catering to many biomedical applications. However, GNP or any other type of nanoparticles is yet to achieve the feat of intracellular regulation of endogenous genes of choice such as through manipulation of a gene-promoter in a chromosome. As for gene modulation and delivery, GNP (or other nanoparticles) showed only limited gene therapy potential, which relied on the delivery of `exogenous' genes invoking gene knockdown or replacement. Practically, there are no instances for the nanoparticle-mediated promoter regulation of `endogenous' genes, more so, as a cancer selective phenomenon. In this regard, we report the development of a simple, easily modifiable GNP-formulation, which promoted/up-regulated the expression of a specific category of `endogenous' genes, the glucocorticoid responsive genes. This genetic up-regulation was induced in only cancer cells by modified GNP-mediated transcriptional activation of its cytoplasmic receptor, glucocorticoid receptor (GR). Normal cells and their GR remained primarily unperturbed by this GNP-formulation. The most potent gene up-regulating GNP-formulation down-regulated a cancer-specific proliferative signal, phospho-Akt in cancer cells, which accompanied retardation of tumor growth in the murine melanoma model. We show that GR-targeted GNPs may find potential use in the targeting and modulation of genetic information in cancer towards developing novel anticancer therapeutics.Nanoparticles, such as gold nanoparticles (GNP), upon convenient modifications perform multi tasks catering to many biomedical applications. However, GNP or any other type of nanoparticles is yet to achieve the feat of intracellular regulation of endogenous genes of choice such as through manipulation of a gene-promoter in a chromosome. As for gene modulation and delivery, GNP (or other nanoparticles) showed only limited gene therapy potential, which relied

Automatic anatomy recognition on CT images with pathology

NASA Astrophysics Data System (ADS)

Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

2016-03-01

Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

Mirror-Induced Behavior in the Magpie (Pica pica): Evidence of Self-Recognition

PubMed Central

Prior, Helmut; Schwarz, Ariane; Güntürkün, Onur

2008-01-01

Comparative studies suggest that at least some bird species have evolved mental skills similar to those found in humans and apes. This is indicated by feats such as tool use, episodic-like memory, and the ability to use one's own experience in predicting the behavior of conspecifics. It is, however, not yet clear whether these skills are accompanied by an understanding of the self. In apes, self-directed behavior in response to a mirror has been taken as evidence of self-recognition. We investigated mirror-induced behavior in the magpie, a songbird species from the crow family. As in apes, some individuals behaved in front of the mirror as if they were testing behavioral contingencies. When provided with a mark, magpies showed spontaneous mark-directed behavior. Our findings provide the first evidence of mirror self-recognition in a non-mammalian species. They suggest that essential components of human self-recognition have evolved independently in different vertebrate classes with a separate evolutionary history. PMID:18715117

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

PubMed Central

Shinozaki, Takahiro

2018-01-01

Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data. PMID:29425248

Transfer Learning for Improved Audio-Based Human Activity Recognition.

PubMed

Ntalampiras, Stavros; Potamitis, Ilyas

2018-06-25

Human activities are accompanied by characteristic sound events, the processing of which might provide valuable information for automated human activity recognition. This paper presents a novel approach addressing the case where one or more human activities are associated with limited audio data, resulting in a potentially highly imbalanced dataset. Data augmentation is based on transfer learning; more specifically, the proposed method: (a) identifies the classes which are statistically close to the ones associated with limited data; (b) learns a multiple input, multiple output transformation; and (c) transforms the data of the closest classes so that it can be used for modeling the ones associated with limited data. Furthermore, the proposed framework includes a feature set extracted out of signal representations of diverse domains, i.e., temporal, spectral, and wavelet. Extensive experiments demonstrate the relevance of the proposed data augmentation approach under a variety of generative recognition schemes.

Postsurgical Disfigurement Influences Disgust Recognition: A Case-Control Study.

PubMed

Lisan, Quentin; George, Nathalie; Hans, Stephane; Laccourreye, Ollivier; Lemogne, Cédric

Little is known about how emotion recognition may be modified in individuals prone to elicit disgust. We sought to determine if subjects with total laryngectomy would present a modified recognition of facial expressions of disgust. A total of 29 patients presenting with a history of advanced-stage laryngeal cancer were recruited, 17 being surgically treated (total laryngectomy) and 12 treated with chemoradiation therapy only. Based on a validated set of images of facial expressions of fear, disgust, surprise, happiness, sadness and anger displayed by 6 actors, we presented participants with expressions of each emotion at 5 levels of increasing intensity and measured their ability to recognize these emotions. Participants with (vs without) laryngectomy showed a higher threshold for the recognition of disgust (3.2. vs 2.7 images needed before emotion recognition, p = 0.03) and a lower success rate of correct recognition (75.5% vs 88.9%, p = 0.03). Subjects presenting with an aesthetic impairment of the head and neck showed poorer performance in disgust recognition when compared with those without disfigurement. These findings might relate either to some perceptual adaptation, habituation phenomenon, or to some higher-level processes related to emotion regulation strategies. Copyright © 2018 Academy of Consultation-Liaison Psychiatry. Published by Elsevier Inc. All rights reserved.

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. Copyright © 2014 Elsevier B.V. All rights reserved.

Biochip microsystem for bioinformatics recognition and analysis

NASA Technical Reports Server (NTRS)

Lue, Jaw-Chyng (Inventor); Fang, Wai-Chi (Inventor)

2011-01-01

A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.

Pathogen recognition in the innate immune response.

PubMed

Kumar, Himanshu; Kawai, Taro; Akira, Shizuo

2009-04-28

Immunity against microbial pathogens primarily depends on the recognition of pathogen components by innate receptors expressed on immune and non-immune cells. Innate receptors are evolutionarily conserved germ-line-encoded proteins and include TLRs (Toll-like receptors), RLRs [RIG-I (retinoic acid-inducible gene-I)-like receptors] and NLRs (Nod-like receptors). These receptors recognize pathogens or pathogen-derived products in different cellular compartments, such as the plasma membrane, the endosomes or the cytoplasm, and induce the expression of cytokines, chemokines and co-stimulatory molecules to eliminate pathogens and instruct pathogen-specific adaptive immune responses. In the present review, we will discuss the recent progress in the study of pathogen recognition by TLRs, RLRs and NLRs and their signalling pathways.

Mismatched expressions decrease face recognition and corresponding ERP old/new effects in schizophrenia.

PubMed

Guillaume, Fabrice; Guillem, François; Tiberghien, Guy; Stip, Emmanuel

2012-09-01

The objective was to investigate the electrophysiological (ERP) correlates of mismatched expression on face recognition in schizophrenia. Expression-change effects and associated ERPs were explored in patients with schizophrenia (n = 20) and paired comparison participants (n = 20) on a long-term face-recognition task. A facial-expression change decreased discriminability for patients with schizophrenia than for healthy participants. The patients' recognition deficit was accompanied by the absence of the midfrontal FN400 and late parietal ERP old/new effects in the mismatched-expression condition. By contrast, preserved midfrontal FN400 and late parietal ERP old/new effects were found in both groups in the unchanged-expression condition. Thus, the preserved parietal old/new effect previously observed in schizophrenia was no longer found here in the situation in which expression changes took place between the study and recognition phases. These findings suggest that, when they are not supposed to take the change of expression into account, the recognition deficit observed here in patients with schizophrenia resulted from an impairment in the mechanisms underlying the emergence, assessment, or utilization of familiarity--as indexed by the ERP old/new effects. In these natural conditions, the impact of the expression change on the implementation of retrieval processes offers new insight into schizophrenia-linked deficits in face recognition, with substantial phenomenological differences with respect to the emergence of familiarity.

University of Rhode Island Adapted Aquatics Program Manual. Second Edition.

ERIC Educational Resources Information Center

Bloomquist, Lorraine E.

This manual provides guidelines for aquatic teachers of people with disabilities. It is based on experience in teaching American Red Cross Adapted Aquatics and is to be used to complement and accompany the Red Cross Adapted Aquatics materials. Emphasis is placed on successful experiences in a positive, safe, reinforcing environment stressing…

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

PubMed Central

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

PubMed

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Evaluation of Adaptive Noise Management Technologies for School-Age Children with Hearing Loss.

PubMed

Wolfe, Jace; Duke, Mila; Schafer, Erin; Jones, Christine; Rakita, Lori

2017-05-01

Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments' adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Twelve children with mild to moderately severe sensorineural hearing loss. Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants' perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement

A Spatial Frequency Account of the Detriment that Local Processing of Navon Letters Has on Face Recognition

ERIC Educational Resources Information Center

Hills, Peter J.; Lewis, Michael B.

2009-01-01

Five minutes of processing the local features of a Navon letter causes a detriment in subsequent face-recognition performance (Macrae & Lewis, 2002). We hypothesize a perceptual after effect explanation of this effect in which face recognition is less accurate after adapting to high-spatial frequencies at high contrasts. Five experiments were…

The Development of Spatial Frequency Biases in Face Recognition

ERIC Educational Resources Information Center

Leonard, Hayley C.; Karmiloff-Smith, Annette; Johnson, Mark H.

2010-01-01

Previous research has suggested that a mid-band of spatial frequencies is critical to face recognition in adults, but few studies have explored the development of this bias in children. We present a paradigm adapted from the adult literature to test spatial frequency biases throughout development. Faces were presented on a screen with particular…

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Code of Federal Regulations, 2010 CFR

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

The soluble pattern recognition receptor PTX3 links humoral innate and adaptive immune responses by helping marginal zone B cells

PubMed Central

Sintes, Jordi; Polentarutti, Nadia; Walland, A. Cooper; Yeiser, John R.; Cunha, Cristina; Lacerda, João F.; Salvatori, Giovanni; Blander, J. Magarian

2016-01-01

Pentraxin 3 (PTX3) is a fluid-phase pattern recognition receptor of the humoral innate immune system with ancestral antibody-like properties but unknown antibody-inducing function. In this study, we found binding of PTX3 to splenic marginal zone (MZ) B cells, an innate-like subset of antibody-producing lymphocytes strategically positioned at the interface between the circulation and the adaptive immune system. PTX3 was released by a subset of neutrophils that surrounded the splenic MZ and expressed an immune activation–related gene signature distinct from that of circulating neutrophils. Binding of PTX3 promoted homeostatic production of IgM and class-switched IgG antibodies to microbial capsular polysaccharides, which decreased in PTX3-deficient mice and humans. In addition, PTX3 increased IgM and IgG production after infection with blood-borne encapsulated bacteria or immunization with bacterial carbohydrates. This immunogenic effect stemmed from the activation of MZ B cells through a neutrophil-regulated pathway that elicited class switching and plasmablast expansion via a combination of T cell–independent and T cell–dependent signals. Thus, PTX3 may bridge the humoral arms of the innate and adaptive immune systems by serving as an endogenous adjuvant for MZ B cells. This property could be harnessed to develop more effective vaccines against encapsulated pathogens. PMID:27621420

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

NASA Astrophysics Data System (ADS)

Mathur, Arpit; Reddy, Shankar M.; Hegde, Rajesh M.

2012-12-01

In this article the significance of a new parametric spectral ratio method that can be used to detect whispered speech segments within normally phonated speech is described. Adaptation methods based on the maximum likelihood linear regression (MLLR) are then used to realize a mismatched train-test style speech recognition system. This proposed parametric spectral ratio method computes a ratio spectrum of the linear prediction (LP) and the minimum variance distortion-less response (MVDR) methods. The smoothed ratio spectrum is then used to detect whispered segments of speech within neutral speech segments effectively. The proposed LP-MVDR ratio method exhibits robustness at different SNRs as indicated by the whisper diarization experiments conducted on the CHAINS and the cell phone whispered speech corpus. The proposed method also performs reasonably better than the conventional methods for whisper detection. In order to integrate the proposed whisper detection method into a conventional speech recognition engine with minimal changes, adaptation methods based on the MLLR are used herein. The hidden Markov models corresponding to neutral mode speech are adapted to the whispered mode speech data in the whispered regions as detected by the proposed ratio method. The performance of this method is first evaluated on whispered speech data from the CHAINS corpus. The second set of experiments are conducted on the cell phone corpus of whispered speech. This corpus is collected using a set up that is used commercially for handling public transactions. The proposed whisper speech recognition system exhibits reasonably better performance when compared to several conventional methods. The results shown indicate the possibility of a whispered speech recognition system for cell phone based transactions.

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Beyond Adapting to Climate Change: Embedding Adaptation in Responses to Multiple Threats and Stresses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilbanks, Thomas J; Kates, Dr. Robert W.

2010-01-01

Climate change impacts are already being experienced in every region of the United States and every part of the world most severely in Arctic regions and adaptation is needed now. Although climate change adaptation research is still in its infancy, significant adaptation planning in the United States has already begun in a number of localities. This article seeks to broaden the adaptation effort by integrating it with broader frameworks of hazards research, sustainability science, and community and regional resilience. To extend the range of experience, we draw from ongoing case studies in the Southeastern United States and the environmental historymore » of New Orleans to consider the multiple threats and stresses that all communities and regions experience. Embedding climate adaptation in responses to multiple threats and stresses helps us to understand climate change impacts, themselves often products of multiple stresses, to achieve community acceptance of needed adaptations as co-benefits of addressing multiple threats, and to mainstream the process of climate adaptation through the larger envelope of social relationships, communication channels, and broad-based awareness of needs for risk management that accompany community resilience.« less

Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian

2008-04-01

Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.

Social norms of accompanied young children and observed crossing behaviors.

PubMed

Rosenbloom, Tova; Sapir-Lavid, Yael; Hadari-Carmi, Ofri

2009-01-01

Social norms for accompanied young children and crossing behaviors were examined in two studies conducted in an Ultra-Orthodox Jewish community in Israel. In Study 1, road behaviors of young children crossing with and without accompaniment and older children were observed, and the actual social norm for accompanied school children younger than 9-years-old was examined. In Study 2, the perceived norm of accompaniment was tested by questionnaires. Young children who crossed without accompaniment exhibited poorer crossing skills compared to older children and to young children crossing with accompaniment. In the four locations observed, the actual accompaniment rate ranged between 15%-60%. The perceived social norm for child accompaniment was lower than the actual norm. The discussion refers to both theoretical issues and their practical implications.

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

Enhanced facial texture illumination normalization for face recognition.

PubMed

Luo, Yong; Guan, Ye-Peng

2015-08-01

An uncontrolled lighting condition is one of the most critical challenges for practical face recognition applications. An enhanced facial texture illumination normalization method is put forward to resolve this challenge. An adaptive relighting algorithm is developed to improve the brightness uniformity of face images. Facial texture is extracted by using an illumination estimation difference algorithm. An anisotropic histogram-stretching algorithm is proposed to minimize the intraclass distance of facial skin and maximize the dynamic range of facial texture distribution. Compared with the existing methods, the proposed method can more effectively eliminate the redundant information of facial skin and illumination. Extensive experiments show that the proposed method has superior performance in normalizing illumination variation and enhancing facial texture features for illumination-insensitive face recognition.

Online adaptive neural control of a robotic lower limb prosthesis

NASA Astrophysics Data System (ADS)

Spanias, J. A.; Simon, A. M.; Finucane, S. B.; Perreault, E. J.; Hargrove, L. J.

2018-02-01

Objective. The purpose of this study was to develop and evaluate an adaptive intent recognition algorithm that continuously learns to incorporate a lower limb amputee’s neural information (acquired via electromyography (EMG)) as they ambulate with a robotic leg prosthesis. Approach. We present a powered lower limb prosthesis that was configured to acquire the user’s neural information and kinetic/kinematic information from embedded mechanical sensors, and identify and respond to the user’s intent. We conducted an experiment with eight transfemoral amputees over multiple days. EMG and mechanical sensor data were collected while subjects using a powered knee/ankle prosthesis completed various ambulation activities such as walking on level ground, stairs, and ramps. Our adaptive intent recognition algorithm automatically transitioned the prosthesis into the different locomotion modes and continuously updated the user’s model of neural data during ambulation. Main results. Our proposed algorithm accurately and consistently identified the user’s intent over multiple days, despite changing neural signals. The algorithm incorporated 96.31% [0.91%] (mean, [standard error]) of neural information across multiple experimental sessions, and outperformed non-adaptive versions of our algorithm—with a 6.66% [3.16%] relative decrease in error rate. Significance. This study demonstrates that our adaptive intent recognition algorithm enables incorporation of neural information over long periods of use, allowing assistive robotic devices to accurately respond to the user’s intent with low error rates.

Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

PubMed Central

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-01-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

Shape adaptive, robust iris feature extraction from noisy iris images.

PubMed

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

Adaptation of hidden Markov models for recognizing speech of reduced frame rate.

PubMed

Lee, Lee-Min; Jean, Fu-Rong

2013-12-01

The frame rate of the observation sequence in distributed speech recognition applications may be reduced to suit a resource-limited front-end device. In order to use models trained using full-frame-rate data in the recognition of reduced frame-rate (RFR) data, we propose a method for adapting the transition probabilities of hidden Markov models (HMMs) to match the frame rate of the observation. Experiments on the recognition of clean and noisy connected digits are conducted to evaluate the proposed method. Experimental results show that the proposed method can effectively compensate for the frame-rate mismatch between the training and the test data. Using our adapted model to recognize the RFR speech data, one can significantly reduce the computation time and achieve the same level of accuracy as that of a method, which restores the frame rate using data interpolation.

Experimental evidence for chick discrimination without recognition in a brood parasite host

PubMed Central

Grim, Tomáš

2006-01-01

Recognition is considered a critical basis for discriminatory behaviours in animals. Theoretically, recognition and discrimination of parasitic chicks are not predicted to evolve in hosts of brood parasitic birds that evict nest-mates. Yet, an earlier study showed that host reed warblers (Acrocephalus scirpaceus) of an evicting parasite, the common cuckoo (Cuculus canorus), can avoid the costs of prolonged care for unrelated young by deserting the cuckoo chick before it fledges. Desertion was not based on specific recognition of the parasite because hosts accept any chick cross-fostered into their nests. Thus, the mechanism of this adaptive host response remains enigmatic. Here, I show experimentally that the cue triggering this ‘discrimination without recognition’ behaviour is the duration of parental care. Neither the intensity of brood care nor the presence of a single-chick in the nest could explain desertions. Hosts responded similarly to foreign chicks, whether heterospecific or experimental conspecifics. The proposed mechanism of discrimination strikingly differs from those found in other parasite–host systems because hosts do not need an internal recognition template of the parasite's appearance to effectively discriminate. Thus, host defences against parasitic chicks may be based upon mechanisms qualitatively different from those operating against parasitic eggs. I also demonstrate that this discriminatory mechanism is non-costly in terms of recognition errors. Comparative data strongly suggest that parasites cannot counter-evolve any adaptation to mitigate effects of this host defence. These findings have crucial implications for the process and end-result of host–parasite arms races and our understanding of the cognitive basis of discriminatory mechanisms in general. PMID:17164201

Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064

Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.

9 CFR 93.409 - Articles accompanying ruminants.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Articles accompanying ruminants. 93.409 Section 93.409 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT...; REQUIREMENTS FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Ruminants § 93.409 Articles accompanying ruminants...

9 CFR 93.409 - Articles accompanying ruminants.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Articles accompanying ruminants. 93.409 Section 93.409 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT...; REQUIREMENTS FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Ruminants § 93.409 Articles accompanying ruminants...

9 CFR 93.409 - Articles accompanying ruminants.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Articles accompanying ruminants. 93.409 Section 93.409 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT...; REQUIREMENTS FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Ruminants § 93.409 Articles accompanying ruminants...

9 CFR 93.409 - Articles accompanying ruminants.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Articles accompanying ruminants. 93.409 Section 93.409 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT...; REQUIREMENTS FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Ruminants § 93.409 Articles accompanying ruminants...

9 CFR 93.409 - Articles accompanying ruminants.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Articles accompanying ruminants. 93.409 Section 93.409 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT...; REQUIREMENTS FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Ruminants § 93.409 Articles accompanying ruminants...

Stages of processing in associative recognition: evidence from behavior, EEG, and classification.

PubMed

Borst, Jelmer P; Schneider, Darryl W; Walsh, Matthew M; Anderson, John R

2013-12-01

In this study, we investigated the stages of information processing in associative recognition. We recorded EEG data while participants performed an associative recognition task that involved manipulations of word length, associative fan, and probe type, which were hypothesized to affect the perceptual encoding, retrieval, and decision stages of the recognition task, respectively. Analyses of the behavioral and EEG data, supplemented with classification of the EEG data using machine-learning techniques, provided evidence that generally supported the sequence of stages assumed by a computational model developed in the Adaptive Control of Thought-Rational cognitive architecture. However, the results suggested a more complex relationship between memory retrieval and decision-making than assumed by the model. Implications of the results for modeling associative recognition are discussed. The study illustrates how a classifier approach, in combination with focused manipulations, can be used to investigate the timing of processing stages.

Low rate of self-awareness and medical recognition of migraine in Germany.

PubMed

Radtke, A; Neuhauser, H

2012-10-01

The study's objective was to assess self-awareness and medical recognition of migraine and their determinants in Germany. We conducted a nationally representative study of the general population of Germany (N = 7341, aged ≥18 years) by means of computer-assisted telephone interviews. Migraine was diagnosed based on the International Classification of Headache Disorders, second edition (ICDH-II). Twelve-month prevalence of ICHD-II-migraine was 10.6% (women 15.6%, men 5.3%). Seventy percent of ICDH-II-migraineurs recognised their headaches as migraine (moderate agreement between ICDH-II and self-diagnosis, κ = 0.46). Only 42% of migraineurs consulted a physician in the previous 12 months. Of those, 63% reported a medical diagnosis of migraine (moderate agreement, κ = 0.40). Women were more likely to be self-aware (odds ratio [OR] 1.81, 95% confidence interval [CI] 1.27-2.60), but the difference was no longer significant when adjusting for migraine features. Physician recognition was more likely in patients with higher educational level (high vs. low education OR 3.90, 95% CI 1.43-10.61 after adjusting for migrainous features). Best predictors for self-awareness and medical recognition of migraine were typical migraine accompaniments and greater headache intensity. Self-awareness and physician recognition of migraine are low in Germany. Presence of typical migraine features and greater headache intensity facilitate medical recognition and awareness of migraine, especially in females.

A neuroanatomical predictor of mirror self-recognition in chimpanzees.

PubMed

Hecht, E E; Mahovetz, L M; Preuss, T M; Hopkins, W D

2017-01-01

The ability to recognize one's own reflection is shared by humans and only a few other species, including chimpanzees. However, this ability is highly variable across individual chimpanzees. In humans, self-recognition involves a distributed, right-lateralized network including frontal and parietal regions involved in the production and perception of action. The superior longitudinal fasciculus (SLF) is a system of white matter tracts linking these frontal and parietal regions. The current study measured mirror self-recognition (MSR) and SLF anatomy in 60 chimpanzees using diffusion tensor imaging. Successful self-recognition was associated with greater rightward asymmetry in the white matter of SLFII and SLFIII, and in SLFIII's gray matter terminations in Broca's area. We observed a visible progression of SLFIII's prefrontal extension in apes that show negative, ambiguous, and compelling evidence of MSR. Notably, SLFIII's terminations in Broca's area are not right-lateralized or particularly pronounced at the population level in chimpanzees, as they are in humans. Thus, chimpanzees with more human-like behavior show more human-like SLFIII connectivity. These results suggest that self-recognition may have co-emerged with adaptations to frontoparietal circuitry. © The Author (2016). Published by Oxford University Press.

A neuroanatomical predictor of mirror self-recognition in chimpanzees

PubMed Central

Mahovetz, L. M.; Preuss, T. M.; Hopkins, W. D.

2017-01-01

Abstract The ability to recognize one’s own reflection is shared by humans and only a few other species, including chimpanzees. However, this ability is highly variable across individual chimpanzees. In humans, self-recognition involves a distributed, right-lateralized network including frontal and parietal regions involved in the production and perception of action. The superior longitudinal fasciculus (SLF) is a system of white matter tracts linking these frontal and parietal regions. The current study measured mirror self-recognition (MSR) and SLF anatomy in 60 chimpanzees using diffusion tensor imaging. Successful self-recognition was associated with greater rightward asymmetry in the white matter of SLFII and SLFIII, and in SLFIII’s gray matter terminations in Broca’s area. We observed a visible progression of SLFIII’s prefrontal extension in apes that show negative, ambiguous, and compelling evidence of MSR. Notably, SLFIII’s terminations in Broca’s area are not right-lateralized or particularly pronounced at the population level in chimpanzees, as they are in humans. Thus, chimpanzees with more human-like behavior show more human-like SLFIII connectivity. These results suggest that self-recognition may have co-emerged with adaptations to frontoparietal circuitry. PMID:27803287

16 CFR 1500.125 - Labeling requirements for accompanying literature.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 2 2011-01-01 2011-01-01 false Labeling requirements for accompanying literature. 1500.125 Section 1500.125 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL... REGULATIONS § 1500.125 Labeling requirements for accompanying literature. When any accompanying literature...

16 CFR 1500.125 - Labeling requirements for accompanying literature.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 16 Commercial Practices 2 2014-01-01 2014-01-01 false Labeling requirements for accompanying literature. 1500.125 Section 1500.125 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL... REGULATIONS § 1500.125 Labeling requirements for accompanying literature. When any accompanying literature...

16 CFR 1500.125 - Labeling requirements for accompanying literature.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Labeling requirements for accompanying literature. 1500.125 Section 1500.125 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL... REGULATIONS § 1500.125 Labeling requirements for accompanying literature. When any accompanying literature...

16 CFR 1500.125 - Labeling requirements for accompanying literature.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Labeling requirements for accompanying literature. 1500.125 Section 1500.125 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL... REGULATIONS § 1500.125 Labeling requirements for accompanying literature. When any accompanying literature...

9 CFR 93.307 - Articles accompanying horses.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Articles accompanying horses. 93.307 Section 93.307 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Horses § 93.307 Articles accompanying horses. No...

9 CFR 93.208 - Articles accompanying poultry.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Articles accompanying poultry. 93.208 Section 93.208 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Poultry § 93.208 Articles accompanying poultry. No...

9 CFR 93.307 - Articles accompanying horses.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Articles accompanying horses. 93.307 Section 93.307 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Horses § 93.307 Articles accompanying horses. No...

9 CFR 93.208 - Articles accompanying poultry.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Articles accompanying poultry. 93.208 Section 93.208 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Poultry § 93.208 Articles accompanying poultry. No...

9 CFR 93.307 - Articles accompanying horses.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Articles accompanying horses. 93.307 Section 93.307 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Horses § 93.307 Articles accompanying horses. No...

9 CFR 93.508 - Articles accompanying swine.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Articles accompanying swine. 93.508 Section 93.508 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Swine § 93.508 Articles accompanying swine. No litter...

9 CFR 93.508 - Articles accompanying swine.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Articles accompanying swine. 93.508 Section 93.508 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Swine § 93.508 Articles accompanying swine. No litter...

9 CFR 93.508 - Articles accompanying swine.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Articles accompanying swine. 93.508 Section 93.508 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Swine § 93.508 Articles accompanying swine. No litter...

9 CFR 93.208 - Articles accompanying poultry.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Articles accompanying poultry. 93.208 Section 93.208 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Poultry § 93.208 Articles accompanying poultry. No...

9 CFR 93.208 - Articles accompanying poultry.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Articles accompanying poultry. 93.208 Section 93.208 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Poultry § 93.208 Articles accompanying poultry. No...

