Effects of Age and Working Memory Capacity on Speech Recognition Performance in Noise Among Listeners With Normal Hearing.

Science.gov (United States)

Gordon-Salant, Sandra; Cole, Stacey Samuels

2016-01-01

This study aimed to determine if younger and older listeners with normal hearing who differ on working memory span perform differently on speech recognition tests in noise. Older adults typically exhibit poorer speech recognition scores in noise than younger adults, which is attributed primarily to poorer hearing sensitivity and more limited working memory capacity in older than younger adults. Previous studies typically tested older listeners with poorer hearing sensitivity and shorter working memory spans than younger listeners, making it difficult to discern the importance of working memory capacity on speech recognition. This investigation controlled for hearing sensitivity and compared speech recognition performance in noise by younger and older listeners who were subdivided into high and low working memory groups. Performance patterns were compared for different speech materials to assess whether or not the effect of working memory capacity varies with the demands of the specific speech test. The authors hypothesized that (1) normal-hearing listeners with low working memory span would exhibit poorer speech recognition performance in noise than those with high working memory span; (2) older listeners with normal hearing would show poorer speech recognition scores than younger listeners with normal hearing, when the two age groups were matched for working memory span; and (3) an interaction between age and working memory would be observed for speech materials that provide contextual cues. Twenty-eight older (61 to 75 years) and 25 younger (18 to 25 years) normal-hearing listeners were assigned to groups based on age and working memory status. Northwestern University Auditory Test No. 6 words and Institute of Electrical and Electronics Engineers sentences were presented in noise using an adaptive procedure to measure the signal-to-noise ratio corresponding to 50% correct performance. Cognitive ability was evaluated with two tests of working memory (Listening

Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex.

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Xie, Shan Juan; Lu, Yu; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2015-07-14

Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV) normalization method using guided filter based single scale retinex (GFSSR) is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

Speech recognition in normal hearing and sensorineural hearing loss as a function of the number of spectral channels

NARCIS (Netherlands)

Baskent, Deniz

Speech recognition by normal-hearing listeners improves as a function of the number of spectral channels when tested with a noiseband vocoder simulating cochlear implant signal processing. Speech recognition by the best cochlear implant users, however, saturates around eight channels and does not

Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex

Directory of Open Access Journals (Sweden)

Shan Juan Xie

2015-07-01

Full Text Available Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc. vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs. In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV normalization method using guided filter based single scale retinex (GFSSR is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

Efficient CEPSTRAL Normalization for Robust Speech Recognition

National Research Council Canada - National Science Library

Liu, Fu-Hua; Stern, Richard M; Huang, Xuedong; Acero, Alejandro

1993-01-01

In this paper we describe and compare the performance of a series of cepstrum-based procedures that enable the CMU SPHINX-II speech recognition system to maintain a high level of recognition accuracy...

Comparing Facial Emotional Recognition in Patients with Borderline Personality Disorder and Patients with Schizotypal Personality Disorder with a Normal Group.

Science.gov (United States)

Farsham, Aida; Abbaslou, Tahereh; Bidaki, Reza; Bozorg, Bonnie

2017-04-01

Objective: No research has been conducted on facial emotional recognition on patients with borderline personality disorder (BPD) and schizotypal personality disorder (SPD). The present study aimed at comparing facial emotion recognition in these patients with the general population. The neurocognitive processing of emotions can show the pathologic style of these 2 disorders. Method: Twenty BPD patients, 16 SPD patients, and 20 healthy individuals were selected by available sampling method. Structural Clinical Interview for Axis II, Millon Personality Inventory, Beck Depression Inventory and Facial Emotional Recognition Test was were conducted for all participants. Discussion: The results of one way ANOVA and Scheffe's post hoc test analysis revealed significant differences in neuropsychology assessment of facial emotional recognition between BPD and SPD patients with normal group (p = 0/001). A significant difference was found in emotion recognition of fear between the 2 groups of BPD and normal population (p = 0/008). A significant difference was observed between SPD patients and control group in emotion recognition of wonder (p = 0/04(. The obtained results indicated a deficit in negative emotion recognition, especially disgust emotion, thus, it can be concluded that these patients have the same neurocognitive profile in the emotion domain.

Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

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Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

2014-03-01

Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

Lexical and age effects on word recognition in noise in normal-hearing children.