9 CFR 93.508 - Articles accompanying swine.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Articles accompanying swine. 93.508 Section 93.508 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Swine § 93.508 Articles accompanying swine. No litter...

9 CFR 93.208 - Articles accompanying poultry.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Articles accompanying poultry. 93.208 Section 93.208 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Poultry § 93.208 Articles accompanying poultry. No...

9 CFR 93.307 - Articles accompanying horses.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Articles accompanying horses. 93.307 Section 93.307 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Horses § 93.307 Articles accompanying horses. No...

9 CFR 93.307 - Articles accompanying horses.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Articles accompanying horses. 93.307 Section 93.307 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Horses § 93.307 Articles accompanying horses. No...

9 CFR 93.508 - Articles accompanying swine.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Articles accompanying swine. 93.508 Section 93.508 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... FOR MEANS OF CONVEYANCE AND SHIPPING CONTAINERS Swine § 93.508 Articles accompanying swine. No litter...

Adaptation to novel accents by toddlers

PubMed Central

White, Katherine S.; Aslin, Richard N.

2010-01-01

Word recognition is a balancing act: listeners must be sensitive to phonetic detail to avoid confusing similar words, yet, at the same time, be flexible enough to adapt to phonetically variable pronunciations, such as those produced by speakers of different dialects or by non-native speakers. Recent work has demonstrated that young toddlers are sensitive to phonetic detail during word recognition; pronunciations that deviate from the typical phonological form lead to a disruption of processing. However, it is not known whether young word learners show the flexibility that is characteristic of adult word recognition. The present study explores whether toddlers can adapt to artificial accents in which there is a vowel category shift with respect to the native language. 18–20-month-olds heard mispronunciations of familiar words (e.g., vowels were shifted from [a] to [æ]: “dog” pronounced as “dag”). In test, toddlers were tolerant of mispronunciations if they had recently been exposed to the same vowel shift, but not if they had been exposed to standard pronunciations or other vowel shifts. The effects extended beyond particular items heard in exposure to words sharing the same vowels. These results indicate that, like adults, toddlers show flexibility in their interpretation of phonological detail. Moreover, they suggest that effects of top-down knowledge on the reinterpretation of phonological detail generalize across the phono-lexical system. PMID:21479106

CRISPR-Cas: Adapting to change.

PubMed

Jackson, Simon A; McKenzie, Rebecca E; Fagerlund, Robert D; Kieper, Sebastian N; Fineran, Peter C; Brouns, Stan J J

2017-04-07

Bacteria and archaea are engaged in a constant arms race to defend against the ever-present threats of viruses and invasion by mobile genetic elements. The most flexible weapons in the prokaryotic defense arsenal are the CRISPR-Cas adaptive immune systems. These systems are capable of selective identification and neutralization of foreign DNA and/or RNA. CRISPR-Cas systems rely on stored genetic memories to facilitate target recognition. Thus, to keep pace with a changing pool of hostile invaders, the CRISPR memory banks must be regularly updated with new information through a process termed CRISPR adaptation. In this Review, we outline the recent advances in our understanding of the molecular mechanisms governing CRISPR adaptation. Specifically, the conserved protein machinery Cas1-Cas2 is the cornerstone of adaptive immunity in a range of diverse CRISPR-Cas systems. Copyright © 2017, American Association for the Advancement of Science.

Emotional recognition from the speech signal for a virtual education agent

NASA Astrophysics Data System (ADS)

Tickle, A.; Raghu, S.; Elshaw, M.

2013-06-01

This paper explores the extraction of features from the speech wave to perform intelligent emotion recognition. A feature extract tool (openSmile) was used to obtain a baseline set of 998 acoustic features from a set of emotional speech recordings from a microphone. The initial features were reduced to the most important ones so recognition of emotions using a supervised neural network could be performed. Given that the future use of virtual education agents lies with making the agents more interactive, developing agents with the capability to recognise and adapt to the emotional state of humans is an important step.

Adapting Aquatic Circuit Training for Special Populations.

ERIC Educational Resources Information Center

Thome, Kathleen

1980-01-01

The author discusses how land activities can be adapted to water so that individuals with handicapping conditions can participate in circuit training activities. An initial section lists such organizational procedures as providing vocal and/or visual cues for activities, having assistants accompany the performers throughout the circuit, and…

Pattern Recognition Receptors in Innate Immunity, Host Defense, and Immunopathology

ERIC Educational Resources Information Center

Suresh, Rahul; Mosser, David M.

2013-01-01

Infection by pathogenic microbes initiates a set of complex interactions between the pathogen and the host mediated by pattern recognition receptors. Innate immune responses play direct roles in host defense during the early stages of infection, and they also exert a profound influence on the generation of the adaptive immune responses that ensue.…

The many shades of prion strain adaptation.

PubMed

Baskakov, Ilia V

2014-01-01

In several recent studies transmissible prion disease was induced in animals by inoculation with recombinant prion protein amyloid fibrils produced in vitro. Serial transmission of amyloid fibrils gave rise to a new class of prion strains of synthetic origin. Gradual transformation of disease phenotypes and PrP(Sc) properties was observed during serial transmission of synthetic prions, a process that resembled the phenomenon of prion strain adaptation. The current article discusses the remarkable parallels between phenomena of prion strain adaptation that accompanies cross-species transmission and the evolution of synthetic prions occurring within the same host. Two alternative mechanisms underlying prion strain adaptation and synthetic strain evolution are discussed. The current article highlights the complexity of the prion transmission barrier and strain adaptation and proposes that the phenomenon of prion adaptation is more common than previously thought.

Exploring a recognition-induced recognition decrement

PubMed Central

Dopkins, Stephen; Ngo, Catherine Trinh; Sargent, Jesse

2007-01-01

Four experiments explored a recognition decrement that is associated with the recognition of a word from a short list. The stimulus material for demonstrating the phenomenon was a list of words of different syntactic types. A word from the list was recognized less well following a decision that a word of the same type had occurred in the list than following a decision that such a word had not occurred in the list. A recognition decrement did not occur for a word of a given type following a positive recognition decision to a word of a different type. A recognition decrement did not occur when the list consisted exclusively of nouns. It was concluded that the phenomenon may reflect a criterion shift but probably does not reflect a list strength effect, suppression, or familiarity attribution consequent to a perceived discrepancy between actual and expected fluency. PMID:17063915

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions.

PubMed

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants' tendency to over-attribute anger label to other negative facial expressions. Participants' heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants' performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants' tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children's "pre-existing bias" for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim's perceptive and attentive focus on salient environmental social stimuli.

A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation

NASA Astrophysics Data System (ADS)

Pham, Cuong; Plötz, Thomas; Olivier, Patrick

We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.

Mechanisms of object recognition: what we have learned from pigeons

PubMed Central

Soto, Fabian A.; Wasserman, Edward A.

2014-01-01

Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the “simple” brains of pigeons. PMID:25352784

Unilateral Hearing Loss: Understanding Speech Recognition and Localization Variability-Implications for Cochlear Implant Candidacy.

PubMed

Firszt, Jill B; Reeder, Ruth M; Holden, Laura K

At a minimum, unilateral hearing loss (UHL) impairs sound localization ability and understanding speech in noisy environments, particularly if the loss is severe to profound. Accompanying the numerous negative consequences of UHL is considerable unexplained individual variability in the magnitude of its effects. Identification of covariables that affect outcome and contribute to variability in UHLs could augment counseling, treatment options, and rehabilitation. Cochlear implantation as a treatment for UHL is on the rise yet little is known about factors that could impact performance or whether there is a group at risk for poor cochlear implant outcomes when hearing is near-normal in one ear. The overall goal of our research is to investigate the range and source of variability in speech recognition in noise and localization among individuals with severe to profound UHL and thereby help determine factors relevant to decisions regarding cochlear implantation in this population. The present study evaluated adults with severe to profound UHL and adults with bilateral normal hearing. Measures included adaptive sentence understanding in diffuse restaurant noise, localization, roving-source speech recognition (words from 1 of 15 speakers in a 140° arc), and an adaptive speech-reception threshold psychoacoustic task with varied noise types and noise-source locations. There were three age-sex-matched groups: UHL (severe to profound hearing loss in one ear and normal hearing in the contralateral ear), normal hearing listening bilaterally, and normal hearing listening unilaterally. Although the normal-hearing-bilateral group scored significantly better and had less performance variability than UHLs on all measures, some UHL participants scored within the range of the normal-hearing-bilateral group on all measures. The normal-hearing participants listening unilaterally had better monosyllabic word understanding than UHLs for words presented on the blocked/deaf side but not

Unilateral Hearing Loss: Understanding Speech Recognition and Localization Variability - Implications for Cochlear Implant Candidacy

PubMed Central

Firszt, Jill B.; Reeder, Ruth M.; Holden, Laura K.

2016-01-01

Objectives At a minimum, unilateral hearing loss (UHL) impairs sound localization ability and understanding speech in noisy environments, particularly if the loss is severe to profound. Accompanying the numerous negative consequences of UHL is considerable unexplained individual variability in the magnitude of its effects. Identification of co-variables that affect outcome and contribute to variability in UHLs could augment counseling, treatment options, and rehabilitation. Cochlear implantation as a treatment for UHL is on the rise yet little is known about factors that could impact performance or whether there is a group at risk for poor cochlear implant outcomes when hearing is near-normal in one ear. The overall goal of our research is to investigate the range and source of variability in speech recognition in noise and localization among individuals with severe to profound UHL and thereby help determine factors relevant to decisions regarding cochlear implantation in this population. Design The present study evaluated adults with severe to profound UHL and adults with bilateral normal hearing. Measures included adaptive sentence understanding in diffuse restaurant noise, localization, roving-source speech recognition (words from 1 of 15 speakers in a 140° arc) and an adaptive speech-reception threshold psychoacoustic task with varied noise types and noise-source locations. There were three age-gender-matched groups: UHL (severe to profound hearing loss in one ear and normal hearing in the contralateral ear), normal hearing listening bilaterally, and normal hearing listening unilaterally. Results Although the normal-hearing-bilateral group scored significantly better and had less performance variability than UHLs on all measures, some UHL participants scored within the range of the normal-hearing-bilateral group on all measures. The normal-hearing participants listening unilaterally had better monosyllabic word understanding than UHLs for words presented on

Adaptive remote sensing technology for feature recognition and tracking

NASA Technical Reports Server (NTRS)

Wilson, R. G.; Sivertson, W. E., Jr.; Bullock, G. F.

1979-01-01

A technology development plan designed to reduce the data load and data-management problems associated with global study and monitoring missions is described with a heavy emphasis placed on developing mission capabilities to eliminate the collection of unnecessary data. Improved data selectivity can be achieved through sensor automation correlated with the real-time needs of data users. The first phase of the plan includes the Feature Identification and Location Experiment (FILE) which is scheduled for the 1980 Shuttle flight. The FILE experiment is described with attention given to technology needs, development plan, feature recognition and classification, and cloud-snow detection/discrimination. Pointing, tracking and navigation received particular consideration, and it is concluded that this technology plan is viewed as an alternative to approaches to real-time acquisition that are based on extensive onboard format and inventory processing and reliance upon global-satellite-system navigation data.

Body-wide anatomy recognition in PET/CT images

NASA Astrophysics Data System (ADS)

Wang, Huiqian; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Zhao, Liming; Torigian, Drew A.

2015-03-01

With the rapid growth of positron emission tomography/computed tomography (PET/CT)-based medical applications, body-wide anatomy recognition on whole-body PET/CT images becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem and seldom studied due to unclear anatomy reference frame and low spatial resolution of PET images as well as low contrast and spatial resolution of the associated low-dose CT images. We previously developed an automatic anatomy recognition (AAR) system [15] whose applicability was demonstrated on diagnostic computed tomography (CT) and magnetic resonance (MR) images in different body regions on 35 objects. The aim of the present work is to investigate strategies for adapting the previous AAR system to low-dose CT and PET images toward automated body-wide disease quantification. Our adaptation of the previous AAR methodology to PET/CT images in this paper focuses on 16 objects in three body regions - thorax, abdomen, and pelvis - and consists of the following steps: collecting whole-body PET/CT images from existing patient image databases, delineating all objects in these images, modifying the previous hierarchical models built from diagnostic CT images to account for differences in appearance in low-dose CT and PET images, automatically locating objects in these images following object hierarchy, and evaluating performance. Our preliminary evaluations indicate that the performance of the AAR approach on low-dose CT images achieves object localization accuracy within about 2 voxels, which is comparable to the accuracies achieved on diagnostic contrast-enhanced CT images. Object recognition on low-dose CT images from PET/CT examinations without requiring diagnostic contrast-enhanced CT seems feasible.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

EEG signatures accompanying auditory figure-ground segregation

PubMed Central

Tóth, Brigitta; Kocsis, Zsuzsanna; Háden, Gábor P.; Szerafin, Ágnes; Shinn-Cunningham, Barbara; Winkler, István

2017-01-01

In everyday acoustic scenes, figure-ground segregation typically requires one to group together sound elements over both time and frequency. Electroencephalogram was recorded while listeners detected repeating tonal complexes composed of a random set of pure tones within stimuli consisting of randomly varying tonal elements. The repeating pattern was perceived as a figure over the randomly changing background. It was found that detection performance improved both as the number of pure tones making up each repeated complex (figure coherence) increased, and as the number of repeated complexes (duration) increased – i.e., detection was easier when either the spectral or temporal structure of the figure was enhanced. Figure detection was accompanied by the elicitation of the object related negativity (ORN) and the P400 event-related potentials (ERPs), which have been previously shown to be evoked by the presence of two concurrent sounds. Both ERP components had generators within and outside of auditory cortex. The amplitudes of the ORN and the P400 increased with both figure coherence and figure duration. However, only the P400 amplitude correlated with detection performance. These results suggest that 1) the ORN and P400 reflect processes involved in detecting the emergence of a new auditory object in the presence of other concurrent auditory objects; 2) the ORN corresponds to the likelihood of the presence of two or more concurrent sound objects, whereas the P400 reflects the perceptual recognition of the presence of multiple auditory objects and/or preparation for reporting the detection of a target object. PMID:27421185

EEG signatures accompanying auditory figure-ground segregation.

PubMed

Tóth, Brigitta; Kocsis, Zsuzsanna; Háden, Gábor P; Szerafin, Ágnes; Shinn-Cunningham, Barbara G; Winkler, István

2016-11-01

In everyday acoustic scenes, figure-ground segregation typically requires one to group together sound elements over both time and frequency. Electroencephalogram was recorded while listeners detected repeating tonal complexes composed of a random set of pure tones within stimuli consisting of randomly varying tonal elements. The repeating pattern was perceived as a figure over the randomly changing background. It was found that detection performance improved both as the number of pure tones making up each repeated complex (figure coherence) increased, and as the number of repeated complexes (duration) increased - i.e., detection was easier when either the spectral or temporal structure of the figure was enhanced. Figure detection was accompanied by the elicitation of the object related negativity (ORN) and the P400 event-related potentials (ERPs), which have been previously shown to be evoked by the presence of two concurrent sounds. Both ERP components had generators within and outside of auditory cortex. The amplitudes of the ORN and the P400 increased with both figure coherence and figure duration. However, only the P400 amplitude correlated with detection performance. These results suggest that 1) the ORN and P400 reflect processes involved in detecting the emergence of a new auditory object in the presence of other concurrent auditory objects; 2) the ORN corresponds to the likelihood of the presence of two or more concurrent sound objects, whereas the P400 reflects the perceptual recognition of the presence of multiple auditory objects and/or preparation for reporting the detection of a target object. Copyright © 2016. Published by Elsevier Inc.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Code of Federal Regulations, 2010 CFR

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

Results and conclusions are presented on the application of recent developments in pattern recognition to spacecraft star mapping systems. Sensor data for two representative starfields are processed by an adaptive shape-seeking version of the Fc-V algorithm with good results. Cluster validity measures are evaluated, but not found especially useful to this application. Recommendations are given two system configurations worthy of additional study,

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

PubMed

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

2018-03-01

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

Adaptation aftereffects in the perception of gender from biological motion.

PubMed

Troje, Nikolaus F; Sadr, Javid; Geyer, Henning; Nakayama, Ken

2006-07-28

Human visual perception is highly adaptive. While this has been known and studied for a long time in domains such as color vision, motion perception, or the processing of spatial frequency, a number of more recent studies have shown that adaptation and adaptation aftereffects also occur in high-level visual domains like shape perception and face recognition. Here, we present data that demonstrate a pronounced aftereffect in response to adaptation to the perceived gender of biological motion point-light walkers. A walker that is perceived to be ambiguous in gender under neutral adaptation appears to be male after adaptation with an exaggerated female walker and female after adaptation with an exaggerated male walker. We discuss this adaptation aftereffect as a tool to characterize and probe the mechanisms underlying biological motion perception.

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

PubMed Central

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-01-01

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters. PMID:26690439

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

PubMed

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-12-10

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Entropy in molecular recognition by proteins

PubMed Central

Caro, José A.; Harpole, Kyle W.; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G.; Sharp, Kim A.

2017-01-01

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein–ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein–ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein–ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or “entropy meter” also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water–protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins. PMID:28584100

Entropy in molecular recognition by proteins.

PubMed

Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua

2017-06-20

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions

PubMed Central

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants’ tendency to over-attribute anger label to other negative facial expressions. Participants’ heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants’ performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants’ tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children’s “pre-existing bias” for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim’s perceptive and attentive focus on salient environmental social stimuli. PMID:26509890

Unaware person recognition from the body when face identification fails.

PubMed

Rice, Allyson; Phillips, P Jonathon; Natu, Vaidehi; An, Xiaobo; O'Toole, Alice J

2013-11-01

How does one recognize a person when face identification fails? Here, we show that people rely on the body but are unaware of doing so. State-of-the-art face-recognition algorithms were used to select images of people with almost no useful identity information in the face. Recognition of the face alone in these cases was near chance level, but recognition of the person was accurate. Accuracy in identifying the person without the face was identical to that in identifying the whole person. Paradoxically, people reported relying heavily on facial features over noninternal face and body features in making their identity decisions. Eye movements indicated otherwise, with gaze duration and fixations shifting adaptively toward the body and away from the face when the body was a better indicator of identity than the face. This shift occurred with no cost to accuracy or response time. Human identity processing may be partially inaccessible to conscious awareness.

Adapted Physical Education and Therapeutic Recreation in Schools

ERIC Educational Resources Information Center

Etzel-Wise, D; Mears, B

2004-01-01

Adapted physical education is a mandated service, whereas therapeutic recreation and traditional recreation are considered related services under the Individuals with Disabilities Education Act. In this article, the authors describe the distinctions between the services, recognition of need for referral, methods of assessment, sample…

Sensor agnostic object recognition using a map seeking circuit

NASA Astrophysics Data System (ADS)

Overman, Timothy L.; Hart, Michael

2012-05-01

Automatic object recognition capabilities are traditionally tuned to exploit the specific sensing modality they were designed to. Their successes (and shortcomings) are tied to object segmentation from the background, they typically require highly skilled personnel to train them, and they become cumbersome with the introduction of new objects. In this paper we describe a sensor independent algorithm based on the biologically inspired technology of map seeking circuits (MSC) which overcomes many of these obstacles. In particular, the MSC concept offers transparency in object recognition from a common interface to all sensor types, analogous to a USB device. It also provides a common core framework that is independent of the sensor and expandable to support high dimensionality decision spaces. Ease in training is assured by using commercially available 3D models from the video game community. The search time remains linear no matter how many objects are introduced, ensuring rapid object recognition. Here, we report results of an MSC algorithm applied to object recognition and pose estimation from high range resolution radar (1D), electrooptical imagery (2D), and LIDAR point clouds (3D) separately. By abstracting the sensor phenomenology from the underlying a prior knowledge base, MSC shows promise as an easily adaptable tool for incorporating additional sensor inputs.

Ignoring Memory Hints: The Stubborn Influence of Environmental Cues on Recognition Memory

ERIC Educational Resources Information Center

Selmeczy, Diana; Dobbins, Ian G.

2017-01-01

Recognition judgments can benefit from the use of environmental cues that signal the general likelihood of encountering familiar versus unfamiliar stimuli. While incorporating such cues is often adaptive, there are circumstances (e.g., eyewitness testimony) in which observers should fully ignore environmental cues in order to preserve memory…

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

PubMed Central

Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

A modified active appearance model based on an adaptive artificial bee colony.

PubMed

Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

The Development of Adaptive Decision Making: Recognition-Based Inference in Children and Adolescents

ERIC Educational Resources Information Center

Horn, Sebastian S.; Ruggeri, Azzurra; Pachur, Thorsten

2016-01-01

Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment,…

Acid Response of Bifidobacterium longum subsp. longum BBMN68 Is Accompanied by Modification of the Cell Membrane Fatty Acid Composition.

PubMed

Liu, Songling; Ren, Fazheng; Jiang, Jingli; Zhao, Liang

2016-07-28

The acid response of Bifidobacterium longum subsp. longum BBMN68 has been studied in our previous study. The fab gene, which is supposed to be involved in membrane fatty acid biosynthesis, was demonstrated to be induced in acid response. In order to investigate the relationship between acid response and cell membrane fatty acid composition, the acid adaptation of BBMN68 was assessed and the membrane fatty acid composition at different adaptation conditions was identified. Indeed, the fatty acid composition was influenced by acid adaptation. Our results showed that the effective acid adaptations were accompanied with decrease in the unsaturated to saturated fatty acids ratio (UFA/SFA) and increase in cyclopropane fatty acid (CFA) content, which corresponded to previous studies. Moreover, both effective and non-effective acid adaptation conditions resulted in decrease in the C18:1 cis-9/C18:1 trans-9 ratio, indicating that the C18:1 cis-9/C18:1 trans-9 ratio is associated with acid tolerance response but not with acid adaptation response. Taken together, this study indicated that the UFA/SFA and CFA content of BBMN68 were involved in acid adaptation and the C18:1 cis-9/C18:1 trans-9 ratio was involved in acid tolerance response.

Action recognition using mined hierarchical compound features.

PubMed

Gilbert, Andrew; Illingworth, John; Bowden, Richard

2011-05-01

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

Character Recognition Using Genetically Trained Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diniz, C.; Stantz, K.M.; Trahan, M.W.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfidmore » recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

Recognition of the Component Odors in Mixtures

PubMed Central

Fletcher, Dane B; Hettinger, Thomas P

2017-01-01

Abstract Natural olfactory stimuli are volatile-chemical mixtures in which relative perceptual saliencies determine which odor-components are identified. Odor identification also depends on rapid selective adaptation, as shown for 4 odor stimuli in an earlier experimental simulation of natural conditions. Adapt-test pairs of mixtures of water-soluble, distinct odor stimuli with chemical features in common were studied. Identification decreased for adapted components but increased for unadapted mixture-suppressed components, showing compound identities were retained, not degraded to individual molecular features. Four additional odor stimuli, 1 with 2 perceptible odor notes, and an added “water-adapted” control tested whether this finding would generalize to other 4-compound sets. Selective adaptation of mixtures of the compounds (odors): 3 mM benzaldehyde (cherry), 5 mM maltol (caramel), 1 mM guaiacol (smoke), and 4 mM methyl anthranilate (grape-smoke) again reciprocally unmasked odors of mixture-suppressed components in 2-, 3-, and 4-component mixtures with 2 exceptions. The cherry note of “benzaldehyde” (itself) and the shared note of “methyl anthranilate and guaiacol” (together) were more readily identified. The pervasive mixture-component dominance and dynamic perceptual salience may be mediated through peripheral adaptation and central mutual inhibition of neural responses. Originating in individual olfactory receptor variants, it limits odor identification and provides analytic properties for momentary recognition of a few remaining mixture-components. PMID:28641388

Mechanism of HSV infection through soluble adapter-mediated virus bridging to the EGF receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakano, Kenji, E-mail: kenakano@med.kyushu-u.ac.j; Kobayashi, Masatoshi; Nakamura, Kei-ichiro

2011-04-25

Herpes simplex virus entry into cells requires the binding of envelope glycoprotein D (gD) to an entry receptor. Depending on the cell, entry occurs by different mechanisms, including fusion at the cell surface or endocytosis. Here we examined the entry mechanism through a non-HSV receptor mediated by a soluble bi-specific adapter protein composed of recognition elements for gD and the EGF receptor (EGFR). Virus entered into endosomes using either EGF or an EGFR-specific single chain antibody (scFv) for receptor recognition. Infection was less efficient with the EGF adapter which could be attributed to its weaker binding to a viral gD.more » Infection mediated by the scFv adapter was pH sensitive, indicating that gD-EGFR bridging alone was insufficient for capsid release from endosomes. We also show that the scFv adapter enhanced infection of EGFR-expressing tumor tissue in vivo. Our results indicate that adapters may retarget HSV infection without drastically changing the entry mechanism.« less

Language Model Combination and Adaptation Using Weighted Finite State Transducers

NASA Technical Reports Server (NTRS)

Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.

2010-01-01

In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences

The accompanying adult: authority to give consent in the UK.

PubMed

Lal, Seema Madhur Lata; Parekh, Susan; Mason, Carol; Roberts, Graham

2007-05-01

Children may be accompanied by various people when attending for dental treatment. Before treatment is started, there is a legal requirement that the operator obtain informed consent for the proposed procedure. In the case of minors, the person authorized to give consent (parental responsibility) is usually a parent. To ascertain if accompanying persons of children attending the Department of Paediatric Dentistry at the Eastman Dental Hospital, London were empowered to give consent for the child's dental treatment. A total of 250 accompanying persons of children attending were selected, over a 6-month period. A questionnaire was used to establish whether the accompanying person(s) were authorized to give consent. The study showed that 12% of accompanying persons had no legal authority to give consent for the child's dental treatment. Clinicians need to be aware of the status of persons accompanying children to ensure valid consent is obtained.

Adaptive Myogenesis under Hypoxia

PubMed Central

Yun, Zhong; Lin, Qun; Giaccia, Amato J.

2005-01-01

Previous studies have indicated that myoblasts can differentiate and repair muscle injury after an ischemic insult. However, it is unclear how hypoxia or glucose deprivation in the ischemic microenvironment affects myoblast differentiation. We have found that myogenesis can adapt to hypoxic conditions. This adaptive mechanism is accompanied by initial inhibition of the myoD, E2A, and myogenin genes followed by resumption of their expression in an oxygen-dependent manner. The regulation of myoD transcription by hypoxia is correlated with transient deacetylation of histones associated with the myoD promoter. It is noteworthy that, unlike the differentiation of other cell types such as preadipocytes or chondroblasts, the effect of hypoxia on myogenesis is independent of HIF-1, a ubiquitous regulator of transcription under hypoxia. While myogenesis can also adapt to glucose deprivation, the combination of severe hypoxia and glucose deprivation found in an ischemic environment results in pronounced loss of myoblasts. Our studies indicate that the ischemic muscle can be repaired via the adaptive differentiation of myogenic precursors, which depends on the levels of oxygen and glucose in the ischemic microenvironment. PMID:15798192

Robust Wave-front Correction in a Small Scale Adaptive Optics System Using a Membrane Deformable Mirror

NASA Astrophysics Data System (ADS)

Choi, Y.; Park, S.; Baik, S.; Jung, J.; Lee, S.; Yoo, J.

A small scale laboratory adaptive optics system using a Shack-Hartmann wave-front sensor (WFS) and a membrane deformable mirror (DM) has been built for robust image acquisition. In this study, an adaptive limited control technique is adopted to maintain the long-term correction stability of an adaptive optics system. To prevent the waste of dynamic correction range for correcting small residual wave-front distortions which are inefficient to correct, the built system tries to limit wave-front correction when a similar small difference wave-front pattern is repeatedly generated. Also, the effect of mechanical distortion in an adaptive optics system is studied and a pre-recognition method for the distortion is devised to prevent low-performance system operation. A confirmation process for a balanced work assignment among deformable mirror (DM) actuators is adopted for the pre-recognition. The corrected experimental results obtained by using a built small scale adaptive optics system are described in this paper.

Forecasting of hourly load by pattern recognition in a small area power system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

16 CFR § 1500.125 - Labeling requirements for accompanying literature.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 16 Commercial Practices 2 2013-01-01 2013-01-01 false Labeling requirements for accompanying literature. § 1500.125 Section § 1500.125 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL... REGULATIONS § 1500.125 Labeling requirements for accompanying literature. When any accompanying literature...

Relative preservation of the recognition of positive facial expression "happiness" in Alzheimer disease.

PubMed

Maki, Yohko; Yoshida, Hiroshi; Yamaguchi, Tomoharu; Yamaguchi, Haruyasu

2013-01-01

Positivity recognition bias has been reported for facial expression as well as memory and visual stimuli in aged individuals, whereas emotional facial recognition in Alzheimer disease (AD) patients is controversial, with possible involvement of confounding factors such as deficits in spatial processing of non-emotional facial features and in verbal processing to express emotions. Thus, we examined whether recognition of positive facial expressions was preserved in AD patients, by adapting a new method that eliminated the influences of these confounding factors. Sensitivity of six basic facial expressions (happiness, sadness, surprise, anger, disgust, and fear) was evaluated in 12 outpatients with mild AD, 17 aged normal controls (ANC), and 25 young normal controls (YNC). To eliminate the factors related to non-emotional facial features, averaged faces were prepared as stimuli. To eliminate the factors related to verbal processing, the participants were required to match the images of stimulus and answer, avoiding the use of verbal labels. In recognition of happiness, there was no difference in sensitivity between YNC and ANC, and between ANC and AD patients. AD patients were less sensitive than ANC in recognition of sadness, surprise, and anger. ANC were less sensitive than YNC in recognition of surprise, anger, and disgust. Within the AD patient group, sensitivity of happiness was significantly higher than those of the other five expressions. In AD patient, recognition of happiness was relatively preserved; recognition of happiness was most sensitive and was preserved against the influences of age and disease.

Recognition memory for emotional and neutral faces: an event-related potential study.

PubMed

Johansson, Mikael; Mecklinger, Axel; Treese, Anne-Cécile

2004-12-01

This study examined emotional influences on the hypothesized event-related potential (ERP) correlates of familiarity and recollection (Experiment 1) and the states of awareness (Experiment 2) accompanying recognition memory for faces differing in facial affect. Participants made gender judgments to positive, negative, and neutral faces at study and were in the test phase instructed to discriminate between studied and nonstudied faces. Whereas old-new discrimination was unaffected by facial expression, negative faces were recollected to a greater extent than both positive and neutral faces as reflected in the parietal ERP old-new effect and in the proportion of remember judgments. Moreover, emotion-specific modulations were observed in frontally recorded ERPs elicited by correctly rejected new faces that concurred with a more liberal response criterion for emotional as compared to neutral faces. Taken together, the results are consistent with the view that processes promoting recollection are facilitated for negative events and that emotion may affect recognition performance by influencing criterion setting mediated by the prefrontal cortex.

Conflict adaptation in patients diagnosed with schizophrenia.

PubMed

Abrahamse, Elger; Ruitenberg, Marit; Boddewyn, Sarah; Oreel, Edith; de Schryver, Maarten; Morrens, Manuel; van Dijck, Jean-Philippe

2017-11-01

Cognitive control impairments may contribute strongly to the overall cognitive deficits observed in patients diagnosed with schizophrenia. In the current study we explore a specific cognitive control function referred to as conflict adaptation. Previous studies on conflict adaptation in schizophrenia showed equivocal results, and, moreover, were plagued by confounded research designs. Here we assessed for the first time conflict adaptation in schizophrenia with a design that avoided the major confounds of feature integration and stimulus-response contingency learning. Sixteen patients diagnosed with schizophrenia and sixteen healthy, matched controls performed a vocal Stroop task to determine the congruency sequence effect - a marker of conflict adaptation. A reliable congruency sequence effect was observed for both healthy controls and patients diagnosed with schizophrenia. These findings indicate that schizophrenia is not necessarily accompanied by impaired conflict adaptation. As schizophrenia has been related to abnormal functioning in core conflict adaptation areas such as anterior cingulate and dorsolateral prefrontal cortex, further research is required to better understand the precise impact of such abnormal brain functioning at the behavioral level. Copyright © 2017 Elsevier B.V. All rights reserved.

Delivering organisational adaptation through legislative mechanisms: Evidence from the Adaptation Reporting Power (Climate Change Act 2008).

PubMed

Jude, S R; Drew, G H; Pollard, S J T; Rocks, S A; Jenkinson, K; Lamb, R

2017-01-01

There is increasing recognition that organisations, particularly in key infrastructure sectors, are potentially vulnerable to climate change and extreme weather events, and require organisational responses to ensure they are resilient and adaptive. However, detailed evidence of how adaptation is facilitated, implemented and reported, particularly through legislative mechanisms is lacking. The United Kingdom Climate Change Act (2008), introduced the Adaptation Reporting Power, enabling the Government to direct so-called reporting authorities to report their climate change risks and adaptation plans. We describe the authors' unique role and experience supporting the Department for Environment, Food and Rural Affairs (Defra) during the Adaptation Reporting Power's first round. An evaluation framework, used to review the adaptation reports, is presented alongside evidence on how the process provides new insights into adaptation activities and triggered organisational change in 78% of reporting authorities, including the embedding of climate risk and adaptation issues. The role of legislative mechanisms and risk-based approaches in driving and delivering adaptation is discussed alongside future research needs, including the development of organisational maturity models to determine resilient and well adapting organisations. The Adaptation Reporting Power process provides a basis for similar initiatives in other countries, although a clear engagement strategy to ensure buy-in to the process and research on its long-term legacy, including the potential merits of voluntary approaches, is required. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Study on feasibility of laser reflective tomography with satellite-accompany

NASA Astrophysics Data System (ADS)

Gu, Yu; Hu, Yi-hua; Hao, Shi-qi; Gu, You-lin; Zhao, Nan-xiang; Wang, Yang-yang

2015-10-01

Laser reflective tomography is a long-range, high-resolution active detection technology, whose advantage is that the spatial resolution is unrelated with the imaging distance. Accompany satellite is a specific satellite around the target spacecraft with encircling movement. When using the accompany satellite to detect the target aircraft, multi-angle echo data can be obtained with the application of reflective tomography imaging. The feasibility of such detection working mode was studied in this article. Accompany orbit model was established with horizontal circular fleet and the parameters of accompany flight was defined. The simulation of satellite-to-satellite reflective tomography imaging with satellite-accompany was carried out. The operating mode of reflective tomographic data acquisition from monostatic laser radar was discussed and designed. The flight period, which equals to the all direction received data consuming time, is one of the important accompany flight parameters. The azimuth angle determines the plane of image formation while the elevation angle determines the projection direction. Both of the azimuth and elevation angles guide the satellite attitude stability controller in order to point the laser radar spot on the target. The influences of distance between accompany satellite and target satellite on tomographic imaging consuming time was analyzed. The influences of flight period, azimuth angle and elevation angle on tomographic imaging were analyzed as well. Simulation results showed that the satellite-accompany laser reflective tomography is a feasible and effective method to the satellite-to-satellite detection.

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.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

PubMed

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Cognitive penetrability and emotion recognition in human facial expressions

PubMed Central

Marchi, Francesco

2015-01-01

Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration (CP) of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on CP, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept CP in some cases of emotion recognition. Finally, we discuss a recently proposed mechanism for CP in the face-based recognition of emotion. PMID:26150796

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

PubMed Central

Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

2016-01-01

Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

Early effects of duloxetine on emotion recognition in healthy volunteers

PubMed Central

Bamford, Susan; Penton-Voak, Ian; Pinkney, Verity; Baldwin, David S; Munafò, Marcus R; Garner, Matthew

2015-01-01

The serotonin-noradrenaline reuptake inhibitor (SNRI) duloxetine is an effective treatment for major depression and generalised anxiety disorder. Neuropsychological models of antidepressant drug action suggest therapeutic effects might be mediated by the early correction of maladaptive biases in emotion processing, including the recognition of emotional expressions. Sub-chronic administration of duloxetine (for two weeks) produces adaptive changes in neural circuitry implicated in emotion processing; however, its effects on emotional expression recognition are unknown. Forty healthy participants were randomised to receive either 14 days of duloxetine (60 mg/day, titrated from 30 mg after three days) or matched placebo (with sham titration) in a double-blind, between-groups, repeated-measures design. On day 0 and day 14 participants completed a computerised emotional expression recognition task that measured sensitivity to the six primary emotions. Thirty-eight participants (19 per group) completed their course of tablets and were included in the analysis. Results provide evidence that duloxetine, compared to placebo, may reduce the accurate recognition of sadness. Drug effects were driven by changes in participants’ ability to correctly detect subtle expressions of sadness, with greater change observed in the placebo relative to the duloxetine group. These effects occurred in the absence of changes in mood. Our preliminary findings require replication, but complement recent evidence that sadness recognition is a therapeutic target in major depression, and a mechanism through which SNRIs could resolve negative biases in emotion processing to achieve therapeutic effects. PMID:25759400

Who accompanies children to a dental hospital appointment?

PubMed

Virdee, P K; Rodd, H D

2007-06-01

To determine who accompanies paediatric dental patients to their appointments, in a teaching hospital setting. Data were recorded prospectively for children attending the Paediatric Dentistry clinic of the Charles Clifford Dental Hospital, Sheffield, England, over 4 months which included two school holiday periods. The data were recorded on a standardised data collection sheet, which included age and gender of the patient; number/s of accompanying adults and children and their relationship to the patient; the appointment session and appointment type. A total of 394 paediatric dental visits were recorded. Patients were of a mean age of 10 (range 1-17 years). Most visits were for treatment (44.7%) and review (39.8%), with a much smaller proportion being new patient assessments (8.9%) and emergency appointments (6.6%). The numbers of afternoon and morning sessions recorded were approximately similar and 35% of the visits were recorded in a school holiday day. The majority of patients attended with at least one parent (91.6%). A parent was most likely to attend a new patient assessment (97.1%) or review visit (94.3%). Parental presence was less likely for treatment (89%) and least likely for emergency visits (84%). Most patients attended with their mother (62.1%). Patients were less frequently accompanied by parents (13.1%), their father (12.1%) and one or both grandparents (4.3%). Smaller proportions were accompanied by older siblings, a step parent, other relatives or foster carers. Two patients attended unaccompanied. The time of day, or whether it was a school holiday period or not, did not influence parental presence or the numbers of adults accompanying patients. However the additional presence of other children (non patients) was more likely on morning sessions and during school holidays. One way analysis of variance (ANOVA), an independent sample t-test or chi-squared tests were undertaken as appropriate to determine whether there were any significant

Increased deficits in emotion recognition and regulation in children and adolescents with exogenous obesity.

PubMed

Percinel, Ipek; Ozbaran, Burcu; Kose, Sezen; Simsek, Damla Goksen; Darcan, Sukran

2018-03-01

In this study we aimed to evaluate emotion recognition and emotion regulation skills of children with exogenous obesity between the ages of 11 and 18 years and compare them with healthy controls. The Schedule for Affective Disorders and Schizophrenia for School Aged Children was used for psychiatric evaluations. Emotion recognition skills were evaluated using Faces Test and Reading the Mind in the Eyes Test. The Difficulties in Emotions Regulation Scale was used for evaluating skills of emotion regulation. Children with obesity had lower scores on Faces Test and Reading the Mind in the Eyes Test, and experienced greater difficulty in emotional regulation skills. Improved understanding of emotional recognition and emotion regulation in young people with obesity may improve their social adaptation and help in the treatment of their disorder. To the best of our knowledge, this is the first study to evaluate both emotional recognition and emotion regulation functions in obese children and obese adolescents between 11 and 18 years of age.

Semantic Network Adaptation Based on QoS Pattern Recognition for Multimedia Streams

NASA Astrophysics Data System (ADS)

Exposito, Ernesto; Gineste, Mathieu; Lamolle, Myriam; Gomez, Jorge

This article proposes an ontology based pattern recognition methodology to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams. The use of this ontology by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet self-optimization of communication services regarding the actual application requirements. A case study showing how this methodology is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach.

Building social-ecological resilience through adaptive comanagement in the Cache River Watershed of southern Illinois

Treesearch

Kofi Akamani

2014-01-01

There is growing recognition that the sustainable governance of water resources requires building social-ecological resilience against future surprises. Adaptive comanagement, a distinct institutional mechanism that combines the learning focus of adaptive management with the multilevel linkages of comanagement, has recently emerged as a promising mechanism for building...

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

Deep learning architecture for recognition of abnormal activities

NASA Astrophysics Data System (ADS)

Khatrouch, Marwa; Gnouma, Mariem; Ejbali, Ridha; Zaied, Mourad

2018-04-01

The video surveillance is one of the key areas in computer vision researches. The scientific challenge in this field involves the implementation of automatic systems to obtain detailed information about individuals and groups behaviors. In particular, the detection of abnormal movements of groups or individuals requires a fine analysis of frames in the video stream. In this article, we propose a new method to detect anomalies in crowded scenes. We try to categorize the video in a supervised mode accompanied by unsupervised learning using the principle of the autoencoder. In order to construct an informative concept for the recognition of these behaviors, we use a technique of representation based on the superposition of human silhouettes. The evaluation of the UMN dataset demonstrates the effectiveness of the proposed approach.

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

PubMed

Erb, Julia; Ludwig, Alexandra Annemarie; Kunke, Dunja; Fuchs, Michael; Obleser, Jonas

2018-04-24

Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

PubMed

Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Effects of Repetition Priming on Recognition Memory: Testing a Perceptual Fluency-Disfluency Model

ERIC Educational Resources Information Center

Huber, David E.; Clark, Tedra F.; Curran, Tim; Winkielman, Piotr

2008-01-01

Five experiments explored the effects of immediate repetition priming on episodic recognition (the "Jacoby-Whitehouse effect") as measured with forced-choice testing. These experiments confirmed key predictions of a model adapted from D. E. Huber and R. C. O'Reilly's (2003) dynamic neural network of perception. In this model, short prime durations…

Recognition of speaker-dependent continuous speech with KEAL

NASA Astrophysics Data System (ADS)

Mercier, G.; Bigorgne, D.; Miclet, L.; Le Guennec, L.; Querre, M.

1989-04-01

A description of the speaker-dependent continuous speech recognition system KEAL is given. An unknown utterance, is recognized by means of the followng procedures: acoustic analysis, phonetic segmentation and identification, word and sentence analysis. The combination of feature-based, speaker-independent coarse phonetic segmentation with speaker-dependent statistical classification techniques is one of the main design features of the acoustic-phonetic decoder. The lexical access component is essentially based on a statistical dynamic programming technique which aims at matching a phonemic lexical entry containing various phonological forms, against a phonetic lattice. Sentence recognition is achieved by use of a context-free grammar and a parsing algorithm derived from Earley's parser. A speaker adaptation module allows some of the system parameters to be adjusted by matching known utterances with their acoustical representation. The task to be performed, described by its vocabulary and its grammar, is given as a parameter of the system. Continuously spoken sentences extracted from a 'pseudo-Logo' language are analyzed and results are presented.

Music, memory, and Alzheimer's disease: is music recognition spared in dementia, and how can it be assessed?

PubMed

Cuddy, Lola L; Duffin, Jacalyn

2005-01-01

Despite intriguing and suggestive clinical observations, no formal research has assessed the possible sparing of musical recognition and memory in Alzheimer's dementia (AD). A case study is presented of an 84-year old woman with severe cognitive impairment implicating AD, but for whom music recognition and memory, according to her caregivers, appeared to be spared. The hypotheses addressed were, first, that memory for familiar music may be spared in dementia, and second, that musical recognition and memory may be reliably assessed with existing tests if behavioral observation is employed to overcome the problem of verbal or written communication. Our hypotheses were stimulated by the patient EN, for whom diagnosis of AD became probable in 2000. With severe problems in memory, language, and cognition, she now has a mini-mental status score of 8 (out of 30) and is unable to understand or recall standard instructions. In order to assess her music recognition abilities, three tests from the previous literature were adapted for behavioral observation. Two tests involved the discrimination of familiar melodies from unfamiliar melodies. The third involved the detection of distortions ("wrong" notes) in familiar melodies and discrimination of distorted melodies from melodies correctly reproduced. Test melodies were presented to EN on a CD player and her responses were observed by two test administrators. EN responded to familiar melodies by singing along, usually with the words, and often continuing to sing after the stimulus had stopped. She never responded to the unfamiliar melodies. She responded to distorted melodies with facial expressions - surprise, laughter, a frown, or an exclamation, "Oh, dear!"; she never responded in this way to the undistorted melodies. Allowing these responses as indicators of detection, the results for EN were in the normal or near normal range of scores for elderly controls. As well, lyrics to familiar melodies, spoken in a conversational

Superior voice recognition in a patient with acquired prosopagnosia and object agnosia.

PubMed

Hoover, Adria E N; Démonet, Jean-François; Steeves, Jennifer K E

2010-11-01

Anecdotally, it has been reported that individuals with acquired prosopagnosia compensate for their inability to recognize faces by using other person identity cues such as hair, gait or the voice. Are they therefore superior at the use of non-face cues, specifically voices, to person identity? Here, we empirically measure person and object identity recognition in a patient with acquired prosopagnosia and object agnosia. We quantify person identity (face and voice) and object identity (car and horn) recognition for visual, auditory, and bimodal (visual and auditory) stimuli. The patient is unable to recognize faces or cars, consistent with his prosopagnosia and object agnosia, respectively. He is perfectly able to recognize people's voices and car horns and bimodal stimuli. These data show a reverse shift in the typical weighting of visual over auditory information for audiovisual stimuli in a compromised visual recognition system. Moreover, the patient shows selectively superior voice recognition compared to the controls revealing that two different stimulus domains, persons and objects, may not be equally affected by sensory adaptation effects. This also implies that person and object identity recognition are processed in separate pathways. These data demonstrate that an individual with acquired prosopagnosia and object agnosia can compensate for the visual impairment and become quite skilled at using spared aspects of sensory processing. In the case of acquired prosopagnosia it is advantageous to develop a superior use of voices for person identity recognition in everyday life. Copyright © 2010 Elsevier Ltd. All rights reserved.

Design and test of a hybrid foot force sensing and GPS system for richer user mobility activity recognition.

PubMed

Zhang, Zelun; Poslad, Stefan

2013-11-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals.

Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition

PubMed Central

Zhang, Zelun; Poslad, Stefan

2013-01-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals. PMID:24189333

Pigmentary glaucoma accompanied by Usher syndrome.

PubMed

Koucheki, Behrooz; Jalali, Kamran Hodjat

2012-08-01

To report a case of pigmentary glaucoma (PG) accompanied by Usher syndrome. Case report. The results were presented after standard ocular examination, visual field test, anterior segment and fundus photography, electroretinography, and otolaryngology consultation were conducted. Typical retinitis pigmentosa, flat electroretinography, congenital sensorineural hearing loss, high intraocular pressure, Krukenberg spindle, iris concavity, radial iris transillumination defect, severe pigment deposition on the trabecular meshwork, and glaucomatous optic nerve damage were indicative of PG accompanied by Usher syndrome. In some rare cases, PG may coexist with Usher syndrome. Common findings of Usher syndrome, including night blindness, impaired vision, visual field defects, and retinal changes may distract the clinician from considering the diagnosis of glaucoma. Such association should be borne in mind to make a timely diagnosis and treatment possible.

On the Time Course of Vocal Emotion Recognition

PubMed Central

Pell, Marc D.; Kotz, Sonja A.

2011-01-01

How quickly do listeners recognize emotions from a speaker's voice, and does the time course for recognition vary by emotion type? To address these questions, we adapted the auditory gating paradigm to estimate how much vocal information is needed for listeners to categorize five basic emotions (anger, disgust, fear, sadness, happiness) and neutral utterances produced by male and female speakers of English. Semantically-anomalous pseudo-utterances (e.g., The rivix jolled the silling) conveying each emotion were divided into seven gate intervals according to the number of syllables that listeners heard from sentence onset. Participants (n = 48) judged the emotional meaning of stimuli presented at each gate duration interval, in a successive, blocked presentation format. Analyses looked at how recognition of each emotion evolves as an utterance unfolds and estimated the “identification point” for each emotion. Results showed that anger, sadness, fear, and neutral expressions are recognized more accurately at short gate intervals than happiness, and particularly disgust; however, as speech unfolds, recognition of happiness improves significantly towards the end of the utterance (and fear is recognized more accurately than other emotions). When the gate associated with the emotion identification point of each stimulus was calculated, data indicated that fear (M = 517 ms), sadness (M = 576 ms), and neutral (M = 510 ms) expressions were identified from shorter acoustic events than the other emotions. These data reveal differences in the underlying time course for conscious recognition of basic emotions from vocal expressions, which should be accounted for in studies of emotional speech processing. PMID:22087275

[The effect of the serotonin transporter 5-HTTLPR polymorphism on the recognition of facial emotions in schizophrenia].

PubMed

Alfimova, M V; Golimbet, V E; Korovaitseva, G I; Lezheiko, T V; Abramova, L I; Aksenova, E V; Bolgov, M I

2014-01-01

The 5-HTTLPR SLC6A4 and catechol-o-methyltransferase (COMT) Val158Met polymorphisms are reported to be associated with processing of facial expressions in general population. Impaired recognition of facial expressions that is characteristic of schizophrenia negatively impacts on the social adaptation of the patients. To search for molecular mechanisms of this deficit, we studied main and epistatic effects of 5-HTTLPR and Val158Met polymorphisms on the facial emotion recognition in patients with schizophrenia (n=299) and healthy controls (n=232). The 5-HTTLPR polymorphism was associated with the emotion recognition in patients. The ll-homozygotes recognized facial emotions significantly better compared to those with an s-allele (F=8.00; p=0.005). Although the recognition of facial emotions was correlated with negative symptoms, verbal learning and trait anxiety, these variables did not significantly modified the association. In both groups, no effect of the COMT on the recognition of facial emotions was found.

Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

ERIC Educational Resources Information Center

Harris, Richard W.; And Others

1988-01-01

A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition

NASA Astrophysics Data System (ADS)

Luqman, Muhammad Muzzamil; Delalandre, Mathieu; Brouard, Thierry; Ramel, Jean-Yves; Lladós, Josep

The motivation behind our work is to present a new methodology for symbol recognition. The proposed method employs a structural approach for representing visual associations in symbols and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical information by an attributed relational graph and compute a signature from this structural graph. We have addressed the sensitivity of structural representations to noise, by using data adapted fuzzy intervals. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set. The Bayesian network is deployed in a supervised learning scenario for recognizing query symbols. The method has been evaluated for robustness against degradations & deformations on pre-segmented 2D linear architectural & electronic symbols from GREC databases, and for its recognition abilities on symbols with context noise i.e. cropped symbols.

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2014 CFR

2014-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2011 CFR

2011-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2013 CFR

2013-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2012 CFR

2012-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2010 CFR

2010-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

Adaptive gamma correction-based expert system for nonuniform illumination face enhancement

NASA Astrophysics Data System (ADS)

Abdelhamid, Iratni; Mustapha, Aouache; Adel, Oulefki

2018-03-01

The image quality of a face recognition system suffers under severe lighting conditions. Thus, this study aims to develop an approach for nonuniform illumination adjustment based on an adaptive gamma correction (AdaptGC) filter that can solve the aforementioned issue. An approach for adaptive gain factor prediction was developed via neural network model-based cross-validation (NN-CV). To achieve this objective, a gamma correction function and its effects on the face image quality with different gain values were examined first. Second, an orientation histogram (OH) algorithm was assessed as a face's feature descriptor. Subsequently, a density histogram module was developed for face label generation. During the NN-CV construction, the model was assessed to recognize the OH descriptor and predict the face label. The performance of the NN-CV model was evaluated by examining the statistical measures of root mean square error and coefficient of efficiency. Third, to evaluate the AdaptGC enhancement approach, an image quality metric was adopted using enhancement by entropy, contrast per pixel, second-derivative-like measure of enhancement, and sharpness, then supported by visual inspection. The experiment results were examined using five face's databases, namely, extended Yale-B, Carnegie Mellon University-Pose, Illumination, and Expression, Mobio, FERET, and Oulu-CASIA-NIR-VIS. The final results prove that AdaptGC filter implementation compared with state-of-the-art methods is the best choice in terms of contrast and nonuniform illumination adjustment. In summary, the benefits attained prove that AdaptGC is driven by a profitable enhancement rate, which provides satisfying features for high rate face recognition systems.

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

PubMed

Katić, Darko; Julliard, Chantal; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie; Jannin, Pierre; Gibaud, Bernard

2015-09-01

The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data

BDNF Expression in Perirhinal Cortex is Associated with Exercise-Induced Improvement in Object Recognition Memory

PubMed Central

Hopkins, Michael E.; Bucci, David J.

2010-01-01

Physical exercise induces widespread neurobiological adaptations and improves learning and memory. Most research in this field has focused on hippocampus-based spatial tasks and changes in brain-derived neurotrophic factor (BDNF) as a putative substrate underlying exercise-induced cognitive improvements. Chronic exercise can also be anxiolytic and causes adaptive changes in stress reactivity. The present study employed a perirhinal cortex-dependent object recognition task as well as the elevated plus maze to directly test for interactions between the cognitive and anxiolytic effects of exercise in male Long Evans rats. Hippocampal and perirhinal cortex tissue was collected to determine whether the relationship between BDNF and cognitive performance extends to this non-spatial and non-hippocampal-dependent task. We also examined whether the cognitive improvements persisted once the exercise regimen was terminated. Our data indicate that 4 weeks of voluntary exercise every-other-day improved object recognition memory. Importantly, BDNF expression in the perirhinal cortex of exercising rats was strongly correlated with object recognition memory. Exercise also decreased anxiety-like behavior, however there was no evidence to support a relationship between anxiety-like behavior and performance on the novel object recognition task. There was a trend for a negative relationship between anxiety-like behavior and hippocampal BDNF. Neither the cognitive improvements nor the relationship between cognitive function and perirhinal BDNF levels persisted after 2 weeks of inactivity. These are the first data demonstrating that region-specific changes in BDNF protein levels are correlated with exercise-induced improvements in non-spatial memory, mediated by structures outside the hippocampus and are consistent with the theory that, with regard to object recognition, the anxiolytic and cognitive effects of exercise may be mediated through separable mechanisms. PMID:20601027

Critical thinking of student nurses during clinical accompaniment.

PubMed

Uys, B Y; Meyer, S M

2005-08-01

The purpose of this study was to investigate the methods of clinical accompaniment used by clinical facilitators in practice. The findings of the study also reflected facilitators' perceptions regarding critical thinking and the facilitation thereof. A quantitative research design was used. A literature study was conducted to identify the methods of accompaniment that facilitate critical thinking. Data was collected by means of a questionnaire developed for that purpose. Making a content-related validity judgment, and involving seven clinical facilitators in an academic institution, ensured the validity of the questionnaire. The results of the study indicated that various clinical methods of accompaniment were used. To a large extent, these methods correlated with those discussed in the literature review. The researcher further concluded that the concepts 'critical thinking' and 'facilitation' were not interpreted correctly by the respondents, and would therefore not be implemented in a proper manner in nursing practice. Furthermore, it seemed evident that tutor-driven learning realised more often than student-driven learning. In this regard, the requirement of outcomes-based education was not satisfied. The researcher is therefore of the opinion that a practical programme for the development of critical thinking skills during clinical accompaniment must be developed within the framework of outcomes-based education.

Detecting facial emotion recognition deficits in schizophrenia using dynamic stimuli of varying intensities.

PubMed

Hargreaves, A; Mothersill, O; Anderson, M; Lawless, S; Corvin, A; Donohoe, G

2016-10-28

Deficits in facial emotion recognition have been associated with functional impairments in patients with Schizophrenia (SZ). Whilst a strong ecological argument has been made for the use of both dynamic facial expressions and varied emotion intensities in research, SZ emotion recognition studies to date have primarily used static stimuli of a singular, 100%, intensity of emotion. To address this issue, the present study aimed to investigate accuracy of emotion recognition amongst patients with SZ and healthy subjects using dynamic facial emotion stimuli of varying intensities. To this end an emotion recognition task (ERT) designed by Montagne (2007) was adapted and employed. 47 patients with a DSM-IV diagnosis of SZ and 51 healthy participants were assessed for emotion recognition. Results of the ERT were tested for correlation with performance in areas of cognitive ability typically found to be impaired in psychosis, including IQ, memory, attention and social cognition. Patients were found to perform less well than healthy participants at recognising each of the 6 emotions analysed. Surprisingly, however, groups did not differ in terms of impact of emotion intensity on recognition accuracy; for both groups higher intensity levels predicted greater accuracy, but no significant interaction between diagnosis and emotional intensity was found for any of the 6 emotions. Accuracy of emotion recognition was, however, more strongly correlated with cognition in the patient cohort. Whilst this study demonstrates the feasibility of using ecologically valid dynamic stimuli in the study of emotion recognition accuracy, varying the intensity of the emotion displayed was not demonstrated to impact patients and healthy participants differentially, and thus may not be a necessary variable to include in emotion recognition research. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reduced adaptability, but no fundamental disruption, of norm-based face coding following early visual deprivation from congenital cataracts.

PubMed

Rhodes, Gillian; Nishimura, Mayu; de Heering, Adelaide; Jeffery, Linda; Maurer, Daphne

2017-05-01

Faces are adaptively coded relative to visual norms that are updated by experience, and this adaptive coding is linked to face recognition ability. Here we investigated whether adaptive coding of faces is disrupted in individuals (adolescents and adults) who experience face recognition difficulties following visual deprivation from congenital cataracts in infancy. We measured adaptive coding using face identity aftereffects, where smaller aftereffects indicate less adaptive updating of face-coding mechanisms by experience. We also examined whether the aftereffects increase with adaptor identity strength, consistent with norm-based coding of identity, as in typical populations, or whether they show a different pattern indicating some more fundamental disruption of face-coding mechanisms. Cataract-reversal patients showed significantly smaller face identity aftereffects than did controls (Experiments 1 and 2). However, their aftereffects increased significantly with adaptor strength, consistent with norm-based coding (Experiment 2). Thus we found reduced adaptability but no fundamental disruption of norm-based face-coding mechanisms in cataract-reversal patients. Our results suggest that early visual experience is important for the normal development of adaptive face-coding mechanisms. © 2016 John Wiley & Sons Ltd.

Impact of severity of drug use on discrete emotions recognition in polysubstance abusers.

PubMed

Fernández-Serrano, María José; Lozano, Oscar; Pérez-García, Miguel; Verdejo-García, Antonio

2010-06-01

Neuropsychological studies support the association between severity of drug intake and alterations in specific cognitive domains and neural systems, but there is disproportionately less research on the neuropsychology of emotional alterations associated with addiction. One of the key aspects of adaptive emotional functioning potentially relevant to addiction progression and treatment is the ability to recognize basic emotions in the faces of others. Therefore, the aims of this study were: (i) to examine facial emotion recognition in abstinent polysubstance abusers, and (ii) to explore the association between patterns of quantity and duration of use of several drugs co-abused (including alcohol, cannabis, cocaine, heroin and MDMA) and the ability to identify discrete facial emotional expressions portraying basic emotions. We compared accuracy of emotion recognition of facial expressions portraying six basic emotions (measured with the Ekman Faces Test) between polysubstance abusers (PSA, n=65) and non-drug using comparison individuals (NDCI, n=30), and used regression models to explore the association between quantity and duration of use of the different drugs co-abused and indices of recognition of each of the six emotions, while controlling for relevant socio-demographic and affect-related confounders. Results showed: (i) that PSA had significantly poorer recognition than NDCI for facial expressions of anger, disgust, fear and sadness; (ii) that measures of quantity and duration of drugs used significantly predicted poorer discrete emotions recognition: quantity of cocaine use predicted poorer anger recognition, and duration of cocaine use predicted both poorer anger and fear recognition. Severity of cocaine use also significantly predicted overall recognition accuracy. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Ocular myasthenia gravis accompanied by anosmia.

PubMed

Chen, Ying; Wang, Li; Zhou, Li; Gao, Ying

2016-02-01

We report a case of ocular myasthenia gravis (MG) accompanied by anosmia. A 76-year-old man had idiopathic anosmia of 2-year duration. Four months before consultation, he began to have drooping in the right upper eyelid along with muscle soreness, distension, and pain in the nape. His tongue was dark-red with a thin and white coating; his pulse was wiry and slippery. According to Traditional Chinese Medicine, eyelid drooping and anosmia are the main signs of liver constraint and spleen deficiency. In Western Medicine, the diagnosis was ocular MG and idiopathic anosmia. Our patient, along with the literature, suggests that anosmia may be an early symptom before MG. MG accompanied by anosmia could be a special subtype of MG according to antibody production and symptoms.

Recognition of flow in everyday life using sensor agent robot with laser range finder

NASA Astrophysics Data System (ADS)

Goshima, Misa; Mita, Akira

2011-04-01

In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

Genome and transcriptome adaptation accompanying emergence of the definitive type 2 host-restricted Salmonella enterica serovar Typhimurium pathovar.

PubMed

Kingsley, Robert A; Kay, Sally; Connor, Thomas; Barquist, Lars; Sait, Leanne; Holt, Kathryn E; Sivaraman, Karthi; Wileman, Thomas; Goulding, David; Clare, Simon; Hale, Christine; Seshasayee, Aswin; Harris, Simon; Thomson, Nicholas R; Gardner, Paul; Rabsch, Wolfgang; Wigley, Paul; Humphrey, Tom; Parkhill, Julian; Dougan, Gordon

2013-08-27

Salmonella enterica serovar Typhimurium definitive type 2 (DT2) is host restricted to Columba livia (rock or feral pigeon) but is also closely related to S. Typhimurium isolates that circulate in livestock and cause a zoonosis characterized by gastroenteritis in humans. DT2 isolates formed a distinct phylogenetic cluster within S. Typhimurium based on whole-genome-sequence polymorphisms. Comparative genome analysis of DT2 94-213 and S. Typhimurium SL1344, DT104, and D23580 identified few differences in gene content with the exception of variations within prophages. However, DT2 94-213 harbored 22 pseudogenes that were intact in other closely related S. Typhimurium strains. We report a novel in silico approach to identify single amino acid substitutions in proteins that have a high probability of a functional impact. One polymorphism identified using this method, a single-residue deletion in the Tar protein, abrogated chemotaxis to aspartate in vitro. DT2 94-213 also exhibited an altered transcriptional profile in response to culture at 42°C compared to that of SL1344. Such differentially regulated genes included a number involved in flagellum biosynthesis and motility. IMPORTANCE Whereas Salmonella enterica serovar Typhimurium can infect a wide range of animal species, some variants within this serovar exhibit a more limited host range and altered disease potential. Phylogenetic analysis based on whole-genome sequences can identify lineages associated with specific virulence traits, including host adaptation. This study represents one of the first to link pathogen-specific genetic signatures, including coding capacity, genome degradation, and transcriptional responses to host adaptation within a Salmonella serovar. We performed comparative genome analysis of reference and pigeon-adapted definitive type 2 (DT2) S. Typhimurium isolates alongside phenotypic and transcriptome analyses, to identify genetic signatures linked to host adaptation within the DT2 lineage.

Emotion recognition from speech: tools and challenges

NASA Astrophysics Data System (ADS)

Al-Talabani, Abdulbasit; Sellahewa, Harin; Jassim, Sabah A.

2015-05-01

Human emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more "natural" than the acted datasets where the subjects attempt to suppress all but one emotion.

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

PubMed Central

Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

2014-01-01

Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

9 CFR 93.314 - Horses, certification, and accompanying equipment.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., certification, and accompanying equipment. (a) Horses offered for importation from any part of the world shall... region of origin, or if exported from Mexico, shall be accompanied either by such a certificate or by a... were imported from regions affected with CEM. (b) If a horse is presented for importation from a region...

Automatic voice recognition using traditional and artificial neural network approaches

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1989-01-01

The main objective of this research is to develop an algorithm for isolated-word recognition. This research is focused on digital signal analysis rather than linguistic analysis of speech. Features extraction is carried out by applying a Linear Predictive Coding (LPC) algorithm with order of 10. Continuous-word and speaker independent recognition will be considered in future study after accomplishing this isolated word research. To examine the similarity between the reference and the training sets, two approaches are explored. The first is implementing traditional pattern recognition techniques where a dynamic time warping algorithm is applied to align the two sets and calculate the probability of matching by measuring the Euclidean distance between the two sets. The second is implementing a backpropagation artificial neural net model with three layers as the pattern classifier. The adaptation rule implemented in this network is the generalized least mean square (LMS) rule. The first approach has been accomplished. A vocabulary of 50 words was selected and tested. The accuracy of the algorithm was found to be around 85 percent. The second approach is in progress at the present time.

Metastatic Basal cell carcinoma accompanying gorlin syndrome.

PubMed

Bilir, Yeliz; Gokce, Erkan; Ozturk, Banu; Deresoy, Faik Alev; Yuksekkaya, Ruken; Yaman, Emel

2014-01-01

Gorlin-Goltz syndrome or basal cell nevus syndrome is an autosomal dominant syndrome characterized by skeletal anomalies, numerous cysts observed in the jaw, and multiple basal cell carcinoma of the skin, which may be accompanied by falx cerebri calcification. Basal cell carcinoma is the most commonly skin tumor with slow clinical course and low metastatic potential. Its concomitance with Gorlin syndrome, resulting from a mutation in a tumor suppressor gene, may substantially change morbidity and mortality. A 66-year-old male patient with a history of recurrent basal cell carcinoma was presented with exophthalmus in the left eye and the lesions localized in the left lateral orbita and left zygomatic area. His physical examination revealed hearing loss, gapped teeth, highly arched palate, and frontal prominence. Left orbital mass, cystic masses at frontal and ethmoidal sinuses, and multiple pulmonary nodules were detected at CT scans. Basal cell carcinoma was diagnosed from biopsy of ethmoid sinus. Based on the clinical and typical radiological characteristics (falx cerebri calcification, bifid costa, and odontogenic cysts), the patient was diagnosed with metastatic skin basal cell carcinoma accompanied by Gorlin syndrome. Our case is a basal cell carcinoma with aggressive course accompanying a rarely seen syndrome.

Adaptive evolution of baker's yeast in a dough‐like environment enhances freeze and salinity tolerance

PubMed Central

Aguilera, Jaime; Andreu, Pasqual; Randez‐Gil, Francisca; Prieto, Jose Antonio

2010-01-01

Summary We used adaptive evolution to improve freeze tolerance of industrial baker's yeast. Our hypothesis was that adaptation to low temperature is accompanied by enhanced resistance of yeast to freezing. Based on this hypothesis, yeast was propagated in a flour‐free liquid dough model system, which contained sorbitol and NaCl, by successive batch refreshments maintained constantly at 12°C over at least 200 generations. Relative to the parental population, the maximal growth rate (µmax) under the restrictive conditions, increased gradually over the time course of the experiment. This increase was accompanied by enhanced freeze tolerance. However, these changes were not the consequence of genetic adaptation to low temperature, a fact that was confirmed by prolonged selection of yeast cells in YPD at 12°C. Instead, the experimental populations showed a progressive increase in NaCl tolerance. This phenotype was likely achieved at the expense of others traits, since evolved cells showed a ploidy reduction, a defect in the glucose derepression mechanism and a loss in their ability to utilize gluconeogenic carbon sources. We discuss the genetic flexibility of S. cerevisiae in terms of adaptation to the multiple constraints of the experimental design applied to drive adaptive evolution and the technologically advantageous phenotype of the evolved population. PMID:21255321

Learning and recognition of on-premise signs from weakly labeled street view images.

PubMed

Tsai, Tsung-Hung; Cheng, Wen-Huang; You, Chuang-Wen; Hu, Min-Chun; Tsui, Arvin Wen; Chi, Heng-Yu

2014-03-01

Camera-enabled mobile devices are commonly used as interaction platforms for linking the user's virtual and physical worlds in numerous research and commercial applications, such as serving an augmented reality interface for mobile information retrieval. The various application scenarios give rise to a key technique of daily life visual object recognition. On-premise signs (OPSs), a popular form of commercial advertising, are widely used in our living life. The OPSs often exhibit great visual diversity (e.g., appearing in arbitrary size), accompanied with complex environmental conditions (e.g., foreground and background clutter). Observing that such real-world characteristics are lacking in most of the existing image data sets, in this paper, we first proposed an OPS data set, namely OPS-62, in which totally 4649 OPS images of 62 different businesses are collected from Google's Street View. Further, for addressing the problem of real-world OPS learning and recognition, we developed a probabilistic framework based on the distributional clustering, in which we proposed to exploit the distributional information of each visual feature (the distribution of its associated OPS labels) as a reliable selection criterion for building discriminative OPS models. Experiments on the OPS-62 data set demonstrated the outperformance of our approach over the state-of-the-art probabilistic latent semantic analysis models for more accurate recognitions and less false alarms, with a significant 151.28% relative improvement in the average recognition rate. Meanwhile, our approach is simple, linear, and can be executed in a parallel fashion, making it practical and scalable for large-scale multimedia applications.

Processing F0 with cochlear implants: Modulation frequency discrimination and speech intonation recognition.

PubMed

Chatterjee, Monita; Peng, Shu-Chen

2008-01-01

Fundamental frequency (F0) processing by cochlear implant (CI) listeners was measured using a psychophysical task and a speech intonation recognition task. Listeners' Weber fractions for modulation frequency discrimination were measured using an adaptive, 3-interval, forced-choice paradigm: stimuli were presented through a custom research interface. In the speech intonation recognition task, listeners were asked to indicate whether resynthesized bisyllabic words, when presented in the free field through the listeners' everyday speech processor, were question-like or statement-like. The resynthesized tokens were systematically manipulated to have different initial-F0s to represent male vs. female voices, and different F0 contours (i.e. falling, flat, and rising) Although the CI listeners showed considerable variation in performance on both tasks, significant correlations were observed between the CI listeners' sensitivity to modulation frequency in the psychophysical task and their performance in intonation recognition. Consistent with their greater reliance on temporal cues, the CI listeners' performance in the intonation recognition task was significantly poorer with the higher initial-F0 stimuli than with the lower initial-F0 stimuli. Similar results were obtained with normal hearing listeners attending to noiseband-vocoded CI simulations with reduced spectral resolution.

Processing F0 with Cochlear Implants: Modulation Frequency Discrimination and Speech Intonation Recognition

PubMed Central

Chatterjee, Monita; Peng, Shu-Chen

2008-01-01

Fundamental frequency (F0) processing by cochlear implant (CI) listeners was measured using a psychophysical task and a speech intonation recognition task. Listeners’ Weber fractions for modulation frequency discrimination were measured using an adaptive, 3-interval, forced-choice paradigm: stimuli were presented through a custom research interface. In the speech intonation recognition task, listeners were asked to indicate whether resynthesized bisyllabic words, when presented in the free field through the listeners’ everyday speech processor, were question-like or statement-like. The resynthesized tokens were systematically manipulated to have different initial F0s to represent male vs. female voices, and different F0 contours (i.e., falling, flat, and rising) Although the CI listeners showed considerable variation in performance on both tasks, significant correlations were observed between the CI listeners’ sensitivity to modulation frequency in the psychophysical task and their performance in intonation recognition. Consistent with their greater reliance on temporal cues, the CI listeners’ performance in the intonation recognition task was significantly poorer with the higher initial-F0 stimuli than with the lower initial-F0 stimuli. Similar results were obtained with normal hearing listeners attending to noiseband-vocoded CI simulations with reduced spectral resolution. PMID:18093766

Enhanced iris recognition method based on multi-unit iris images

NASA Astrophysics Data System (ADS)

Shin, Kwang Yong; Kim, Yeong Gon; Park, Kang Ryoung

2013-04-01

For the purpose of biometric person identification, iris recognition uses the unique characteristics of the patterns of the iris; that is, the eye region between the pupil and the sclera. When obtaining an iris image, the iris's image is frequently rotated because of the user's head roll toward the left or right shoulder. As the rotation of the iris image leads to circular shifting of the iris features, the accuracy of iris recognition is degraded. To solve this problem, conventional iris recognition methods use shifting of the iris feature codes to perform the matching. However, this increases the computational complexity and level of false acceptance error. To solve these problems, we propose a novel iris recognition method based on multi-unit iris images. Our method is novel in the following five ways compared with previous methods. First, to detect both eyes, we use Adaboost and a rapid eye detector (RED) based on the iris shape feature and integral imaging. Both eyes are detected using RED in the approximate candidate region that consists of the binocular region, which is determined by the Adaboost detector. Second, we classify the detected eyes into the left and right eyes, because the iris patterns in the left and right eyes in the same person are different, and they are therefore considered as different classes. We can improve the accuracy of iris recognition using this pre-classification of the left and right eyes. Third, by measuring the angle of head roll using the two center positions of the left and right pupils, detected by two circular edge detectors, we obtain the information of the iris rotation angle. Fourth, in order to reduce the error and processing time of iris recognition, adaptive bit-shifting based on the measured iris rotation angle is used in feature matching. Fifth, the recognition accuracy is enhanced by the score fusion of the left and right irises. Experimental results on the iris open database of low-resolution images showed that the

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

Adaptation of Instructional Materials for Use with Mainstreamed Students. Final Report.

ERIC Educational Resources Information Center

Macro Systems, Inc., Silver Spring, MD.

The report documents a project to adapt and design instructional media and materials of a regular senior high social studies curriculum for use with mainstreamed mildly handicapped students. Supplementary materials were developed and tested at five sites to accompany the world history textbook, "Our Common Heritage." Products included the…

On the Susceptibility of Adaptive Memory to False Memory Illusions

ERIC Educational Resources Information Center

Howe, Mark L.; Derbish, Mary H.

2010-01-01

Previous research has shown that survival-related processing of word lists enhances retention for that material. However, the claim that survival-related memories are more accurate has only been examined when true recall and recognition of neutral material has been measured. In the current experiments, we examined the adaptive memory superiority…

The Impact of Foreign Postings on Accompanying Military Spouses: An Ethnographic Study

PubMed Central

Blakely, Gillian; Hennessy, Catherine; Chung, Man C.; Skirton, Heather

2014-01-01

As part of an ethnographic study, the impact of foreign postings on spouses who accompany military personnel was explored. Individual interviews and focus groups with 34 British military spouses based in one location in southern Europe were conducted. Key findings suggested that reaction to a foreign posting was a reflection of personal attitudes, prior experiences, support, ability to adjust to change and strength of relationship with the serving spouse and community. For many the experience was positive due to the increased opportunity for family time, for others this helped to compensate for the difficulties experienced. Some military spouses experienced significant distress on the posting, particularly if the family was not well-supported. The potential implications of military spouses not adapting to foreign postings have significant implications for healthcare practice. Provision of more appropriate support resources before and during the posting would facilitate the transition for the military spouse and their family. PMID:26973933

Gimli: open source and high-performance biomedical name recognition

PubMed Central

2013-01-01

Background Automatic recognition of biomedical names is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. In recent years, various solutions have been implemented to tackle this problem. However, limitations regarding system characteristics, customization and usability still hinder their wider application outside text mining research. Results We present Gimli, an open-source, state-of-the-art tool for automatic recognition of biomedical names. Gimli includes an extended set of implemented and user-selectable features, such as orthographic, morphological, linguistic-based, conjunctions and dictionary-based. A simple and fast method to combine different trained models is also provided. Gimli achieves an F-measure of 87.17% on GENETAG and 72.23% on JNLPBA corpus, significantly outperforming existing open-source solutions. Conclusions Gimli is an off-the-shelf, ready to use tool for named-entity recognition, providing trained and optimized models for recognition of biomedical entities from scientific text. It can be used as a command line tool, offering full functionality, including training of new models and customization of the feature set and model parameters through a configuration file. Advanced users can integrate Gimli in their text mining workflows through the provided library, and extend or adapt its functionalities. Based on the underlying system characteristics and functionality, both for final users and developers, and on the reported performance results, we believe that Gimli is a state-of-the-art solution for biomedical NER, contributing to faster and better research in the field. Gimli is freely available at http://bioinformatics.ua.pt/gimli. PMID:23413997

Modular Activating Receptors in Innate and Adaptive Immunity.

PubMed

Berry, Richard; Call, Matthew E

2017-03-14

Triggering of cell-mediated immunity is largely dependent on the recognition of foreign or abnormal molecules by a myriad of cell surface-bound receptors. Many activating immune receptors do not possess any intrinsic signaling capacity but instead form noncovalent complexes with one or more dimeric signaling modules that communicate with a common set of kinases to initiate intracellular information-transfer pathways. This modular architecture, where the ligand binding and signaling functions are detached from one another, is a common theme that is widely employed throughout the innate and adaptive arms of immune systems. The evolutionary advantages of this highly adaptable platform for molecular recognition are visible in the variety of ligand-receptor interactions that can be linked to common signaling pathways, the diversification of receptor modules in response to pathogen challenges, and the amplification of cellular responses through incorporation of multiple signaling motifs. Here we provide an overview of the major classes of modular activating immune receptors and outline the current state of knowledge regarding how these receptors assemble, recognize their ligands, and ultimately trigger intracellular signal transduction pathways that activate immune cell effector functions.

Pollen Image Recognition Based on DGDB-LBP Descriptor

NASA Astrophysics Data System (ADS)

Han, L. P.; Xie, Y. H.

2018-01-01

In this paper, we propose DGDB-LBP, a local binary pattern descriptor based on the pixel blocks in the dominant gradient direction. Differing from traditional LBP and its variants, DGDB-LBP encodes by comparing the main gradient magnitude of each block rather than the single pixel value or the average of pixel blocks, in doing so, it reduces the influence of noise on pollen images and eliminates redundant and non-informative features. In order to fully describe the texture features of pollen images and analyze it under multi-scales, we propose a new sampling strategy, which uses three types of operators to extract the radial, angular and multiple texture features under different scales. Considering that the pollen images have some degree of rotation under the microscope, we propose the adaptive encoding direction, which is determined by the texture distribution of local region. Experimental results on the Pollenmonitor dataset show that the average correct recognition rate of our method is superior to other pollen recognition methods in recent years.

Adaptability of mitosporic stage in Sphaerodes mycoparasitica towards its mycoparasitic-polyphagous lifestyle.

PubMed

Vujanovic, Vladimir; Kim, Seon Hwa

2017-01-01

Sphaerodes mycoparasitica Vuj. is a Fusarium-specific mycoparasite. Some recent discoveries recognize its biotrophic polyphagous lifestyle as an interesting biocontrol property against a broad spectrum of mycotoxigenic Fusarium hosts. Secondary metabolites such as mycotoxins produced by Fusarium spp. may play an important role in the signaling process, allowing an early mycoparasite-host recognition. A multiple-paper-disc assay has been conducted to test S. mycoparasitica hyphal adaptability to filtrates of 12 Fusarium spp. This study shows that shifts of adapted and nonadapted hyphal migration towards different Fusarium-host filtrates may partly explain S. mycoparasitica polyphagous lifestyle, and its adaptability depending on host preference or compatibility. In terms of host compatibility, the current findings suggest that S. mycoparasitica tends to prefer native Fusarium hosts more related to its origin and propose that the mycoparasite could possess diphasic interactions such as biotrophic-attraction and antagonistic-inhibition relationships based on relative radial growth. This implies that the mycoparasite may use a group of mycotoxins produced by specific Fusarium spp. as an adaptive selective mechanism that facilitates a parasite-host recognition and further successful mycoparasitism. In particular, relative polarity or hydrophilicity/hydrophobicity of mycotoxins may be related to solubility and absorption properties in hyphae of the mycoparasite. Taken together, the studies of host compatibility and adaptability depending on host filtrates will aid in understanding complex mechanisms of S. mycoparasitica, as a promising model organism for a specific biotrophic mycoparasite to enhance and improve biocontrol efficacy against Fusaria.

A split recognition mode combined with cascade signal amplification strategy for highly specific, sensitive detection of microRNA.

PubMed

Wang, Rui; Wang, Lei; Zhao, Haiyan; Jiang, Wei

2016-12-15

MicroRNAs (miRNAs) are vital for many biological processes and have been regarded as cancer biomarkers. Specific and sensitive detection of miRNAs is essential for cancer diagnosis and therapy. Herein, a split recognition mode combined with cascade signal amplification strategy is developed for highly specific and sensitive detection of miRNA. The split recognition mode possesses two specific recognition processes, which are based on toehold-mediated strand displacement reaction (TSDR) and direct hybridization reaction. Two recognition probes, hairpin probe (HP) with overhanging toehold domain and assistant probe (AP), are specially designed. Firstly, the toehold domain of HP and AP recognize part of miRNA simultaneously, accompanied with TSDR to unfold the HP and form the stable DNA Y-shaped junction structure (YJS). Then, the AP in YJS can further act as primer to initiate strand displacement amplification, releasing numerous trigger sequences. Finally, the trigger sequences hybridize with padlock DNA to initiate circular rolling circle amplification and generate enhanced fluorescence responses. In this strategy, the dual recognition effect of split recognition mode guarantees the excellent selectivity to discriminate let-7b from high-homology sequences. Furthermore, the high amplification efficiency of cascade signal amplification guarantees a high sensitivity with the detection limit of 3.2 pM and the concentration of let-7b in total RNA sample extracted from Hela cells is determined. These results indicate our strategy will be a promising miRNA detection strategy in clinical diagnosis and disease treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents.

PubMed

Yu, Litao; Yang, Yang; Huang, Zi; Wang, Peng; Song, Jingkuan; Shen, Heng Tao

2016-12-01

In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyze video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of Web video event recognition, where Web videos often describe large-granular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from Web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous Web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model, which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video data sets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of Web video event recognition.

Rotation, scale, and translation invariant pattern recognition using feature extraction

NASA Astrophysics Data System (ADS)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine

PubMed Central

Luo, Guangchun; Qin, Ke; Wang, Nan; Niu, Weina

2018-01-01

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy. PMID:29494543

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine.

PubMed

Ma, Zhiyuan; Luo, Guangchun; Qin, Ke; Wang, Nan; Niu, Weina

2018-03-01

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy.

Adaptive virus detection using filament-coupled antibodies.

PubMed

Stone, Gregory P; Lin, Kelvin S; Haselton, Frederick R

2006-01-01

We recently reported the development of a filament-antibody recognition assay (FARA), in which the presence of virions in solution initiates the formation of enzyme-linked immunosorbent assay (ELISA)-like antibody complexes. The unique features of this assay are that processing is achieved by motion of a filament and that, in the presence of a virus, antibody-virus complexes are coupled to the filament at known locations. In this work, we combine the unique features of this assay with a 638-nm laser-based optical detector to enable adaptive control of virus detection. Integration of on-line fluorescence detection yields approximately a five-fold increase in signal-to-noise ratio (SNR) compared to the fluorescence detection method reported previously. A one-minute incubation with an M13K07 test virus is required to detect 10(10) virionsml, and 40 min was required to detect 10(8) virionsml. In tests of the components of an adaptive strategy, a 30-min virus (3.3 x 10(10) virionsml) incubation time, followed by repositioning the filament-captured virus either within the detecting antibody chamber, (20 microg ml) or within the virus chamber, found an increase in signal roughly proportional to the cumulative residence times in these chambers. Furthermore, cumulative fluorescence signals observed for a filament-captured virus after repeated positioning of the filament within the virus chamber are similar to those observed for a single long incubation time. The unique features of the FARA-like design combined with online optical detection to direct subsequent bioprocessing steps provides new flexibility for developing adaptive molecular recognition assays.

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

PubMed

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

1992-01-01

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

Metastatic Basal Cell Carcinoma Accompanying Gorlin Syndrome

PubMed Central

Bilir, Yeliz; Gokce, Erkan; Ozturk, Banu; Deresoy, Faik Alev; Yuksekkaya, Ruken; Yaman, Emel

2014-01-01

Gorlin-Goltz syndrome or basal cell nevus syndrome is an autosomal dominant syndrome characterized by skeletal anomalies, numerous cysts observed in the jaw, and multiple basal cell carcinoma of the skin, which may be accompanied by falx cerebri calcification. Basal cell carcinoma is the most commonly skin tumor with slow clinical course and low metastatic potential. Its concomitance with Gorlin syndrome, resulting from a mutation in a tumor suppressor gene, may substantially change morbidity and mortality. A 66-year-old male patient with a history of recurrent basal cell carcinoma was presented with exophthalmus in the left eye and the lesions localized in the left lateral orbita and left zygomatic area. His physical examination revealed hearing loss, gapped teeth, highly arched palate, and frontal prominence. Left orbital mass, cystic masses at frontal and ethmoidal sinuses, and multiple pulmonary nodules were detected at CT scans. Basal cell carcinoma was diagnosed from biopsy of ethmoid sinus. Based on the clinical and typical radiological characteristics (falx cerebri calcification, bifid costa, and odontogenic cysts), the patient was diagnosed with metastatic skin basal cell carcinoma accompanied by Gorlin syndrome. Our case is a basal cell carcinoma with aggressive course accompanying a rarely seen syndrome. PMID:25506011

Explicit and implicit processes in behavioural adaptation to road width.

PubMed

Lewis-Evans, Ben; Charlton, Samuel G

2006-05-01

The finding that drivers may react to safety interventions in a way that is contrary to what was intended is the phenomenon of behavioural adaptation. This phenomenon has been demonstrated across various safety interventions and has serious implications for road safety programs the world over. The present research used a driving simulator to assess behavioural adaptation in drivers' speed and lateral displacement in response to manipulations of road width. Of interest was whether behavioural adaptation would occur and whether we could determine whether it was the result of explicit, conscious decisions or implicit perceptual processes. The results supported an implicit, zero perceived risk model of behavioural adaptation with reduced speeds on a narrowed road accompanied by increased ratings of risk and a marked inability of the participants to identify that any change in road width had occurred.

Brain neuroplastic changes accompany anxiety and memory deficits in a model of complex regional pain syndrome.

PubMed

Tajerian, Maral; Leu, David; Zou, Yani; Sahbaie, Peyman; Li, Wenwu; Khan, Hamda; Hsu, Vivian; Kingery, Wade; Huang, Ting Ting; Becerra, Lino; Clark, J David

2014-10-01

Complex regional pain syndrome (CRPS) is a painful condition with approximately 50,000 annual new cases in the United States. It is a major cause of work-related disability, chronic pain after limb fractures, and persistent pain after extremity surgery. Additionally, CRPS patients often experience cognitive changes, anxiety, and depression. The supraspinal mechanisms linked to these CRPS-related comorbidities remain poorly understood. The authors used a previously characterized mouse model of tibia fracture/cast immobilization showing the principal stigmata of CRPS (n = 8 to 20 per group) observed in humans. The central hypothesis was that fracture/cast mice manifest changes in measures of thigmotaxis (indicative of anxiety) and working memory reflected in neuroplastic changes in amygdala, perirhinal cortex, and hippocampus. The authors demonstrate that nociceptive sensitization in these mice is accompanied by altered thigmotactic behaviors in the zero maze but not open field assay, and working memory dysfunction in novel object recognition and social memory but not in novel location recognition. Furthermore, the authors found evidence of structural changes and synaptic plasticity including changes in dendritic architecture and decreased levels of synaptophysin and brain-derived neurotrophic factor in specific brain regions. The study findings provide novel observations regarding behavioral changes and brain plasticity in a mouse model of CRPS. In addition to elucidating some of the supraspinal correlates of the syndrome, this work supports the potential use of therapeutic interventions that not only directly target sensory input and other peripheral mechanisms, but also attempt to ameliorate the broader pain experience by modifying its associated cognitive and emotional comorbidities.

ARG1 Functions in the Physiological Adaptation of Undifferentiated Plant Cells to Spaceflight.

PubMed

Zupanska, Agata K; Schultz, Eric R; Yao, JiQiang; Sng, Natasha J; Zhou, Mingqi; Callaham, Jordan B; Ferl, Robert J; Paul, Anna-Lisa

2017-11-01

Scientific access to spaceflight and especially the International Space Station has revealed that physiological adaptation to spaceflight is accompanied or enabled by changes in gene expression that significantly alter the transcriptome of cells in spaceflight. A wide range of experiments have shown that plant physiological adaptation to spaceflight involves gene expression changes that alter cell wall and other metabolisms. However, while transcriptome profiling aptly illuminates changes in gene expression that accompany spaceflight adaptation, mutation analysis is required to illuminate key elements required for that adaptation. Here we report how transcriptome profiling was used to gain insight into the spaceflight adaptation role of Altered response to gravity 1 (Arg1), a gene known to affect gravity responses in plants on Earth. The study compared expression profiles of cultured lines of Arabidopsis thaliana derived from wild-type (WT) cultivar Col-0 to profiles from a knock-out line deficient in the gene encoding ARG1 (ARG1 KO), both on the ground and in space. The cell lines were launched on SpaceX CRS-2 as part of the Cellular Expression Logic (CEL) experiment of the BRIC-17 spaceflight mission. The cultured cell lines were grown within 60 mm Petri plates in Petri Dish Fixation Units (PDFUs) that were housed within the Biological Research In Canisters (BRIC) hardware. Spaceflight samples were fixed on orbit. Differentially expressed genes were identified between the two environments (spaceflight and comparable ground controls) and the two genotypes (WT and ARG1 KO). Each genotype engaged unique genes during physiological adaptation to the spaceflight environment, with little overlap. Most of the genes altered in expression in spaceflight in WT cells were found to be Arg1-dependent, suggesting a major role for that gene in the physiological adaptation of undifferentiated cells to spaceflight. Key Words: ARG1-Spaceflight-Gene expression

Working memory capacity may influence perceived effort during aided speech recognition in noise.

PubMed

Rudner, Mary; Lunner, Thomas; Behrens, Thomas; Thorén, Elisabet Sundewall; Rönnberg, Jerker

2012-09-01

Recently there has been interest in using subjective ratings as a measure of perceived effort during speech recognition in noise. Perceived effort may be an indicator of cognitive load. Thus, subjective effort ratings during speech recognition in noise may covary both with signal-to-noise ratio (SNR) and individual cognitive capacity. The present study investigated the relation between subjective ratings of the effort involved in listening to speech in noise, speech recognition performance, and individual working memory (WM) capacity in hearing impaired hearing aid users. In two experiments, participants with hearing loss rated perceived effort during aided speech perception in noise. Noise type and SNR were manipulated in both experiments, and in the second experiment hearing aid compression release settings were also manipulated. Speech recognition performance was measured along with WM capacity. There were 46 participants in all with bilateral mild to moderate sloping hearing loss. In Experiment 1 there were 16 native Danish speakers (eight women and eight men) with a mean age of 63.5 yr (SD = 12.1) and average pure tone (PT) threshold of 47. 6 dB (SD = 9.8). In Experiment 2 there were 30 native Swedish speakers (19 women and 11 men) with a mean age of 70 yr (SD = 7.8) and average PT threshold of 45.8 dB (SD = 6.6). A visual analog scale (VAS) was used for effort rating in both experiments. In Experiment 1, effort was rated at individually adapted SNRs while in Experiment 2 it was rated at fixed SNRs. Speech recognition in noise performance was measured using adaptive procedures in both experiments with Dantale II sentences in Experiment 1 and Hagerman sentences in Experiment 2. WM capacity was measured using a letter-monitoring task in Experiment 1 and the reading span task in Experiment 2. In both experiments, there was a strong and significant relation between rated effort and SNR that was independent of individual WM capacity, whereas the

A case of peribiliary cysts accompanying bile duct carcinoma

PubMed Central

Miura, Fumihiko; Takada, Tadahiro; Amano, Hodaka; Yoshida, Masahiro; Isaka, Takahiro; Toyota, Naoyuki; Wada, Keita; Takagi, Kenji; Kato, Kenichiro

2006-01-01

A rare case of peribiliary cysts accompanying bile duct carcinoma is presented. A 54-year-old man was diagnosed as having lower bile duct carcinoma and peribiliary cysts by diagnostic imaging. He underwent pylorus preserving pancreatoduodenectomy. As for the peribiliary cysts, a course of observation was taken. Over surgery due to misdiagnosis of patients with biliary malignancy accompanied by peribiliary cysts should be avoided. PMID:16874882

Adapting to Changing Memory Retrieval Demands: Evidence from Event-Related Potentials

ERIC Educational Resources Information Center

Benoit, Roland G.; Werkle-Bergner, Markus; Mecklinger, Axel; Kray, Jutta

2009-01-01

This study investigated preparatory processes involved in adapting to changing episodic memory retrieval demands. Event-related potentials (ERPs) were recorded while participants performed a general old/new recognition task and a specific task that also required retrieval of perceptual details. The relevant task remained either constant or changed…

Affect-Based Adaptation of an Applied Video Game for Educational Purposes

ERIC Educational Resources Information Center

Bontchev, Boyan; Vassileva, Dessislava

2017-01-01

Purpose: This paper aims to clarify how affect-based adaptation can improve implicit recognition of playing style of individuals during game sessions. This study presents the "Rush for Gold" game using dynamic difficulty adjustment of tasks based on both player performance and affectation inferred through electrodermal activity and…

A comparison study between MLP and convolutional neural network models for character recognition

NASA Astrophysics Data System (ADS)

Ben Driss, S.; Soua, M.; Kachouri, R.; Akil, M.

2017-05-01

Optical Character Recognition (OCR) systems have been designed to operate on text contained in scanned documents and images. They include text detection and character recognition in which characters are described then classified. In the classification step, characters are identified according to their features or template descriptions. Then, a given classifier is employed to identify characters. In this context, we have proposed the unified character descriptor (UCD) to represent characters based on their features. Then, matching was employed to ensure the classification. This recognition scheme performs a good OCR Accuracy on homogeneous scanned documents, however it cannot discriminate characters with high font variation and distortion.3 To improve recognition, classifiers based on neural networks can be used. The multilayer perceptron (MLP) ensures high recognition accuracy when performing a robust training. Moreover, the convolutional neural network (CNN), is gaining nowadays a lot of popularity for its high performance. Furthermore, both CNN and MLP may suffer from the large amount of computation in the training phase. In this paper, we establish a comparison between MLP and CNN. We provide MLP with the UCD descriptor and the appropriate network configuration. For CNN, we employ the convolutional network designed for handwritten and machine-printed character recognition (Lenet-5) and we adapt it to support 62 classes, including both digits and characters. In addition, GPU parallelization is studied to speed up both of MLP and CNN classifiers. Based on our experimentations, we demonstrate that the used real-time CNN is 2x more relevant than MLP when classifying characters.

7 CFR 319.37-12 - Prohibited articles accompanying restricted articles.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 5 2010-01-01 2010-01-01 false Prohibited articles accompanying restricted articles... Stock, Plants, Roots, Bulbs, Seeds, and Other Plant Products 1,2 § 319.37-12 Prohibited articles accompanying restricted articles. A restricted article for importation into the United States shall not be...

7 CFR 319.37-12 - Prohibited articles accompanying restricted articles.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 5 2011-01-01 2011-01-01 false Prohibited articles accompanying restricted articles... Stock, Plants, Roots, Bulbs, Seeds, and Other Plant Products 1,2 § 319.37-12 Prohibited articles accompanying restricted articles. A restricted article for importation into the United States shall not be...

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

31 CFR 560.507 - Accompanied baggage authorized.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the United States directly or indirectly from Iran are authorized to import into the United States... Iran are authorized to export from the United States accompanied baggage normally incident to travel...

31 CFR 560.507 - Accompanied baggage authorized.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the United States directly or indirectly from Iran are authorized to import into the United States... Iran are authorized to export from the United States accompanied baggage normally incident to travel...

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Recognition memory strength is predicted by pupillary responses at encoding while fixation patterns distinguish recollection from familiarity.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2011-10-01

Thirty-five healthy participants incidentally encoded a set of man-made and natural object pictures, while their pupil response and eye movements were recorded. At retrieval, studied and new stimuli were rated as novel, familiar (strong, moderate, or weak), or recollected. We found that both pupil response and fixation patterns at encoding predict later recognition memory strength. The extent of pupillary response accompanying incidental encoding was found to be predictive of subsequent memory. In addition, the number of fixations was also predictive of later recognition memory strength, suggesting that the accumulation of greater visual detail, even for single objects, is critical for the creation of a strong memory. Moreover, fixation patterns at encoding distinguished between recollection and familiarity at retrieval, with more dispersed fixations predicting familiarity and more clustered fixations predicting recollection. These data reveal close links between the autonomic control of pupil responses and eye movement patterns on the one hand and memory encoding on the other. Moreover, the data illustrate quantitative as well as qualitative differences in the incidental visual processing of stimuli, which are differentially predictive of the strength and the kind of memory experienced at recognition.

Severity-Based Adaptation with Limited Data for ASR to Aid Dysarthric Speakers

PubMed Central

Mustafa, Mumtaz Begum; Salim, Siti Salwah; Mohamed, Noraini; Al-Qatab, Bassam; Siong, Chng Eng

2014-01-01

Automatic speech recognition (ASR) is currently used in many assistive technologies, such as helping individuals with speech impairment in their communication ability. One challenge in ASR for speech-impaired individuals is the difficulty in obtaining a good speech database of impaired speakers for building an effective speech acoustic model. Because there are very few existing databases of impaired speech, which are also limited in size, the obvious solution to build a speech acoustic model of impaired speech is by employing adaptation techniques. However, issues that have not been addressed in existing studies in the area of adaptation for speech impairment are as follows: (1) identifying the most effective adaptation technique for impaired speech; and (2) the use of suitable source models to build an effective impaired-speech acoustic model. This research investigates the above-mentioned two issues on dysarthria, a type of speech impairment affecting millions of people. We applied both unimpaired and impaired speech as the source model with well-known adaptation techniques like the maximum likelihood linear regression (MLLR) and the constrained-MLLR(C-MLLR). The recognition accuracy of each impaired speech acoustic model is measured in terms of word error rate (WER), with further assessments, including phoneme insertion, substitution and deletion rates. Unimpaired speech when combined with limited high-quality speech-impaired data improves performance of ASR systems in recognising severely impaired dysarthric speech. The C-MLLR adaptation technique was also found to be better than MLLR in recognising mildly and moderately impaired speech based on the statistical analysis of the WER. It was found that phoneme substitution was the biggest contributing factor in WER in dysarthric speech for all levels of severity. The results show that the speech acoustic models derived from suitable adaptation techniques improve the performance of ASR systems in recognising

22 CFR 40.102 - Guardian required to accompany excluded alien.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Guardian required to accompany excluded alien. 40.102 Section 40.102 Foreign Relations DEPARTMENT OF STATE VISAS REGULATIONS PERTAINING TO BOTH... Guardian required to accompany excluded alien. INA 212(a)(9)(B) is not applicable at the time of visa...

22 CFR 40.102 - Guardian required to accompany excluded alien.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Guardian required to accompany excluded alien. 40.102 Section 40.102 Foreign Relations DEPARTMENT OF STATE VISAS REGULATIONS PERTAINING TO BOTH... Guardian required to accompany excluded alien. INA 212(a)(9)(B) is not applicable at the time of visa...

22 CFR 40.102 - Guardian required to accompany excluded alien.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Guardian required to accompany excluded alien. 40.102 Section 40.102 Foreign Relations DEPARTMENT OF STATE VISAS REGULATIONS PERTAINING TO BOTH... Guardian required to accompany excluded alien. INA 212(a)(9)(B) is not applicable at the time of visa...

22 CFR 40.102 - Guardian required to accompany excluded alien.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Guardian required to accompany excluded alien. 40.102 Section 40.102 Foreign Relations DEPARTMENT OF STATE VISAS REGULATIONS PERTAINING TO BOTH... Guardian required to accompany excluded alien. INA 212(a)(9)(B) is not applicable at the time of visa...

22 CFR 40.102 - Guardian required to accompany excluded alien.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Guardian required to accompany excluded alien. 40.102 Section 40.102 Foreign Relations DEPARTMENT OF STATE VISAS REGULATIONS PERTAINING TO BOTH... Guardian required to accompany excluded alien. INA 212(a)(9)(B) is not applicable at the time of visa...

30 CFR 250.212 - What information must accompany the EP?

Code of Federal Regulations, 2011 CFR

2011-07-01

... management information required by § 250.226; (o) Environmental impact analysis information required by § 250... 30 Mineral Resources 2 2011-07-01 2011-07-01 false What information must accompany the EP? 250.212... and Information Contents of Exploration Plans (ep) § 250.212 What information must accompany the EP...

Deep learning and face recognition: the state of the art

NASA Astrophysics Data System (ADS)

Balaban, Stephen

2015-05-01

Deep Neural Networks (DNNs) have established themselves as a dominant technique in machine learning. DNNs have been top performers on a wide variety of tasks including image classification, speech recognition, and face recognition.1-3 Convolutional neural networks (CNNs) have been used in nearly all of the top performing methods on the Labeled Faces in the Wild (LFW) dataset.3-6 In this talk and accompanying paper, I attempt to provide a review and summary of the deep learning techniques used in the state-of-the-art. In addition, I highlight the need for both larger and more challenging public datasets to benchmark these systems. Despite the ability of DNNs and autoencoders to perform unsupervised feature learning, modern facial recognition pipelines still require domain specific engineering in the form of re-alignment. For example, in Facebook's recent DeepFace paper, a 3D "frontalization" step lies at the beginning of the pipeline. This step creates a 3D face model for the incoming image and then uses a series of affine transformations of the fiducial points to "frontalize" the image. This step enables the DeepFace system to use a neural network architecture with locally connected layers without weight sharing as opposed to standard convolutional layers.6 Deep learning techniques combined with large datasets have allowed research groups to surpass human level performance on the LFW dataset.3, 5 The high accuracy (99.63% for FaceNet at the time of publishing) and utilization of outside data (hundreds of millions of images in the case of Google's FaceNet) suggest that current face verification benchmarks such as LFW may not be challenging enough, nor provide enough data, for current techniques.3, 5 There exist a variety of organizations with mobile photo sharing applications that would be capable of releasing a very large scale and highly diverse dataset of facial images captured on mobile devices. Such an "ImageNet for Face Recognition" would likely receive a warm

Recognition of bacterial plant pathogens: local, systemic and transgenerational immunity.

PubMed

Henry, Elizabeth; Yadeta, Koste A; Coaker, Gitta

2013-09-01

Bacterial pathogens can cause multiple plant diseases and plants rely on their innate immune system to recognize and actively respond to these microbes. The plant innate immune system comprises extracellular pattern recognition receptors that recognize conserved microbial patterns and intracellular nucleotide binding leucine-rich repeat (NLR) proteins that recognize specific bacterial effectors delivered into host cells. Plants lack the adaptive immune branch present in animals, but still afford flexibility to pathogen attack through systemic and transgenerational resistance. Here, we focus on current research in plant immune responses against bacterial pathogens. Recent studies shed light onto the activation and inactivation of pattern recognition receptors and systemic acquired resistance. New research has also uncovered additional layers of complexity surrounding NLR immune receptor activation, cooperation and sub-cellular localizations. Taken together, these recent advances bring us closer to understanding the web of molecular interactions responsible for coordinating defense responses and ultimately resistance. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment.

PubMed

Cicirelli, Franco; Fortino, Giancarlo; Giordano, Andrea; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea

2016-09-01

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

Engineering responsive polymer building blocks with host-guest molecular recognition for functional applications.

PubMed

Hu, Jinming; Liu, Shiyong

2014-07-15

CONSPECTUS: All living organisms and soft matter are intrinsically responsive and adaptive to external stimuli. Inspired by this fact, tremendous effort aiming to emulate subtle responsive features exhibited by nature has spurred the invention of a diverse range of responsive polymeric materials. Conventional stimuli-responsive polymers are constructed via covalent bonds and can undergo reversible or irreversible changes in chemical structures, physicochemical properties, or both in response to a variety of external stimuli. They have been imparted with a variety of emerging applications including drug and gene delivery, optical sensing and imaging, diagnostics and therapies, smart coatings and textiles, and tissue engineering. On the other hand, in comparison with molecular chemistry held by covalent bonds, supramolecular chemistry built on weak and reversible noncovalent interactions has emerged as a powerful and versatile strategy for materials fabrication due to its facile accessibility, extraordinary reversibility and adaptivity, and potent applications in diverse fields. Typically involving more than one type of noncovalent interactions (e.g., hydrogen bonding, metal coordination, hydrophobic association, electrostatic interactions, van der Waals forces, and π-π stacking), host-guest recognition refers to the formation of supramolecular inclusion complexes between two or more entities connected together in a highly controlled and cooperative manner. The inherently reversible and adaptive nature of host-guest molecular recognition chemistry, stemming from multiple noncovalent interactions, has opened up a new platform to construct novel types of stimuli-responsive materials. The introduction of host-guest chemistry not only enriches the realm of responsive materials but also confers them with promising new applications. Most intriguingly, the integration of responsive polymer building blocks with host-guest recognition motifs will endow the former with

Genetic erosion impedes adaptive responses to stressful environments

PubMed Central

Bijlsma, R; Loeschcke, Volker

2012-01-01

Biodiversity is increasingly subjected to human-induced changes of the environment. To persist, populations continually have to adapt to these often stressful changes including pollution and climate change. Genetic erosion in small populations, owing to fragmentation of natural habitats, is expected to obstruct such adaptive responses: (i) genetic drift will cause a decrease in the level of adaptive genetic variation, thereby limiting evolutionary responses; (ii) inbreeding and the concomitant inbreeding depression will reduce individual fitness and, consequently, the tolerance of populations to environmental stress. Importantly, inbreeding generally increases the sensitivity of a population to stress, thereby increasing the amount of inbreeding depression. As adaptation to stress is most often accompanied by increased mortality (cost of selection), the increase in the ‘cost of inbreeding’ under stress is expected to severely hamper evolutionary adaptive processes. Inbreeding thus plays a pivotal role in this process and is expected to limit the probability of genetically eroded populations to successfully adapt to stressful environmental conditions. Consequently, the dynamics of small fragmented populations may differ considerably from large nonfragmented populations. The resilience of fragmented populations to changing and deteriorating environments is expected to be greatly decreased. Alleviating inbreeding depression, therefore, is crucial to ensure population persistence. PMID:25568035

ARG1 Functions in the Physiological Adaptation of Undifferentiated Plant Cells to Spaceflight

NASA Astrophysics Data System (ADS)

Zupanska, Agata K.; Schultz, Eric R.; Yao, JiQiang; Sng, Natasha J.; Zhou, Mingqi; Callaham, Jordan B.; Ferl, Robert J.; Paul, Anna-Lisa

2017-11-01

Scientific access to spaceflight and especially the International Space Station has revealed that physiological adaptation to spaceflight is accompanied or enabled by changes in gene expression that significantly alter the transcriptome of cells in spaceflight. A wide range of experiments have shown that plant physiological adaptation to spaceflight involves gene expression changes that alter cell wall and other metabolisms. However, while transcriptome profiling aptly illuminates changes in gene expression that accompany spaceflight adaptation, mutation analysis is required to illuminate key elements required for that adaptation. Here we report how transcriptome profiling was used to gain insight into the spaceflight adaptation role of Altered response to gravity 1 (Arg1), a gene known to affect gravity responses in plants on Earth. The study compared expression profiles of cultured lines of Arabidopsis thaliana derived from wild-type (WT) cultivar Col-0 to profiles from a knock-out line deficient in the gene encoding ARG1 (ARG1 KO), both on the ground and in space. The cell lines were launched on SpaceX CRS-2 as part of the Cellular Expression Logic (CEL) experiment of the BRIC-17 spaceflight mission. The cultured cell lines were grown within 60 mm Petri plates in Petri Dish Fixation Units (PDFUs) that were housed within the Biological Research In Canisters (BRIC) hardware. Spaceflight samples were fixed on orbit. Differentially expressed genes were identified between the two environments (spaceflight and comparable ground controls) and the two genotypes (WT and ARG1 KO). Each genotype engaged unique genes during physiological adaptation to the spaceflight environment, with little overlap. Most of the genes altered in expression in spaceflight in WT cells were found to be Arg1-dependent, suggesting a major role for that gene in the physiological adaptation of undifferentiated cells to spaceflight.

An LRR/Malectin Receptor-Like Kinase Mediates Resistance to Non-adapted and Adapted Powdery Mildew Fungi in Barley and Wheat.

PubMed

Rajaraman, Jeyaraman; Douchkov, Dimitar; Hensel, Götz; Stefanato, Francesca L; Gordon, Anna; Ereful, Nelzo; Caldararu, Octav F; Petrescu, Andrei-Jose; Kumlehn, Jochen; Boyd, Lesley A; Schweizer, Patrick

2016-01-01

Pattern recognition receptors (PRRs) belonging to the multigene family of receptor-like kinases (RLKs) are the sensing devices of plants for microbe- or pathogen-associated molecular patterns released from microbial organisms. Here we describe Rnr8 (for Required for non-host resistance 8 ) encoding HvLEMK1, a LRR-malectin domain-containing transmembrane RLK that mediates non-host resistance of barley to the non-adapted wheat powdery mildew fungus Blumeria graminis f.sp. tritici . Transgenic barley lines with silenced HvLEMK1 allow entry and colony growth of the non-adapted pathogen, although sporulation was reduced and final colony size did not reach that of the adapted barley powdery mildew fungus B. graminis f.sp. hordei . Transient expression of the barley or wheat LEMK1 genes enhanced resistance in wheat to the adapted wheat powdery mildew fungus while expression of the same genes did not protect barley from attack by the barley powdery mildew fungus. The results suggest that HvLEMK1 is a factor mediating non-host resistance in barley and quantitative host resistance in wheat to the wheat powdery mildew fungus.

Mechanism of substrate recognition by the novel Botulinum Neurotoxin subtype F5.

PubMed

Guo, Jiubiao; Chan, Edward Wai Chi; Chen, Sheng

2016-01-22

Botulinum Neurotoxins (BoNTs) are the causative agents of botulism, which act by potently inhibiting the neurotransmitter release in motor neurons. Seven serotypes of BoNTs designated as BoNT/A-G have been identified. Recently, two novel types of Botulinum neurotoxins, which cleave a novel scissile bond, L(54)-E(55), of VAMP-2 have been reported including BoNT/F subtype F5 and serotype H. However, little has been known on how these BoNTs recognize their substrates. The present study addressed for the first time the unique substrate recognition mechanism of LC/F5. Our data indicated that the optimal peptide required for efficient LC/F5 substrate cleavage is VAMP-2 (20-65). Interestingly, the overall mode of substrate recognition adopted by LC/F5 was similar to LC/F1, except that its recognition sites were shifted one helix toward the N-terminus of VAMP-2 when compared to that of LC/F1. The composition of LC/F5 pockets were found to have changed accordingly to facilitate specific recognition of these new sites of VAMP-2, including the P2', P1', P2, P3, B3, B2 and B1 sites. The study provides direct evidence of the evolutionary adaption of BoNT to recognize its substrate which is useful for effective antitoxin and inhibitor development.

Neural correlates of improved recognition of happy faces after erythropoietin treatment in bipolar disorder.

PubMed

Miskowiak, K W; Petersen, N A; Harmer, C J; Ehrenreich, E; Kessing, L V; Vinberg, M; Macoveanu, J; Siebner, H R

2018-06-07

Bipolar disorder is associated with impairments in social cognition including the recognition of happy faces. This is accompanied by imbalanced cortico-limbic response to emotional faces. We found that EPO improved the recognition of happy faces in patients with bipolar disorder. This randomized, controlled, longitudinal fMRI study explores the neuronal underpinnings of this effect. Forty-four patients with bipolar disorder in full or partial remission were randomized to eight weekly erythropoietin (EPO; 40 000 IU) or saline (NaCl 0.9%) infusions in a double-blind, parallel-group design. Participants underwent whole-brain fMRI at 3T, mood ratings and blood tests at baseline and week 14. During fMRI, participants viewed happy and fearful faces and performed a gender discrimination task. Thirty-four patients had complete pre- and post-treatment fMRI data (EPO: N = 18, saline: N = 16). Erythropoietin vs. saline increased right superior frontal response to happy vs. fearful faces. This correlated with improved happiness recognition in the EPO group. Erythropoietin also enhanced gender discrimination accuracy for happy faces. These effects were not influenced by medication, mood, red blood cells or blood pressure. Together with previous findings, the present observation suggests that increased dorsal prefrontal attention control is a common mechanism of EPO-associated improvements across several cognitive domains. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Reduced adaptability, but no fundamental disruption, of norm-based face-coding mechanisms in cognitively able children and adolescents with autism.

PubMed

Rhodes, Gillian; Ewing, Louise; Jeffery, Linda; Avard, Eleni; Taylor, Libby

2014-09-01

Faces are adaptively coded relative to visual norms that are updated by experience. This coding is compromised in autism and the broader autism phenotype, suggesting that atypical adaptive coding of faces may be an endophenotype for autism. Here we investigate the nature of this atypicality, asking whether adaptive face-coding mechanisms are fundamentally altered, or simply less responsive to experience, in autism. We measured adaptive coding, using face identity aftereffects, in cognitively able children and adolescents with autism and neurotypical age- and ability-matched participants. We asked whether these aftereffects increase with adaptor identity strength as in neurotypical populations, or whether they show a different pattern indicating a more fundamental alteration in face-coding mechanisms. As expected, face identity aftereffects were reduced in the autism group, but they nevertheless increased with adaptor strength, like those of our neurotypical participants, consistent with norm-based coding of face identity. Moreover, their aftereffects correlated positively with face recognition ability, consistent with an intact functional role for adaptive coding in face recognition ability. We conclude that adaptive norm-based face-coding mechanisms are basically intact in autism, but are less readily calibrated by experience. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Prosopagnosia and facial expression recognition].

PubMed

Koyama, Shinichi

2014-04-01

This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

Adaptive method of recognition of signals for one and two-frequency signal system in the telephony on the background of speech

NASA Astrophysics Data System (ADS)

Kuznetsov, Michael V.

2006-05-01

For reliable teamwork of various systems of automatic telecommunication including transferring systems of optical communication networks it is necessary authentic recognition of signals for one- or two-frequency service signal system. The analysis of time parameters of an accepted signal allows increasing reliability of detection and recognition of the service signal system on a background of speech.

Track and vertex reconstruction: From classical to adaptive methods

NASA Astrophysics Data System (ADS)

Strandlie, Are; Frühwirth, Rudolf

2010-04-01

This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.

Impaired social recognition memory in Recombination Activating Gene 1-deficient mice

PubMed Central

McGowan, Patrick O.; Hope, Thomas A.; Meck, Warren H.; Kelsoe, Garnett; Williams, Christina L.

2012-01-01

The Recombination Activating Genes (RAGs) encode two enzymes that play key roles in the adaptive immune system. RAG1 and RAG2 mediate VDJ recombination, a process necessary for the maturation of B- and T-cells. Interestingly, RAG1 is also expressed in the brain, particularly in areas of high neural density such as the hippocampus, although its function is unknown. We tested evidence that RAG1 plays a role in brain function using a social recognition memory task, an assessment of the acquisition and retention of conspecific identity. In a first experiment, we found that RAG1-deficient mice show impaired social recognition memory compared to mice wildtype for the RAG1 allele. In a second experiment, by breeding to homogenize background genotype we found that RAG1-deficient mice show impaired social recognition memory relative to heterozygous or RAG2-deficient littermates. Because RAG1 and RAG2 null mice are both immunodeficient, the results suggest that the memory impairment is not an indirect effect of immunological dysfunction. RAG1-deficient mice show normal habituation to non-socially derived odors and habituation to an open-field, indicating that the observed effect is not likely a result of a general deficit in habituation to novelty. These data trace the origin of the impairment in social recognition memory in RAG1-deficient mice to the RAG1 gene locus and implicate RAG1 in memory formation. PMID:21354115

Computer Recognition of Facial Profiles

DTIC Science & Technology

1974-08-01

facial recognition 20. ABSTRACT (Continue on reverse side It necessary and Identify by block number) A system for the recognition of human faces from...21 2.6 Classification Algorithms ........... ... 32 III FACIAL RECOGNITION AND AUTOMATIC TRAINING . . . 37 3.1 Facial Profile Recognition...provide a fair test of the classification system. The work of Goldstein, Harmon, and Lesk [81 indicates, however, that for facial recognition , a ten class

Automatic detection and recognition of signs from natural scenes.

PubMed

Chen, Xilin; Yang, Jie; Zhang, Jing; Waibel, Alex

2004-01-01

In this paper, we present an approach to automatic detection and recognition of signs from natural scenes, and its application to a sign translation task. The proposed approach embeds multiresolution and multiscale edge detection, adaptive searching, color analysis, and affine rectification in a hierarchical framework for sign detection, with different emphases at each phase to handle the text in different sizes, orientations, color distributions and backgrounds. We use affine rectification to recover deformation of the text regions caused by an inappropriate camera view angle. The procedure can significantly improve text detection rate and optical character recognition (OCR) accuracy. Instead of using binary information for OCR, we extract features from an intensity image directly. We propose a local intensity normalization method to effectively handle lighting variations, followed by a Gabor transform to obtain local features, and finally a linear discriminant analysis (LDA) method for feature selection. We have applied the approach in developing a Chinese sign translation system, which can automatically detect and recognize Chinese signs as input from a camera, and translate the recognized text into English.

A cascaded neuro-computational model for spoken word recognition

NASA Astrophysics Data System (ADS)

Hoya, Tetsuya; van Leeuwen, Cees

2010-03-01

In human speech recognition, words are analysed at both pre-lexical (i.e., sub-word) and lexical (word) levels. The aim of this paper is to propose a constructive neuro-computational model that incorporates both these levels as cascaded layers of pre-lexical and lexical units. The layered structure enables the system to handle the variability of real speech input. Within the model, receptive fields of the pre-lexical layer consist of radial basis functions; the lexical layer is composed of units that perform pattern matching between their internal template and a series of labels, corresponding to the winning receptive fields in the pre-lexical layer. The model adapts through self-tuning of all units, in combination with the formation of a connectivity structure through unsupervised (first layer) and supervised (higher layers) network growth. Simulation studies show that the model can achieve a level of performance in spoken word recognition similar to that of a benchmark approach using hidden Markov models, while enabling parallel access to word candidates in lexical decision making.

Nonlinear filtering for character recognition in low quality document images

NASA Astrophysics Data System (ADS)

Diaz-Escobar, Julia; Kober, Vitaly

2014-09-01

Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition.

PubMed

Janko, Vito; Luštrek, Mitja

2017-12-29

The recognition of the user's context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system's energy expenditure and the system's accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.

Dissociations among functional subsystems governing melody recognition after right-hemisphere damage.

PubMed

Steinke, W R; Cuddy, L L; Jakobson, L S

2001-07-01

This study describes an amateur musician, KB, who became amusic following a right-hemisphere stroke. A series of assessments conducted post-stroke revealed that KB functioned in the normal range for most verbal skills. However, compared with controls matched in age and music training, KB showed severe loss of pitch and rhythmic processing abilities. His ability to recognise and identify familiar instrumental melodies was also lost. Despite these deficits, KB performed remarkably well when asked to recognise and identify familiar song melodies presented without accompanying lyrics. This dissociation between the ability to recognise/identify song vs. instrumental melodies was replicated across different sets of musical materials, including newly learned melodies. Analyses of the acoustical and musical features of song and instrumental melodies discounted an explanation of the dissociation based on these features alone. Rather, the results suggest a functional dissociation resulting from a focal brain lesion. We propose that, in the case of song melodies, there remains sufficient activation in KB's melody analysis system to coactivate an intact representation of both associative information and the lyrics in the speech lexicon, making recognition and identification possible. In the case of instrumental melodies, no such associative processes exist; thus recognition and identification do not occur.

5 CFR 582.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2012 CFR

2012-01-01

... accompany legal process. 582.203 Section 582.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS COMMERCIAL GARNISHMENT OF FEDERAL EMPLOYEES' PAY Service of Legal Process § 582.203 Information minimally required to accompany legal process. (a) Sufficient identifying...

5 CFR 582.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2010 CFR

2010-01-01

... accompany legal process. 582.203 Section 582.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS COMMERCIAL GARNISHMENT OF FEDERAL EMPLOYEES' PAY Service of Legal Process § 582.203 Information minimally required to accompany legal process. (a) Sufficient identifying...

5 CFR 582.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2011 CFR

2011-01-01

... accompany legal process. 582.203 Section 582.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS COMMERCIAL GARNISHMENT OF FEDERAL EMPLOYEES' PAY Service of Legal Process § 582.203 Information minimally required to accompany legal process. (a) Sufficient identifying...

5 CFR 582.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2014 CFR

2014-01-01

... accompany legal process. 582.203 Section 582.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS COMMERCIAL GARNISHMENT OF FEDERAL EMPLOYEES' PAY Service of Legal Process § 582.203 Information minimally required to accompany legal process. (a) Sufficient identifying...

5 CFR 582.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2013 CFR

2013-01-01

... accompany legal process. 582.203 Section 582.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS COMMERCIAL GARNISHMENT OF FEDERAL EMPLOYEES' PAY Service of Legal Process § 582.203 Information minimally required to accompany legal process. (a) Sufficient identifying...

Perception of pathogenic or beneficial bacteria and their evasion of host immunity: pattern recognition receptors in the frontline

PubMed Central

Trdá, Lucie; Boutrot, Freddy; Claverie, Justine; Brulé, Daphnée; Dorey, Stephan; Poinssot, Benoit

2015-01-01

Plants are continuously monitoring the presence of microorganisms to establish an adapted response. Plants commonly use pattern recognition receptors (PRRs) to perceive microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) which are microorganism molecular signatures. Located at the plant plasma membrane, the PRRs are generally receptor-like kinases (RLKs) or receptor-like proteins (RLPs). MAMP detection will lead to the establishment of a plant defense program called MAMP-triggered immunity (MTI). In this review, we overview the RLKs and RLPs that assure early recognition and control of pathogenic or beneficial bacteria. We also highlight the crucial function of PRRs during plant-microbe interactions, with a special emphasis on the receptors of the bacterial flagellin and peptidoglycan. In addition, we discuss the multiple strategies used by bacteria to evade PRR-mediated recognition. PMID:25904927

Dopamine D1 receptor activation leads to object recognition memory in a coral reef fish.

PubMed

Hamilton, Trevor J; Tresguerres, Martin; Kline, David I

2017-07-01

Object recognition memory is the ability to identify previously seen objects and is an adaptive mechanism that increases survival for many species throughout the animal kingdom. Previously believed to be possessed by only the highest order mammals, it is now becoming clear that fish are also capable of this type of memory formation. Similar to the mammalian hippocampus, the dorsolateral pallium regulates distinct memory processes and is modulated by neurotransmitters such as dopamine. Caribbean bicolour damselfish ( Stegastes partitus ) live in complex environments dominated by coral reef structures and thus likely possess many types of complex memory abilities including object recognition. This study used a novel object recognition test in which fish were first presented two identical objects, then after a retention interval of 10 min with no objects, the fish were presented with a novel object and one of the objects they had previously encountered in the first trial. We demonstrate that the dopamine D 1 -receptor agonist (SKF 38393) induces the formation of object recognition memories in these fish. Thus, our results suggest that dopamine-receptor mediated enhancement of spatial memory formation in fish represents an evolutionarily conserved mechanism in vertebrates. © 2017 The Author(s).

Discriminant WSRC for Large-Scale Plant Species Recognition.

PubMed

Zhang, Shanwen; Zhang, Chuanlei; Zhu, Yihai; You, Zhuhong

2017-01-01

In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.

Emotion recognition in early Parkinson's disease patients undergoing deep brain stimulation or dopaminergic therapy: a comparison to healthy participants.

PubMed

McIntosh, Lindsey G; Mannava, Sishir; Camalier, Corrie R; Folley, Bradley S; Albritton, Aaron; Konrad, Peter E; Charles, David; Park, Sohee; Neimat, Joseph S

2014-01-01

Parkinson's disease (PD) is traditionally regarded as a neurodegenerative movement disorder, however, nigrostriatal dopaminergic degeneration is also thought to disrupt non-motor loops connecting basal ganglia to areas in frontal cortex involved in cognition and emotion processing. PD patients are impaired on tests of emotion recognition, but it is difficult to disentangle this deficit from the more general cognitive dysfunction that frequently accompanies disease progression. Testing for emotion recognition deficits early in the disease course, prior to cognitive decline, better assesses the sensitivity of these non-motor corticobasal ganglia-thalamocortical loops involved in emotion processing to early degenerative change in basal ganglia circuits. In addition, contrasting this with a group of healthy aging individuals demonstrates changes in emotion processing specific to the degeneration of basal ganglia circuitry in PD. Early PD patients (EPD) were recruited from a randomized clinical trial testing the safety and tolerability of deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) in early-staged PD. EPD patients were previously randomized to receive optimal drug therapy only (ODT), or drug therapy plus STN-DBS (ODT + DBS). Matched healthy elderly controls (HEC) and young controls (HYC) also participated in this study. Participants completed two control tasks and three emotion recognition tests that varied in stimulus domain. EPD patients were impaired on all emotion recognition tasks compared to HEC. Neither therapy type (ODT or ODT + DBS) nor therapy state (ON/OFF) altered emotion recognition performance in this study. Finally, HEC were impaired on vocal emotion recognition relative to HYC, suggesting a decline related to healthy aging. This study supports the existence of impaired emotion recognition early in the PD course, implicating an early disruption of fronto-striatal loops mediating emotional function.

Structural self-assembly and avalanchelike dynamics in locally adaptive networks

NASA Astrophysics Data System (ADS)

Gräwer, Johannes; Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

2015-07-01

Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events.

Profiles of Discourse Recognition

ERIC Educational Resources Information Center

Singer, Murray

2013-01-01

A discourse recognition theory derived from more general memory formulations would be broad in its psychological implications. This study compared discourse recognition with some established profiles of item recognition. Participants read 10 stories either once or twice each. They then rated their confidence in recognizing explicit, paraphrased,…

Sudden Event Recognition: A Survey

PubMed Central

Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

2013-01-01

Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

Methods of Psychological and Pedagogical Accompaniment of First-Year Students in Process of Adapting to Learning at University

ERIC Educational Resources Information Center

Maralova, Tatyana P.; Filipenkova, Olesya G.; Galitskikh, Elena O.; Shulga, Tatiana I.; Sidyacheva, Natalya V.; Ovsyanik, Olga A.

2016-01-01

The relevance of the study is conditioned by the complexity of students' adaptation to learning at University due to the change of social environment, an alarming feelings about the precise self-determination, lack of knowledge in opportunities for self-expression in art, science, sport and public life. The purpose of the paper is to identify…

Repetition Suppression and Reactivation in Auditory–Verbal Short-Term Recognition Memory

PubMed Central

D'Esposito, Mark

2009-01-01

The neural response to stimulus repetition is not uniform across brain regions, stimulus modalities, or task contexts. For instance, it has been observed in many functional magnetic resonance imaging (fMRI) studies that sometimes stimulus repetition leads to a relative reduction in neural activity (repetition suppression), whereas in other cases repetition results in a relative increase in activity (repetition enhancement). In the present study, we hypothesized that in the context of a verbal short-term recognition memory task, repetition-related “increases” should be observed in the same posterior temporal regions that have been previously associated with “persistent activity” in working memory rehearsal paradigms. We used fMRI and a continuous recognition memory paradigm with short lags to examine repetition effects in the posterior and anterior regions of the superior temporal cortex. Results showed that, consistent with our hypothesis, the 2 posterior temporal regions consistently associated with working memory maintenance, also show repetition increases during short-term recognition memory. In contrast, a region in the anterior superior temporal lobe showed repetition suppression effects, consistent with previous research work on perceptual adaptation in the auditory–verbal domain. We interpret these results in light of recent theories of the functional specialization along the anterior and posterior axes of the superior temporal lobe. PMID:18987393

Repetition suppression and reactivation in auditory-verbal short-term recognition memory.

PubMed

Buchsbaum, Bradley R; D'Esposito, Mark

2009-06-01

The neural response to stimulus repetition is not uniform across brain regions, stimulus modalities, or task contexts. For instance, it has been observed in many functional magnetic resonance imaging (fMRI) studies that sometimes stimulus repetition leads to a relative reduction in neural activity (repetition suppression), whereas in other cases repetition results in a relative increase in activity (repetition enhancement). In the present study, we hypothesized that in the context of a verbal short-term recognition memory task, repetition-related "increases" should be observed in the same posterior temporal regions that have been previously associated with "persistent activity" in working memory rehearsal paradigms. We used fMRI and a continuous recognition memory paradigm with short lags to examine repetition effects in the posterior and anterior regions of the superior temporal cortex. Results showed that, consistent with our hypothesis, the 2 posterior temporal regions consistently associated with working memory maintenance, also show repetition increases during short-term recognition memory. In contrast, a region in the anterior superior temporal lobe showed repetition suppression effects, consistent with previous research work on perceptual adaptation in the auditory-verbal domain. We interpret these results in light of recent theories of the functional specialization along the anterior and posterior axes of the superior temporal lobe.

Distinct motor strategies underlying split-belt adaptation in human walking and running.

PubMed

Ogawa, Tetsuya; Kawashima, Noritaka; Obata, Hiroki; Kanosue, Kazuyuki; Nakazawa, Kimitaka

2015-01-01

The aim of the present study was to elucidate the adaptive and de-adaptive nature of human running on a split-belt treadmill. The degree of adaptation and de-adaptation was compared with those in walking by calculating the antero-posterior component of the ground reaction force (GRF). Adaptation to walking and running on a split-belt resulted in a prominent asymmetry in the movement pattern upon return to the normal belt condition, while the two components of the GRF showed different behaviors depending on the gaits. The anterior braking component showed prominent adaptive and de-adaptive behaviors in both gaits. The posterior propulsive component, on the other hand, exhibited such behavior only in running, while that in walking showed only short-term aftereffect (lasting less than 10 seconds) accompanied by largely reactive responses. These results demonstrate a possible difference in motor strategies (that is, the use of reactive feedback and adaptive feedforward control) by the central nervous system (CNS) for split-belt locomotor adaptation between walking and running. The present results provide basic knowledge on neural control of human walking and running as well as possible strategies for gait training in athletic and rehabilitation scenes.

Distinct Motor Strategies Underlying Split-Belt Adaptation in Human Walking and Running

PubMed Central

Ogawa, Tetsuya; Kawashima, Noritaka; Obata, Hiroki; Kanosue, Kazuyuki; Nakazawa, Kimitaka

2015-01-01

The aim of the present study was to elucidate the adaptive and de-adaptive nature of human running on a split-belt treadmill. The degree of adaptation and de-adaptation was compared with those in walking by calculating the antero-posterior component of the ground reaction force (GRF). Adaptation to walking and running on a split-belt resulted in a prominent asymmetry in the movement pattern upon return to the normal belt condition, while the two components of the GRF showed different behaviors depending on the gaits. The anterior braking component showed prominent adaptive and de-adaptive behaviors in both gaits. The posterior propulsive component, on the other hand, exhibited such behavior only in running, while that in walking showed only short-term aftereffect (lasting less than 10 seconds) accompanied by largely reactive responses. These results demonstrate a possible difference in motor strategies (that is, the use of reactive feedback and adaptive feedforward control) by the central nervous system (CNS) for split-belt locomotor adaptation between walking and running. The present results provide basic knowledge on neural control of human walking and running as well as possible strategies for gait training in athletic and rehabilitation scenes. PMID:25775426

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

PubMed Central

Jaafar, Haryati; Ibrahim, Salwani; Ramli, Dzati Athiar

2015-01-01

Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN), was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%. PMID:26113861

Examining the Relationships among Item Recognition, Source Recognition, and Recall from an Individual Differences Perspective

ERIC Educational Resources Information Center

Unsworth, Nash; Brewer, Gene A.

2009-01-01

The authors of the current study examined the relationships among item-recognition, source-recognition, free recall, and other memory and cognitive ability tasks via an individual differences analysis. Two independent sources of variance contributed to item-recognition and source-recognition performance, and these two constructs related…

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…

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-12-17

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

Early life stress impairs social recognition due to a blunted response of vasopressin release within the septum of adult male rats.

PubMed

Lukas, Michael; Bredewold, Remco; Landgraf, Rainer; Neumann, Inga D; Veenema, Alexa H

2011-07-01

Early life stress poses a risk for the development of psychopathologies characterized by disturbed emotional, social, and cognitive performance. We used maternal separation (MS, 3h daily, postnatal days 1-14) to test whether early life stress impairs social recognition performance in juvenile (5-week-old) and adult (16-week-old) male Wistar rats. Social recognition was tested in the social discrimination test and defined by increased investigation by the experimental rat towards a novel rat compared with a previously encountered rat. Juvenile control and MS rats demonstrated successful social recognition at inter-exposure intervals of 30 and 60 min. However, unlike adult control rats, adult MS rats failed to discriminate between a previously encountered and a novel rat after 60 min. The social recognition impairment of adult MS rats was accompanied by a lack of a rise in arginine vasopressin (AVP) release within the lateral septum seen during social memory acquisition in adult control rats. This blunted response of septal AVP release was social stimulus-specific because forced swimming induced a rise in septal AVP release in both control and MS rats. Retrodialysis of AVP (1 μg/ml, 3.3 μl/min, 30 min) into the lateral septum during social memory acquisition restored social recognition in adult MS rats at the 60-min interval. These studies demonstrate that MS impairs social recognition performance in adult rats, which is likely caused by blunted septal AVP activation. Impaired social recognition may be linked to MS-induced changes in other social behaviors like aggression as shown previously. Copyright © 2010 Elsevier Ltd. All rights reserved.

Kernel Manifold Alignment for Domain Adaptation.

PubMed

Tuia, Devis; Camps-Valls, Gustau

2016-01-01

The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. However, multimodal architectures must rely on models able to adapt to changes in the data distribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation problem as domain adaptation. In this paper, instead of adapting the trained models themselves, we alternatively focus on finding mappings of the data sources into a common, semantically meaningful, representation domain. This field of manifold alignment extends traditional techniques in statistics such as canonical correlation analysis (CCA) to deal with nonlinear adaptation and possibly non-corresponding data pairs between the domains. We introduce a kernel method for manifold alignment (KEMA) that can match an arbitrary number of data sources without needing corresponding pairs, just few labeled examples in all domains. KEMA has interesting properties: 1) it generalizes other manifold alignment methods, 2) it can align manifolds of very different complexities, performing a discriminative alignment preserving each manifold inner structure, 3) it can define a domain-specific metric to cope with multimodal specificities, 4) it can align data spaces of different dimensionality, 5) it is robust to strong nonlinear feature deformations, and 6) it is closed-form invertible, which allows transfer across-domains and data synthesis. To authors' knowledge this is the first method addressing all these important issues at once. We also present a reduced-rank version of KEMA for computational

Complex Changes in the Innate and Adaptive Immunity Accompany Progressive Degeneration of the Nigrostriatal Pathway Induced by Intrastriatal Injection of 6-Hydroxydopamine in the Rat.

PubMed

Ambrosi, Giulia; Kustrimovic, Natasa; Siani, Francesca; Rasini, Emanuela; Cerri, Silvia; Ghezzi, Cristina; Dicorato, Giuseppe; Caputo, Sofia; Marino, Franca; Cosentino, Marco; Blandini, Fabio

2017-07-01

We investigated changes in innate and adaptive immunity paralleling the progressive nigrostriatal damage occurring in a neurotoxic model of Parkinson's disease (PD) based on unilateral infusion of 6-hydroxydopamine (6-OHDA) into the rat striatum. A time-course analysis was conducted to assess changes in morphology (activation) and cell density of microglia and astrocytes, microglia polarization (M1 vs. M2 phenotype), lymphocyte infiltration in the lesioned substantia nigra pars compacta (SNc), and modifications of CD8+ and subsets of CD4+ T cell in peripheral blood accompanying nigrostriatal degeneration. Confirming previous results, we observed slightly different profiles of activation for astrocytes and microglia paralleling nigral neuronal loss. For astrocytes, morphological changes and cell density increases were mostly evident at the latest time points (14 and 28 days post-surgery), while moderate microglia activation was present since the earliest time point. For the first time, in this model, we described the time-dependent profile of microglia polarization. Activated microglia clearly expressed the M2 phenotype in the earlier phase of the experiment, before cell death became manifest, gradually shifting to the M1 phenotype as SNc cell death started. In parallel, a reduction in the percentage of circulating CD4+ T regulatory (Treg) cells, starting as early as day 3 post-6-OHDA injection, was detected in 6-OHDA-injected rats. Our data show that nigrostriatal degeneration is associated with complex changes in central and peripheral immunity. Microglia activation and polarization, Treg cells, and the factors involved in their cross-talk should be further investigated as targets for the development of therapeutic strategies for disease modification in PD.

The contribution of perceived parental and familial characteristics to attitudes toward accompanied driving among young drivers.

PubMed

Taubman-Ben-Ari, Orit

2011-09-01

One of the main requirements of the graduated driving licensing system in Israel is that new drivers be accompanied by an experienced driver (usually one of their parents) for the first three months after receipt of their license. The current series of studies examined the associations between young drivers' attitudes toward accompanied driving (ATAD) and their perception of their parents' driving styles and parenting modes, as well as dynamic of their family. Young drivers completed questionnaires assessing their ATAD, and either perceived parental driving style (Study 1, n=100), perceived parenting style (Study 2, n=120), or perceived family dynamic (Study 3, n=254). The results indicated significant associations between the young drivers' ATAD of tension, relatedness, avoidance, disapproval, and anxiety, and their own perceptions of the characteristic driving styles of their parents (risky, anxious, angry, and careful). They also indicated significant relationship between youngsters' ATAD and their perceptions of their parents' parenting modes (responsive, demanding, and autonomy-granting). Finally, the results indicated significant negative associations between ATAD of tension, avoidance, disapproval, and anxiety, and family cohesion and adaptability, and a positive association between these two and relatedness. The results are discussed in respect to the relationship between the parental model and the young drivers' ATAD in particular, and risk management in general, and practical implications of these results are offered. Copyright © 2011 Elsevier Ltd. All rights reserved.

Emerging hierarchies in dynamically adapting webs

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Graewer, Johannes; Magnasco, Marcelo; Modes, Carl

Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. We quantify the hierarchical organization of the networks by developing an algorithm that decomposes the architecture to multiple scales and analyzes how the organization in each scale relates to that of the scale above and below it. The methodologies developed in this work are applicable to a wide range of systems including the slime mold physarum polycephalum, human microvasculature, and force chains in granular media.

Target recognitions in multiple-camera closed-circuit television using color constancy

NASA Astrophysics Data System (ADS)

Soori, Umair; Yuen, Peter; Han, Ji Wen; Ibrahim, Izzati; Chen, Wentao; Hong, Kan; Merfort, Christian; James, David; Richardson, Mark

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by

30 CFR 250.228 - What administrative information must accompany the EP?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false What administrative information must accompany the EP? 250.228 Section 250.228 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE... Contents of Exploration Plans (ep) § 250.228 What administrative information must accompany the EP? The...

Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision.

PubMed

Li, Heng; Su, Xiaofan; Wang, Jing; Kan, Han; Han, Tingting; Zeng, Yajie; Chai, Xinyu

2018-01-01

Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual perception, prosthetic recipients can just complete some simple visual tasks, but more complex tasks like face identification/object recognition are extremely difficult. Therefore, it is necessary to investigate and apply image processing strategies for optimizing the visual perception of the recipients. This study focuses on recognition of the object of interest employing simulated prosthetic vision. We used a saliency segmentation method based on a biologically plausible graph-based visual saliency model and a grabCut-based self-adaptive-iterative optimization framework to automatically extract foreground objects. Based on this, two image processing strategies, Addition of Separate Pixelization and Background Pixel Shrink, were further utilized to enhance the extracted foreground objects. i) The results showed by verification of psychophysical experiments that under simulated prosthetic vision, both strategies had marked advantages over Direct Pixelization in terms of recognition accuracy and efficiency. ii) We also found that recognition performance under two strategies was tied to the segmentation results and was affected positively by the paired-interrelated objects in the scene. The use of the saliency segmentation method and image processing strategies can automatically extract and enhance foreground objects, and significantly improve object recognition performance towards recipients implanted a high-density implant. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptation to Antifaces and the Perception of Correct Famous Identity in an Average Face

PubMed Central

Little, Anthony C.; Hancock, Peter J. B.; DeBruine, Lisa M.; Jones, Benedict C.

2011-01-01

Previous experiments have examined exposure to anti-identities (faces that possess traits opposite to an identity through a population average), finding that exposure to antifaces enhances recognition of the plus-identity images. Here we examine adaptation to antifaces using famous female celebrities. We demonstrate: that exposure to a color and shape transformed antiface of a celebrity increases the likelihood of perceiving the identity from which the antiface was manufactured in a composite face and that the effect shows size invariance (experiment 1), equivalent effects are seen in internet and laboratory-based studies (experiment 2), adaptation to shape-only antifaces has stronger effects on identity recognition than adaptation to color-only antifaces (experiment 3), and exposure to male versions of the antifaces does not influence the perception of female faces (experiment 4). Across these studies we found an effect of order where aftereffects were more pronounced in early than later trials. Overall, our studies delineate several aspects of identity aftereffects and support the proposal that identity is coded relative to other faces with special reference to a relatively sex-specific mean face representation. PMID:22363301

Structural basis of DNA folding and recognition in an AMP-DNA aptamer complex: distinct architectures but common recognition motifs for DNA and RNA aptamers complexed to AMP.

PubMed

Lin, C H; Patel, D J

1997-11-01

Structural studies by nuclear magnetic resonance (NMR) of RNA and DNA aptamer complexes identified through in vitro selection and amplification have provided a wealth of information on RNA and DNA tertiary structure and molecular recognition in solution. The RNA and DNA aptamers that target ATP (and AMP) with micromolar affinity exhibit distinct binding site sequences and secondary structures. We report below on the tertiary structure of the AMP-DNA aptamer complex in solution and compare it with the previously reported tertiary structure of the AMP-RNA aptamer complex in solution. The solution structure of the AMP-DNA aptamer complex shows, surprisingly, that two AMP molecules are intercalated at adjacent sites within a rectangular widened minor groove. Complex formation involves adaptive binding where the asymmetric internal bubble of the free DNA aptamer zippers up through formation of a continuous six-base mismatch segment which includes a pair of adjacent three-base platforms. The AMP molecules pair through their Watson-Crick edges with the minor groove edges of guanine residues. These recognition G.A mismatches are flanked by sheared G.A and reversed Hoogsteen G.G mismatch pairs. The AMP-DNA aptamer and AMP-RNA aptamer complexes have distinct tertiary structures and binding stoichiometries. Nevertheless, both complexes have similar structural features and recognition alignments in their binding pockets. Specifically, AMP targets both DNA and RNA aptamers by intercalating between purine bases and through identical G.A mismatch formation. The recognition G.A mismatch stacks with a reversed Hoogsteen G.G mismatch in one direction and with an adenine base in the other direction in both complexes. It is striking that DNA and RNA aptamers selected independently from libraries of 10(14) molecules in each case utilize identical mismatch alignments for molecular recognition with micromolar affinity within binding-site pockets containing common structural elements.

Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

PubMed

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

Adaptation to walking with an exoskeleton that assists ankle extension.

PubMed

Galle, S; Malcolm, P; Derave, W; De Clercq, D

2013-07-01

The goal of this study was to investigate adaptation to walking with bilateral ankle-foot exoskeletons with kinematic control that assisted ankle extension during push-off. We hypothesized that subjects would show a neuromotor and metabolic adaptation during a 24min walking trial with a powered exoskeleton. Nine female subjects walked on a treadmill at 1.36±0.04ms(-1) during 24min with a powered exoskeleton and 4min with an unpowered exoskeleton. Subjects showed a metabolic adaptation after 18.5±5.0min, followed by an adapted period. Metabolic cost, electromyography and kinematics were compared between the unpowered condition, the beginning of the adaptation and the adapted period. In the beginning of the adaptation (4min), a reduction in metabolic cost of 9% was found compared to the unpowered condition. This reduction was accompanied by reduced muscular activity in the plantarflexor muscles, as the powered exoskeleton delivered part of the necessary ankle extension moment. During the adaptation this metabolic reduction further increased to 16%, notwithstanding a constant exoskeleton assistance. This increased reduction is the result of a neuromotor adaptation in which subjects adapt to walking with the exoskeleton, thereby reducing muscular activity in all leg muscles. Because of the fast adaptation and the significant reductions in metabolic cost we want to highlight the potential of an ankle-foot exoskeleton with kinematic control that assists ankle extension during push-off. Copyright © 2013 Elsevier B.V. All rights reserved.

The geography of sex-specific selection, local adaptation, and sexual dimorphism.

PubMed

Connallon, Tim

2015-09-01

Local adaptation and sexual dimorphism are iconic evolutionary scenarios of intraspecific adaptive differentiation in the face of gene flow. Although theory has traditionally considered local adaptation and sexual dimorphism as conceptually distinct processes, emerging data suggest that they often act concurrently during evolutionary diversification. Here, I merge theories of local adaptation in space and sex-specific adaptation over time, and show that their confluence yields several new predictions about the roles of context-specific selection, migration, and genetic correlations, in adaptive diversification. I specifically revisit two influential predictions from classical studies of clinal adaptation and sexual dimorphism: (1) that local adaptation should decrease with distance from the species' range center and (2) that opposing directional selection between the sexes (sexual antagonism) should inevitably accompany the evolution of sexual dimorphism. I show that both predictions can break down under clinally varying selection. First, the geography of local adaptation can be sexually dimorphic, with locations of relatively high local adaptation differing profoundly between the sexes. Second, the intensity of sexual antagonism varies across the species' range, with subpopulations near the range center representing hotspots for antagonistic selection. The results highlight the context-dependent roles of migration versus sexual conflict as primary constraints to adaptive diversification. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Novel Adaptive and Innate Immunity Targets in Hypertension

PubMed Central

Abais-Battad, Justine M.; Dasinger, John Henry; Fehrenbach, Daniel J.; Mattson, David L.

2017-01-01

Hypertension is a worldwide epidemic and global health concern as it is a major risk factor for the development of cardiovascular diseases. A relationship between the immune system and its contributing role to the pathogenesis of hypertension has been long established, but substantial advancements within the last few years have dissected specific causal molecular mechanisms. This review will briefly examine these recent studies exploring the involvement of either innate or adaptive immunity pathways. Such pathways to be discussed include innate immunity factors such as antigen presenting cells and pattern recognition receptors, adaptive immune elements including T and B lymphocytes, and more specifically, the emerging role of T regulatory cells, as well as the potential of cytokines and chemokines to serve as signaling messengers connecting innate and adaptive immunity. Together, we summarize these studies to provide new perspective for what will hopefully lead to more targeted approaches to manipulate the immune system as hypertensive therapy. PMID:28336371

49 CFR 591.6 - Documents accompanying declarations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) IMPORTATION OF VEHICLES AND EQUIPMENT SUBJECT TO FEDERAL SAFETY, BUMPER AND THEFT PREVENTION STANDARDS § 591.6 Documents accompanying... public roads, or that the equipment item was not manufactured for use on a motor vehicle or is not an...

Effects of adaptation of vestibulo-ocular reflex function on manual target localization

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Merkle, L. A.; Barry, S. R.; Huebner, W. P.; Cohen, H. S.; Mueller, S. A.; Fordice, J.

2000-01-01

The goal of the present study was to determine if adaptive modulation of vestibulo-ocular reflex (VOR) function is associated with commensurate alterations in manual target localization. To measure the effects of adapted VOR on manual responses we developed the Vestibular-Contingent Pointing Test (VCP). In the VCP test, subjects pointed to a remembered target following passive whole body rotation in the dark. In the first experiment, subjects performed VCP before and after wearing 0.5X minifying lenses that adaptively attenuate horizontal VOR gain. Results showed that adaptive reduction in horizontal VOR gain was accompanied by a commensurate change in VCP performance. In the second experiment, bilaterally labyrinthine deficient (LD) subjects were tested to confirm that vestibular cues were central to the spatial coding of both eye and hand movements during VCP. LD subjects performed significantly worse than normal subjects. These results demonstrate that adaptive change in VOR can lead to alterations in manual target localization.

Manduca sexta recognition and resistance among allopolyploid Nicotiana host plants

PubMed Central

Lou, Yonggen; Baldwin, Ian T.

2003-01-01

Allopolyploid speciation occurs instantly when the genomes of different species combine to produce self-fertile offspring and has played a central role in the evolution of higher plants, but its consequences for adaptive responses are unknown. We compare herbivore-recognition and -resistance responses of the diploid species and putative ancestral parent Nicotiana attenuata with those of the two derived allopolyploid species Nicotiana clevelandii and Nicotiana bigelovii. Manduca sexta larvae attack all three species, and in N. attenuata attack is recognized when larval oral secretions are introduced to wounds during feeding, resulting in a jasmonate burst, a systemic amplification of trypsin inhibitor accumulation, and a release of volatile organic compounds, which function as a coordinated defense response that slows caterpillar growth and increases the probability of their being attacked. Most aspects of this recognition response are retained with modifications in one allotetraploid (N. bigelovii) but lost in the other (N. clevelandii). Differences between diploid and tetraploid species were apparent in delays (maximum 1 and 0.5 h, respectively) in the jasmonate burst, the elicitation of trypsin inhibitors and release of volatile organic compounds, and the constitutive levels of nicotine, trypsin inhibitors, diterpene glycosides, rutin, and caffeoylputrescine in the leaves. Resistance to M. sexta larvae attack was most strongly associated with diterpene glycosides, which were higher in the diploid than in the two allotetraploid species. Because M. sexta elicitors differentially regulate a large proportion of the N. attenuata transcriptome, we propose that these species are suited for the study of the evolution of adaptive responses requiring trans-activation mechanisms. PMID:14530394

Adaptive laser conditioning of reflective thin film based on photo thermal lens probe

NASA Astrophysics Data System (ADS)

Liu, Zhichao; Zheng, Yi; Zhang, Qinghua; Pan, Feng; Wei, Yaowei; Wang, Jian; Xu, Qiao

2017-12-01

A novel laser conditioning (LC) concept that performs adaptive control of exposure fluence is proposed. As photo-thermal absorption effect can discover defects responsible for laser-induced damage of reflective thin film, in situ photo-thermal lens probe is introduced in conventional LC procedure to detect defects during raster-scanning. The absorptance signal is fed back to guide the adaptive control of exposure fluence. By this method, the damage risk accompanying with LC can be reduced to a rather low level. In order to test the performance of adaptive laser conditioning (ALC), an experimental setup has been built, and several film samples have been tested. The results show that ALC is effective at reducing laser damage risk.

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera).

PubMed

Snell, Terry W; Shearer, Tonya L; Smith, Hilary A; Kubanek, Julia; Gribble, Kristin E; Welch, David B Mark

2009-09-09

repeats are kept nearly identical through a process of concerted evolution. Information-rich molecules like surface glycoproteins are well adapted for chemical communication and aquatic animals may have evolved signaling systems based on these compounds, whereas insects use cuticular hydrocarbons. Owing to its critical role in mating, the mate recognition pheromone gene will be a useful molecular marker for exploring the mechanisms and rates of selection and the evolution of reproductive isolation and speciation using rotifers as a model system. The phylogenetic variation in the mate recognition pheromone gene can now be studied in conjunction with the large amount of ecological and population genetic data being gathered for the Brachionus plicatilis species complex to understand better the evolutionary drivers of cryptic speciation.

The Legal Recognition of Sign Languages

ERIC Educational Resources Information Center

De Meulder, Maartje

2015-01-01

This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

Comparison of the neural correlates of retrieval success in tests of cued recall and recognition memory.

PubMed

Okada, Kayoko; Vilberg, Kaia L; Rugg, Michael D

2012-03-01

The neural correlates of successful retrieval on tests of word stem recall and recognition memory were compared. In the recall test, subjects viewed word stems, half of which were associated with studied items and half with unstudied items, and for each stem attempted to recall a corresponding study word. In the recognition test, old/new judgments were made on old and new words. The neural correlates of successful retrieval were identified by contrasting activity elicited by correctly endorsed test items. Old > new effects common to the two tasks were found in medial and lateral parietal and right entorhinal cortex. Common new > old effects were identified in medial and left frontal cortex, and left anterior intra-parietal sulcus. Greater old > new effects were evident for cued recall in inferior parietal regions abutting those demonstrating common effects, whereas larger new > old effects were found for recall in left frontal cortex and the anterior cingulate. New > old effects were also found for the recall task in right lateral anterior prefrontal cortex, where they were accompanied by old > new effects during recognition. It is concluded that successful recall and recognition are associated with enhanced activity in a common set of recollection-sensitive parietal regions, and that the greater activation in these regions during recall reflects the greater dependence of that task on recollection. Larger new > old effects during recall are interpreted as reflections of the greater opportunity for iterative retrieval attempts when retrieval cues are partial rather than copy cues. Copyright © 2011 Wiley Periodicals, Inc.

Comparison of the neural correlates of retrieval success in tests of cued recall and recognition memory

PubMed Central

Okada, Kayoko; Vilberg, Kaia L.; Rugg, Michael D.

2011-01-01

The neural correlates of successful retrieval on tests of word stem recall and recognition memory were compared. In the recall test, subjects viewed word stems, half of which were associated with studied items and half with unstudied items, and for each stem attempted to recall a corresponding study word. In the recognition test, old/new judgments were made on old and new words. The neural correlates of successful retrieval were identified by contrasting activity elicited by correctly endorsed test items. Old > new effects common to the two tasks were found in medial and lateral parietal, and right entorhinal cortex. Common new > old effects were identified in medial and left frontal cortex, and left anterior intra-parietal sulcus. Greater old > new effects were evident for cued recall in inferior parietal regions abutting those demonstrating common effects, whereas larger new > old effects were found for recall in left frontal cortex and the anterior cingulate. New > old effects were also found for the recall task in right lateral anterior prefrontal cortex, where they were accompanied by old > new effects during recognition. It is concluded that successful recall and recognition are associated with enhanced activity in a common set of recollection-sensitive parietal regions, and that the greater activation in these regions during recall reflects the greater dependence of that task on recollection. Larger new > old effects during recall are interpreted as reflections of the greater opportunity for iterative retrieval attempts when retrieval cues are partial rather than copy cues. PMID:21455941

Sibling recognition and the development of identity: intersubjective consequences of sibling differentiation in the sister relationship.

PubMed

Vivona, Jeanine M

2013-01-01

Identity is, among other things, a means to adapt to the others around whom one must fit. Psychoanalytic theory has highlighted ways in which the child fits in by emulating important others, especially through identification. Alternately, the child may fit into the family and around important others through differentiation, an unconscious process that involves developing or accentuating qualities and desires in oneself that are expressly different from the perceived qualities of another person and simultaneously suppressing qualities and desires that are perceived as similar. With two clinical vignettes centered on the sister relationship, the author demonstrates that recognition of identity differences that result from sibling differentiation carries special significance in the sibling relationship and simultaneously poses particular intersubjective challenges. To the extent that the spotlight of sibling recognition delimits the lateral space one may occupy, repeatedly frustrated desires for sibling recognition may have enduring consequences for one's sense of self-worth and expectations of relationships with peers and partners.

Adaptive false memory: Imagining future scenarios increases false memories in the DRM paradigm.

PubMed

Dewhurst, Stephen A; Anderson, Rachel J; Grace, Lydia; van Esch, Lotte

2016-10-01

Previous research has shown that rating words for their relevance to a future scenario enhances memory for those words. The current study investigated the effect of future thinking on false memory using the Deese/Roediger-McDermott (DRM) procedure. In Experiment 1, participants rated words from 6 DRM lists for relevance to a past or future event (with or without planning) or in terms of pleasantness. In a surprise recall test, levels of correct recall did not vary between the rating tasks, but the future rating conditions led to significantly higher levels of false recall than the past and pleasantness conditions did. Experiment 2 found that future rating led to higher levels of false recognition than did past and pleasantness ratings but did not affect correct recognition. The effect in false recognition was, however, eliminated when DRM items were presented in random order. Participants in Experiment 3 were presented with both DRM lists and lists of unrelated words. Future rating increased levels of false recognition for DRM lures but did not affect correct recognition for DRM or unrelated lists. The findings are discussed in terms of the view that false memories can be associated with adaptive memory functions.

Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition †

PubMed Central

Janko, Vito

2017-01-01

The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301

Adaptive and perceptual learning technologies in medical education and training.

PubMed

Kellman, Philip J

2013-10-01

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Specific recognition of reproductive parasite workers by nest-entrance guards in the bumble bee Bombus terrestris.

PubMed

Blacher, Pierre; Boreggio, Laurie; Leroy, Chloé; Devienne, Paul; Châline, Nicolas; Chameron, Stéphane

2013-12-10

The impact of social parasites on their hosts' fitness is a strong selective pressure that can lead to the evolution of adapted defence strategies. Guarding the nest to prevent the intrusion of parasites is a widespread response of host species. If absolute rejection of strangers provides the best protection against parasites, more fine-tuned strategies can prove more adaptive. Guarding is indeed costly and not all strangers constitute a real threat. That is particularly true for worker reproductive parasitism in social insects since only a fraction of non-nestmate visitors, the fertile ones, can readily engage in parasitic reproduction. Guards should thus be more restrictive towards fertile than sterile non-nestmate workers. We here tested this hypothesis by examining the reaction of nest-entrance guards towards nestmate and non-nestmate workers with varying fertility levels in the bumble bee Bombus terrestris. Because social recognition in social insects mainly relies on cuticular lipids (CLs), chemical analysis was also conducted to examine whether workers' CLs could convey the relevant information upon which guards could base their decision. We thus aimed to determine whether an adapted defensive strategy to worker reproductive parasitism has evolved in B. terrestris colonies. Chemical analysis revealed that the cuticular chemical profiles of workers encode information about both their colony membership and their current fertility, therefore providing potential recognition cues for a suitable adjustment of the guards' defensive decisions. We found that guards were similarly tolerant towards sterile non-nestmate workers than towards nestmate workers. However, as predicted, guards responded more aggressively towards fertile non-nestmates. Our results show that B. terrestris guards discriminate non-nestmates that differ in their reproductive potential and respond more strongly to the individuals that are a greatest threat for the colony. Cuticular hydrocarbons are

Specific recognition of reproductive parasite workers by nest-entrance guards in the bumble bee Bombus terrestris

PubMed Central

2013-01-01

Background The impact of social parasites on their hosts’ fitness is a strong selective pressure that can lead to the evolution of adapted defence strategies. Guarding the nest to prevent the intrusion of parasites is a widespread response of host species. If absolute rejection of strangers provides the best protection against parasites, more fine-tuned strategies can prove more adaptive. Guarding is indeed costly and not all strangers constitute a real threat. That is particularly true for worker reproductive parasitism in social insects since only a fraction of non-nestmate visitors, the fertile ones, can readily engage in parasitic reproduction. Guards should thus be more restrictive towards fertile than sterile non-nestmate workers. We here tested this hypothesis by examining the reaction of nest-entrance guards towards nestmate and non-nestmate workers with varying fertility levels in the bumble bee Bombus terrestris. Because social recognition in social insects mainly relies on cuticular lipids (CLs), chemical analysis was also conducted to examine whether workers’ CLs could convey the relevant information upon which guards could base their decision. We thus aimed to determine whether an adapted defensive strategy to worker reproductive parasitism has evolved in B. terrestris colonies. Results Chemical analysis revealed that the cuticular chemical profiles of workers encode information about both their colony membership and their current fertility, therefore providing potential recognition cues for a suitable adjustment of the guards’ defensive decisions. We found that guards were similarly tolerant towards sterile non-nestmate workers than towards nestmate workers. However, as predicted, guards responded more aggressively towards fertile non-nestmates. Conclusion Our results show that B. terrestris guards discriminate non-nestmates that differ in their reproductive potential and respond more strongly to the individuals that are a greatest threat for

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

PubMed Central

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-01-01

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation. PMID:27999337

An LRR/Malectin Receptor-Like Kinase Mediates Resistance to Non-adapted and Adapted Powdery Mildew Fungi in Barley and Wheat

PubMed Central

Rajaraman, Jeyaraman; Douchkov, Dimitar; Hensel, Götz; Stefanato, Francesca L.; Gordon, Anna; Ereful, Nelzo; Caldararu, Octav F.; Petrescu, Andrei-Jose; Kumlehn, Jochen; Boyd, Lesley A.; Schweizer, Patrick

2016-01-01

Pattern recognition receptors (PRRs) belonging to the multigene family of receptor-like kinases (RLKs) are the sensing devices of plants for microbe- or pathogen-associated molecular patterns released from microbial organisms. Here we describe Rnr8 (for Required for non-host resistance 8) encoding HvLEMK1, a LRR-malectin domain-containing transmembrane RLK that mediates non-host resistance of barley to the non-adapted wheat powdery mildew fungus Blumeria graminis f.sp. tritici. Transgenic barley lines with silenced HvLEMK1 allow entry and colony growth of the non-adapted pathogen, although sporulation was reduced and final colony size did not reach that of the adapted barley powdery mildew fungus B. graminis f.sp. hordei. Transient expression of the barley or wheat LEMK1 genes enhanced resistance in wheat to the adapted wheat powdery mildew fungus while expression of the same genes did not protect barley from attack by the barley powdery mildew fungus. The results suggest that HvLEMK1 is a factor mediating non-host resistance in barley and quantitative host resistance in wheat to the wheat powdery mildew fungus. PMID:28018377

39 CFR 320.7 - Suspension for advertisements accompanying parcels or periodicals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 39 Postal Service 1 2010-07-01 2010-07-01 false Suspension for advertisements accompanying parcels or periodicals. 320.7 Section 320.7 Postal Service UNITED STATES POSTAL SERVICE RESTRICTIONS ON PRIVATE CARRIAGE OF LETTERS SUSPENSION OF THE PRIVATE EXPRESS STATUTES § 320.7 Suspension for advertisements accompanying parcels or periodicals. (a) Th...

41 CFR 101-25.110-3 - Tires accompanying new motor vehicles.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Tires accompanying new...-GENERAL 25.1-General Policies § 101-25.110-3 Tires accompanying new motor vehicles. The tire... vehicle manufacturer or his designee to maintain a record of tires on or in each vehicle shipped by him...

Super Normal Vector for Human Activity Recognition with Depth Cameras.

PubMed

Yang, Xiaodong; Tian, YingLi

2017-05-01

The advent of cost-effectiveness and easy-operation depth cameras has facilitated a variety of visual recognition tasks including human activity recognition. This paper presents a novel framework for recognizing human activities from video sequences captured by depth cameras. We extend the surface normal to polynormal by assembling local neighboring hypersurface normals from a depth sequence to jointly characterize local motion and shape information. We then propose a general scheme of super normal vector (SNV) to aggregate the low-level polynormals into a discriminative representation, which can be viewed as a simplified version of the Fisher kernel representation. In order to globally capture the spatial layout and temporal order, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time cells. In the extensive experiments, the proposed approach achieves superior performance to the state-of-the-art methods on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

Neural-network classifiers for automatic real-world aerial image recognition

NASA Astrophysics Data System (ADS)

Greenberg, Shlomo; Guterman, Hugo

1996-08-01

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

Neural-network classifiers for automatic real-world aerial image recognition.

PubMed

Greenberg, S; Guterman, H

1996-08-10

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

Development of equally intelligible Telugu sentence-lists to test speech recognition in noise.

PubMed

Tanniru, Kishore; Narne, Vijaya Kumar; Jain, Chandni; Konadath, Sreeraj; Singh, Niraj Kumar; Sreenivas, K J Ramadevi; K, Anusha

2017-09-01

To develop sentence lists in the Telugu language for the assessment of speech recognition threshold (SRT) in the presence of background noise through identification of the mean signal-to-noise ratio required to attain a 50% sentence recognition score (SRTn). This study was conducted in three phases. The first phase involved the selection and recording of Telugu sentences. In the second phase, 20 lists, each consisting of 10 sentences with equal intelligibility, were formulated using a numerical optimisation procedure. In the third phase, the SRTn of the developed lists was estimated using adaptive procedures on individuals with normal hearing. A total of 68 native Telugu speakers with normal hearing participated in the study. Of these, 18 (including the speakers) performed on various subjective measures in first phase, 20 performed on sentence/word recognition in noise for second phase and 30 participated in the list equivalency procedures in third phase. In all, 15 lists of comparable difficulty were formulated as test material. The mean SRTn across these lists corresponded to -2.74 (SD = 0.21). The developed sentence lists provided a valid and reliable tool to measure SRTn in Telugu native speakers.

Cardiovascular adaptations to marathon running : the marathoner's heart.

PubMed

Thompson, Paul D

2007-01-01

Endurance exercise training produces a series of cardiac adaptations including resting bradycardia, first and second degree atrioventricular block, increased intolerance to orthostatic stress, and enlargement of the left ventricular walls and of all cardiac chambers. Cardiac dimensions may be increased beyond the upper limits of normal and some endurance athletes demonstrate mild reductions in estimated left ventricular ejection fraction. Among athletes, such adaptations occur primarily in well trained endurance athletes. Clinicians should be aware of the cardiac changes accompanying endurance training to avoid unnecessary evaluation of physiological changes. On the other hand, the presence of conduction abnormalities or cardiac enlargement in low level or recreational athletes should prompt a search for pathological causes. Many of these findings were presented in the 1977 report on the marathon and have simply been better defined with subsequent studies.

Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

PubMed

Bennetts, Rachel J; Mole, Joseph; Bate, Sarah

2017-09-01

Face recognition abilities vary widely. While face recognition deficits have been reported in children, it is unclear whether superior face recognition skills can be encountered during development. This paper presents O.B., a 14-year-old female with extraordinary face recognition skills: a "super-recognizer" (SR). O.B. demonstrated exceptional face-processing skills across multiple tasks, with a level of performance that is comparable to adult SRs. Her superior abilities appear to be specific to face identity: She showed an exaggerated face inversion effect and her superior abilities did not extend to object processing or non-identity aspects of face recognition. Finally, an eye-movement task demonstrated that O.B. spent more time than controls examining the nose - a pattern previously reported in adult SRs. O.B. is therefore particularly skilled at extracting and using identity-specific facial cues, indicating that face and object recognition are dissociable during development, and that super recognition can be detected in adolescence.

Ultra-fast ipsilateral DPOAE adaptation not modulated by attention?

NASA Astrophysics Data System (ADS)

Dalhoff, Ernst; Zelle, Dennis; Gummer, Anthony W.

2018-05-01

Efferent stimulation of outer hair cells is supposed to attenuate cochlear amplification of sound waves and is accompanied by reduced DPOAE amplitudes. Recently, a method using two subsequent f2 pulses during presentation of a longer f1 pulse was introduced to measure fast ipsilateral adaptation effects on separated DPOAE components. Compensating primary-tone onsets for their latencies at the f2-tonotopic place, the average adaptation measured in four normal-hearing subjects was 5.0 dB with a time constant below 5 ms. In the present study, two experiments were performed to determine the origin of this ultra-fast ipsilateral adaptation effect. The first experiment measured ultra-fast ipsilateral adaptation using a two-pulse paradigm at three frequencies in the four subjects, while controlling for visual attention of the subjects. The other experiment also controlled for visual attention, but utilized a sequence of f2 short pulses in the presence of a continuous f1 tone to sample ipsilateral adaptation effects with longer time constants in eight subjects. In the first experiment, no significant change in the ultra-fast adaptation between non-directed attention and visual attention could be detected. In contrast, the second experiment revealed significant changes in the magnitude of the slower ipsilateral adaptation in the visual-attention condition. In conclusion, the lack of an attentional influence indicates that the ultra-fast ipsilateral DPOAE adaptation is not solely mediated by the medial olivocochlear reflex.

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.

31 CFR 538.511 - Accompanied baggage authorized.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 31 Money and Finance:Treasury 3 2013-07-01 2013-07-01 false Accompanied baggage authorized. 538.511 Section 538.511 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... only articles that are necessary for personal use incident to travel, are not intended for any other...

31 CFR 538.511 - Accompanied baggage authorized.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 31 Money and Finance:Treasury 3 2014-07-01 2014-07-01 false Accompanied baggage authorized. 538.511 Section 538.511 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... only articles that are necessary for personal use incident to travel, are not intended for any other...

31 CFR 538.511 - Accompanied baggage authorized.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Accompanied baggage authorized. 538.511 Section 538.511 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... only articles that are necessary for personal use incident to travel, are not intended for any other...

31 CFR 538.511 - Accompanied baggage authorized.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Accompanied baggage authorized. 538.511 Section 538.511 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... only articles that are necessary for personal use incident to travel, are not intended for any other...

31 CFR 538.511 - Accompanied baggage authorized.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 31 Money and Finance:Treasury 3 2012-07-01 2012-07-01 false Accompanied baggage authorized. 538.511 Section 538.511 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... only articles that are necessary for personal use incident to travel, are not intended for any other...

Darwin revisited: The vagus nerve is a causal element in controlling recognition of other's emotions.

PubMed

Colzato, Lorenza S; Sellaro, Roberta; Beste, Christian

2017-07-01

Charles Darwin proposed that via the vagus nerve, the tenth cranial nerve, emotional facial expressions are evolved, adaptive and serve a crucial communicative function. In line with this idea, the later-developed polyvagal theory assumes that the vagus nerve is the key phylogenetic substrate that regulates emotional and social behavior. The polyvagal theory assumes that optimal social interaction, which includes the recognition of emotion in faces, is modulated by the vagus nerve. So far, in humans, it has not yet been demonstrated that the vagus plays a causal role in emotion recognition. To investigate this we employed transcutaneous vagus nerve stimulation (tVNS), a novel non-invasive brain stimulation technique that modulates brain activity via bottom-up mechanisms. A sham/placebo-controlled, randomized cross-over within-subjects design was used to infer a causal relation between the stimulated vagus nerve and the related ability to recognize emotions as indexed by the Reading the Mind in the Eyes Test in 38 healthy young volunteers. Active tVNS, compared to sham stimulation, enhanced emotion recognition for easy items, suggesting that it promoted the ability to decode salient social cues. Our results confirm that the vagus nerve is causally involved in emotion recognition, supporting Darwin's argumentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive Suppression of Noise in Voice Communications

NASA Technical Reports Server (NTRS)

Kozel, David; DeVault, James A.; Birr, Richard B.

2003-01-01

A subsystem for the adaptive suppression of noise in a voice communication system effects a high level of reduction of noise that enters the system through microphones. The subsystem includes a digital signal processor (DSP) plus circuitry that implements voice-recognition and spectral- manipulation techniques. The development of the adaptive noise-suppression subsystem was prompted by the following considerations: During processing of the space shuttle at Kennedy Space Center, voice communications among test team members have been significantly impaired in several instances because some test participants have had to communicate from locations with high ambient noise levels. Ear protection for the personnel involved is commercially available and is used in such situations. However, commercially available noise-canceling microphones do not provide sufficient reduction of noise that enters through microphones and thus becomes transmitted on outbound communication links.

Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

PubMed

Crawford, D C; Bell, D S; Bamber, J C

1993-01-01

A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

Non-native Listeners’ Recognition of High-Variability Speech Using PRESTO

PubMed Central

Tamati, Terrin N.; Pisoni, David B.

2015-01-01

Background Natural variability in speech is a significant challenge to robust successful spoken word recognition. In everyday listening environments, listeners must quickly adapt and adjust to multiple sources of variability in both the signal and listening environments. High-variability speech may be particularly difficult to understand for non-native listeners, who have less experience with the second language (L2) phonological system and less detailed knowledge of sociolinguistic variation of the L2. Purpose The purpose of this study was to investigate the effects of high-variability sentences on non-native speech recognition and to explore the underlying sources of individual differences in speech recognition abilities of non-native listeners. Research Design Participants completed two sentence recognition tasks involving high-variability and low-variability sentences. They also completed a battery of behavioral tasks and self-report questionnaires designed to assess their indexical processing skills, vocabulary knowledge, and several core neurocognitive abilities. Study Sample Native speakers of Mandarin (n = 25) living in the United States recruited from the Indiana University community participated in the current study. A native comparison group consisted of scores obtained from native speakers of English (n = 21) in the Indiana University community taken from an earlier study. Data Collection and Analysis Speech recognition in high-variability listening conditions was assessed with a sentence recognition task using sentences from PRESTO (Perceptually Robust English Sentence Test Open-Set) mixed in 6-talker multitalker babble. Speech recognition in low-variability listening conditions was assessed using sentences from HINT (Hearing In Noise Test) mixed in 6-talker multitalker babble. Indexical processing skills were measured using a talker discrimination task, a gender discrimination task, and a forced-choice regional dialect categorization task. Vocabulary

A new time-adaptive discrete bionic wavelet transform for enhancing speech from adverse noise environment

NASA Astrophysics Data System (ADS)

Palaniswamy, Sumithra; Duraisamy, Prakash; Alam, Mohammad Showkat; Yuan, Xiaohui

2012-04-01

Automatic speech processing systems are widely used in everyday life such as mobile communication, speech and speaker recognition, and for assisting the hearing impaired. In speech communication systems, the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. To obtain an intelligible speech signal and one that is more pleasant to listen, noise reduction is essential. In this paper a new Time Adaptive Discrete Bionic Wavelet Thresholding (TADBWT) scheme is proposed. The proposed technique uses Daubechies mother wavelet to achieve better enhancement of speech from additive non- stationary noises which occur in real life such as street noise and factory noise. Due to the integration of human auditory system model into the wavelet transform, bionic wavelet transform (BWT) has great potential for speech enhancement which may lead to a new path in speech processing. In the proposed technique, at first, discrete BWT is applied to noisy speech to derive TADBWT coefficients. Then the adaptive nature of the BWT is captured by introducing a time varying linear factor which updates the coefficients at each scale over time. This approach has shown better performance than the existing algorithms at lower input SNR due to modified soft level dependent thresholding on time adaptive coefficients. The objective and subjective test results confirmed the competency of the TADBWT technique. The effectiveness of the proposed technique is also evaluated for speaker recognition task under noisy environment. The recognition results show that the TADWT technique yields better performance when compared to alternate methods specifically at lower input SNR.

Prenatal exposure to PCP produces behavioral deficits accompanied by the overexpression of GLAST in the prefrontal cortex of postpubertal mice.

PubMed

Lu, Lingling; Mamiya, Takayoshi; Lu, Ping; Toriumi, Kazuya; Mouri, Akihiro; Hiramatsu, Masayuki; Zou, Li-Bo; Nabeshima, Toshitaka

2011-06-20

Altered glutamatergic neurotransmission in the prefrontal cortex (PFC) has been implicated in a myriad of neuropsychiatric disorders. We previously reported that prenatal exposure to PCP produced long-lasting behavioral deficits, accompanied by the abnormal expression and dysfunction of NMDA receptors. In addition, these behavioral changes were attenuated by clozapine treatment. However, whether the prenatal exposure adversely affects pre-synaptic glutamatergic neurotransmission in postpubertal mice remains unknown. In the present study, we investigated the involvement of prefrontal glutamatergic neurotransmission in the impairment of cognitive and emotional behavior after prenatal PCP treatment (5mg/kg/day) from E6 to E18 in mice. The PCP-treated mice showed an impairment of recognition memory in a novel object recognition test and enhancement of immobility in a forced swimming test at 8 weeks of age. Moreover, the prenatal treatment reduced the extracellular glutamate level, but increased the expression of a glial glutamate transporter (GLAST) in the PFC. The microinjection of DL-threo-β-benzyloxyaspartate (DL-TBOA, 10 nmol/site/bilaterally), a potent blocker of glutamate transporters, reversed these behavioral deficits by enhancing the prefrontal glutamatergic neurotransmission. Taken together, prenatal exposure to PCP produced impairments of long-term memory and emotional function which are associated with abnormalities of pre-synaptic glutamate transmission in the PFC of postpubertal mice. These findings suggest the prenatal inhibition of NMDA receptor function to contribute partly to the pathophysiology of neurodevelopment-related disorders, such as schizophrenia. Copyright © 2011 Elsevier B.V. All rights reserved.

31 CFR 545.507 - Accompanied baggage authorized.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Accompanied baggage authorized. 545.507 Section 545.507 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... that are necessary for personal use incident to travel, that are not intended for any other person or...

31 CFR 560.507 - Accompanied baggage authorized.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 31 Money and Finance:Treasury 3 2012-07-01 2012-07-01 false Accompanied baggage authorized. 560.507 Section 560.507 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... for personal use incident to travel, not intended for any other person or for sale, and are not...

Challenging ocular image recognition

NASA Astrophysics Data System (ADS)

Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

2011-06-01

Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Facial Emotion Processing and Social Adaptation in Adults with and without Autism Spectrum Disorder

ERIC Educational Resources Information Center

Garcia-Villamisar, Domingo; Rojahn, Johannes; Zaja, Rebecca H.; Jodra, Marina

2010-01-01

Individuals with autism spectrum disorder (ASD) and individuals with intellectual disabilities without ASD have limited facial emotion recognition abilities, which may adversely impact social adjustment and other adaptive behavior. This study was designed to examine this relationship in adults with and without ASD. Two groups of adults with…

Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.

PubMed

Notarnicola, Ippolito; Petrucci, Cristina; De Jesus Barbosa, Maria Rosimar; Giorgi, Fabio; Stievano, Alessandro; Rocco, Gennaro; Lancia, Loreto

2017-06-01

This study aimed to analyse the concept of "complex adaptive systems." The construct is still nebulous in the literature, and a further explanation of the idea is needed to have a shared knowledge of it. A concept analysis was conducted utilizing Rodgers evolutionary method. The inclusive years of bibliographic search started from 2005 to 2015. The search was conducted at PubMed©, CINAHL© (EBSCO host©), Scopus©, Web of Science©, and Academic Search Premier©. Retrieved papers were critically analysed to explore the attributes, antecedents, and consequences of the concept. Moreover, surrogates, related terms, and a pattern recognition scheme were identified. The concept analysis showed that complex systems are adaptive and have the ability to process information. They can adapt to the environment and consequently evolve. Nursing is a complex adaptive system, and the nursing profession in practice exhibits complex adaptive system characteristics. Complexity science through complex adaptive systems provides new ways of seeing and understanding the mechanisms that underpin the nursing profession. © 2017 John Wiley & Sons Australia, Ltd.

Epistatically Interacting Substitutions Are Enriched during Adaptive Protein Evolution

PubMed Central

Gong, Lizhi Ian; Bloom, Jesse D.

2014-01-01

Most experimental studies of epistasis in evolution have focused on adaptive changes—but adaptation accounts for only a portion of total evolutionary change. Are the patterns of epistasis during adaptation representative of evolution more broadly? We address this question by examining a pair of protein homologs, of which only one is subject to a well-defined pressure for adaptive change. Specifically, we compare the nucleoproteins from human and swine influenza. Human influenza is under continual selection to evade recognition by acquired immune memory, while swine influenza experiences less such selection due to the fact that pigs are less likely to be infected with influenza repeatedly in a lifetime. Mutations in some types of immune epitopes are therefore much more strongly adaptive to human than swine influenza—here we focus on epitopes targeted by human cytotoxic T lymphocytes. The nucleoproteins of human and swine influenza possess nearly identical numbers of such epitopes. However, mutations in these epitopes are fixed significantly more frequently in human than in swine influenza, presumably because these epitope mutations are adaptive only to human influenza. Experimentally, we find that epistatically constrained mutations are fixed only in the adaptively evolving human influenza lineage, where they occur at sites that are enriched in epitopes. Overall, our results demonstrate that epistatically interacting substitutions are enriched during adaptation, suggesting that the prevalence of epistasis is dependent on the underlying evolutionary forces at play. PMID:24811236

Noise adaptation in integrate-and fire neurons.

PubMed

Rudd, M E; Brown, L G

1997-07-01

The statistical spiking response of an ensemble of identically prepared stochastic integrate-and-fire neurons to a rectangular input current plus gaussian white noise is analyzed. It is shown that, on average, integrate-and-fire neurons adapt to the root-mean-square noise level of their input. This phenomenon is referred to as noise adaptation. Noise adaptation is characterized by a decrease in the average neural firing rate and an accompanying decrease in the average value of the generator potential, both of which can be attributed to noise-induced resets of the generator potential mediated by the integrate-and-fire mechanism. A quantitative theory of noise adaptation in stochastic integrate-and-fire neurons is developed. It is shown that integrate-and-fire neurons, on average, produce transient spiking activity whenever there is an increase in the level of their input noise. This transient noise response is either reduced or eliminated over time, depending on the parameters of the model neuron. Analytical methods are used to prove that nonleaky integrate-and-fire neurons totally adapt to any constant input noise level, in the sense that their asymptotic spiking rates are independent of the magnitude of their input noise. For leaky integrate-and-fire neurons, the long-run noise adaptation is not total, but the response to noise is partially eliminated. Expressions for the probability density function of the generator potential and the first two moments of the potential distribution are derived for the particular case of a nonleaky neuron driven by gaussian white noise of mean zero and constant variance. The functional significance of noise adaptation for the performance of networks comprising integrate-and-fire neurons is discussed.

Haloarcula hispanica CRISPR authenticates PAM of a target sequence to prime discriminative adaptation

PubMed Central

Li, Ming; Wang, Rui; Xiang, Hua

2014-01-01

The prokaryotic immune system CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated genes) adapts to foreign invaders by acquiring their short deoxyribonucleic acid (DNA) fragments as spacers, which guide subsequent interference to foreign nucleic acids based on sequence matching. The adaptation mechanism avoiding acquiring ‘self’ DNA fragments is poorly understood. In Haloarcula hispanica, we previously showed that CRISPR adaptation requires being primed by a pre-existing spacer partially matching the invader DNA. Here, we further demonstrate that flanking a fully-matched target sequence, a functional PAM (protospacer adjacent motif) is still required to prime adaptation. Interestingly, interference utilizes only four PAM sequences, whereas adaptation-priming tolerates as many as 23 PAM sequences. This relaxed PAM selectivity explains how adaptation-priming maximizes its tolerance of PAM mutations (that escape interference) while avoiding mis-targeting the spacer DNA within CRISPR locus. We propose that the primed adaptation, which hitches and cooperates with the interference pathway, distinguishes target from non-target by CRISPR ribonucleic acid guidance and PAM recognition. PMID:24803673

30 CFR 250.221 - What environmental monitoring information must accompany the EP?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 2 2011-07-01 2011-07-01 false What environmental monitoring information must... monitoring information must accompany the EP? The following environmental monitoring information, as applicable, must accompany your EP: (a) Monitoring systems. A description of any existing and planned...

Probing the Energetics of Antigen-Antibody Recognition by Titration Microcalorimetry

PubMed

Jelesarov; Leder; Bosshard

1996-06-01

Our understanding of the energetics that govern antigen-antibody recognition lags behind the increasingly rapid accumulation of structural information on antigen-antibody complexes. Thanks to the development of highly sensitive microcalorimeters, the thermodynamic parameters of antigen-antibody interactions can now be measured with precision and using only nanomole quantities of protein. The method of choice is isothermal titration calorimetry, in which a solution of the antibody (or antigen) is titrated with small aliquots of the antigen (or antibody) and the heat change accompanying the formation of the antigen-antibody complex is measured with a sensitivity as high as 0.1 μcal s-1. The free energy of binding (DeltaG), the binding enthalpy (DeltaH), and the binding entropy (DeltaS) are usually obtained from a single experiment, and no spectroscopic or radioactive label must be introduced into the antigen or antibody. The often large and negative change in heat capacity (DeltaCp) accompanying the formation of an antigen-antibody complex is obtained from DeltaH measured at different temperatures. The basic theory and the principle of the measurements are reviewed and illustrated by examples. The thermodynamic parameters relate to the dynamic physical forces that govern the association of the freely moving antigen and antibody into a well-structured and unique complex. This information complements the static picture of the antigen-antibody complex that results from X-ray diffraction analysis. Attempts to correlate dynamic and static aspects are discussed briefly.

Concept and design philosophy of a person-accompanying robot

NASA Astrophysics Data System (ADS)

Mizoguchi, Hiroshi; Shigehara, Takaomi; Goto, Yoshiyasu; Hidai, Ken-ichi; Mishima, Taketoshi

1999-01-01

This paper proposes a person accompanying robot as a novel human collaborative robot. The person accompanying robot is such legged mobile robot that is possible to follow the person utilizing its vision. towards future aging society, human collaboration and human support are required as novel applications of robots. Such human collaborative robots share the same space with humans. But conventional robots are isolated from humans and lack the capability to observe humans. Study on human observing function of robot is crucial to realize novel robot such as service and pet robot. To collaborate and support humans properly human collaborative robot must have capability to observe and recognize humans. Study on human observing function of robot is crucial to realize novel robot such as service and pet robot. The authors are currently implementing a prototype of the proposed accompanying robot.As a base for the human observing function of the prototype robot, we have realized face tracking utilizing skin color extraction and correlation based tracking. We also develop a method for the robot to pick up human voice clearly and remotely by utilizing microphone arrays. Results of these preliminary study suggest feasibility of the proposed robot.

Real-time implementation of an interactive jazz accompaniment system

NASA Astrophysics Data System (ADS)

Deshpande, Nikhil

Modern computational algorithms and digital signal processing (DSP) are able to combine with human performers without forced or predetermined structure in order to create dynamic and real-time accompaniment systems. With modern computing power and intelligent algorithm layout and design, it is possible to achieve more detailed auditory analysis of live music. Using this information, computer code can follow and predict how a human's musical performance evolves, and use this to react in a musical manner. This project builds a real-time accompaniment system to perform together with live musicians, with a focus on live jazz performance and improvisation. The system utilizes a new polyphonic pitch detector and embeds it in an Ableton Live system - combined with Max for Live - to perform elements of audio analysis, generation, and triggering. The system also relies on tension curves and information rate calculations from the Creative Artificially Intuitive and Reasoning Agent (CAIRA) system to help understand and predict human improvisation. These metrics are vital to the core system and allow for extrapolated audio analysis. The system is able to react dynamically to a human performer, and can successfully accompany the human as an entire rhythm section.

Unrealistic optimism and 'nosognosia': illness recognition in the healthy brain.

PubMed

McKay, Ryan; Buchmann, Andreas; Germann, Nicole; Yu, Shancong; Brugger, Peter

2014-12-01

At the centenary of research on anosognosia, the time seems ripe to supplement work in anosognosic patients with empirical studies on nosognosia in healthy participants. To this end, we adopted a signal detection framework to investigate the lateralized recognition of illness words--an operational measure of nosognosia--in healthy participants. As positively biased reports about one's current health status (anosognosia) and future health status (unrealistic optimism) have both been associated with deficient right hemispheric functioning, and conversely with undisturbed left hemispheric functioning, we hypothesised that more optimistic participants would adopt a more conservative response criterion, and/or display less sensitivity, when identifying illnesses in our nosognosia task; especially harmful illnesses presented to the left hemisphere via the right visual field. Thirty-two healthy right-handed men estimated their own relative risk of contracting a series of illnesses in the future, and then completed a novel computer task assessing their recognition of illness names presented to the left or right visual field. To check that effects were specific to the recognition of illness (rather than reflecting recognition of lexical items per se), we also administered a standard lateralized lexical decision task. Highly optimistic participants tended to be more conservative in detecting illnesses, especially harmful illnesses presented to the right visual field. Contrary to expectation, they were also more sensitive to illness names in this half-field. We suggest that, in evolutionary terms, unrealistic optimism may be an adaptive trait that combines a high perceptual sensitivity to threat with a high threshold for acknowledging its presence. The signal detection approach to nosognosia developed here may open up new avenues for the understanding of anosognosia in neurological patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genetic specificity of face recognition.

PubMed

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Moreland Recognition Program.

ERIC Educational Resources Information Center

Moreland Elementary School District, San Jose, CA.

THE FOLLOWING IS THE FULL TEXT OF THIS DOCUMENT: Recognition for special effort and achievement has been noted as a component of effective schools. Schools in the Moreland School District have effectively improved standards of discipline and achievement by providing forty-six different ways for children to receive positive recognition. Good…

Recognition memory in tree shrew (Tupaia belangeri) after repeated familiarization sessions.

PubMed

Khani, Abbas; Rainer, Gregor

2012-07-01

Recognition memories are formed during perceptual experience and allow subsequent recognition of previously encountered objects as well as their distinction from novel objects. As a consequence, novel objects are generally explored longer than familiar objects by many species. This novelty preference has been documented in rodents using the novel object recognition (NOR) test, as well is in primates including humans using preferential looking time paradigms. Here, we examine novelty preference using the NOR task in tree shrew, a small animal species that is considered to be an intermediary between rodents and primates. Our paradigm consisted of three phases: arena familiarization, object familiarization sessions with two identical objects in the arena and finally a test session following a 24-h retention period with a familiar and a novel object in the arena. We employed two different object familiarization durations: one and three sessions on consecutive days. After three object familiarization sessions, tree shrews exhibited robust preference for novel objects on the test day. This was accompanied by significant reduction in familiar object exploration time, occurring largely between the first and second day of object familiarization. By contrast, tree shrews did not show a significant preference for the novel object after a one-session object familiarization. Nonetheless, they spent significantly less time exploring the familiar object on the test day compared to the object familiarization day, indicating that they did maintain a memory trace for the familiar object. Our study revealed different time courses for familiar object habituation and emergence of novelty preference, suggesting that novelty preference is dependent on well-consolidated memory of the competing familiar object. Taken together, our results demonstrate robust novelty preference of tree shrews, in general similarity to previous findings in rodents and primates. Copyright © 2012 Elsevier B

Adaptation to nonlinear frequency compression in normal-hearing adults: a comparison of training approaches.

PubMed

Dickinson, Ann-Marie; Baker, Richard; Siciliano, Catherine; Munro, Kevin J

2014-10-01

To identify which training approach, if any, is most effective for improving perception of frequency-compressed speech. A between-subject design using repeated measures. Forty young adults with normal hearing were randomly allocated to one of four groups: a training group (sentence or consonant) or a control group (passive exposure or test-only). Test and training material differed in terms of material and speaker. On average, sentence training and passive exposure led to significantly improved sentence recognition (11.0% and 11.7%, respectively) compared with the consonant training group (2.5%) and test-only group (0.4%), whilst, consonant training led to significantly improved consonant recognition (8.8%) compared with the sentence training group (1.9%), passive exposure group (2.8%), and test-only group (0.8%). Sentence training led to improved sentence recognition, whilst consonant training led to improved consonant recognition. This suggests learning transferred between speakers and material but not stimuli. Passive exposure to sentence material led to an improvement in sentence recognition that was equivalent to gains from active training. This suggests that it may be possible to adapt passively to frequency-compressed speech.

Face-space: A unifying concept in face recognition research.

PubMed

Valentine, Tim; Lewis, Michael B; Hills, Peter J

2016-10-01

The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

[Stress adaptive effects after traumatic brain injury].

PubMed

Teryaeva, N B; Moshkin, A V