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Ren, Cuncun; Liu, Sha; Liu, Haihong; Kong, Ying; Liu, Xin; Li, Shujing

2015-12-01

The purposes of the present study were (1) to examine the lexical and age effects on word recognition of normal-hearing (NH) children in noise, and (2) to compare the word-recognition performance in noise to that in quiet listening conditions. Participants were 213 NH children (age ranged between 3 and 6 years old). Eighty-nine and 124 of the participants were tested in noise and quiet listening conditions, respectively. The Standard-Chinese Lexical Neighborhood Test, which contains lists of words in four lexical categories (i.e., dissyllablic easy (DE), dissyllablic hard (DH), monosyllable easy (ME), and monosyllable hard (MH)) was used to evaluate the Mandarin Chinese word recognition in speech spectrum-shaped noise (SSN) with a signal-to-noise ratio (SNR) of 0dB. A two-way repeated-measures analysis of variance was conducted to examine the lexical effects with syllable length and difficulty level as the main factors on word recognition in the quiet and noise listening conditions. The effects of age on word-recognition performance were examined using a regression model. The word-recognition performance in noise was significantly poorer than that in quiet and the individual variations in performance in noise were much greater than those in quiet. Word recognition scores showed that the lexical effects were significant in the SSN. Children scored higher with dissyllabic words than with monosyllabic words; "easy" words scored higher than "hard" words in the noise condition. The scores of the NH children in the SSN (SNR=0dB) for the DE, DH, ME, and MH words were 85.4, 65.9, 71.7, and 46.2% correct, respectively. The word-recognition performance also increased with age in each lexical category for the NH children tested in noise. Both age and lexical characteristics of words had significant influences on the performance of Mandarin-Chinese word recognition in noise. The lexical effects were more obvious under noise listening conditions than in quiet. The word-recognition

Comparing Facial Emotional Recognition in Patients with Borderline Personality Disorder and Patients with Schizotypal Personality Disorder with a Normal Group

Directory of Open Access Journals (Sweden)

Aida Farsham

2017-04-01

Full Text Available Objective: No research has been conducted on facial emotional recognition on patients with borderline personality disorder (BPD and schizotypal personality disorder (SPD. The present study aimed at comparing facial emotion recognition in these patients with the general population. The neurocognitive processing of emotions can show the pathologic style of these 2 disorders. Method:  Twenty BPD patients, 16 SPD patients, and 20 healthy individuals were selected by available sampling method. Structural Clinical Interview for Axis II, Millon Personality Inventory, Beck Depression Inventory and Facial Emotional Recognition Test was were conducted for all participants.Discussion: The results of one way ANOVA and Scheffe’s post hoc test analysis revealed significant differences in neuropsychology assessment of  facial emotional recognition between BPD and  SPD patients with normal group (p = 0/001. A significant difference was found in emotion recognition of fear between the 2 groups of BPD and normal population (p = 0/008. A significant difference was observed between SPD patients and control group in emotion recognition of wonder (p = 0/04(.The obtained results indicated a deficit in negative emotion recognition, especially disgust emotion, thus, it can be concluded that these patients have the same neurocognitive profile in the emotion domain.

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

Science.gov (United States)

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition

KAUST Repository

Li, Huibin; Di, Huang; Morvan, Jean-Marie; Chen, Liming

2011-01-01

This paper proposes a novel approach for 3D face recognition by learning weighted sparse representation of encoded facial normal information. To comprehensively describe 3D facial surface, three components, in X, Y, and Z-plane respectively

Lexical tone recognition in noise in normal-hearing children and prelingually deafened children with cochlear implants.

Science.gov (United States)

Mao, Yitao; Xu, Li

2017-01-01

The purpose of the present study was to investigate Mandarin tone recognition in background noise in children with cochlear implants (CIs), and to examine the potential factors contributing to their performance. Tone recognition was tested using a two-alternative forced-choice paradigm in various signal-to-noise ratio (SNR) conditions (i.e. quiet, +12, +6, 0, and -6 dB). Linear correlation analysis was performed to examine possible relationships between the tone-recognition performance of the CI children and the demographic factors. Sixty-six prelingually deafened children with CIs and 52 normal-hearing (NH) children as controls participated in the study. Children with CIs showed an overall poorer tone-recognition performance and were more susceptible to noise than their NH peers. Tone confusions between Mandarin tone 2 and tone 3 were most prominent in both CI and NH children except for in the poorest SNR conditions. Age at implantation was significantly correlated with tone-recognition performance of the CI children in noise. There is a marked deficit in tone recognition in prelingually deafened children with CIs, particularly in noise listening conditions. While factors that contribute to the large individual differences are still elusive, early implantation could be beneficial to tone development in pediatric CI users.

Recognition memory for colored and black-and-white scenes in normal and color deficient observers (dichromats).

Science.gov (United States)

Brédart, Serge; Cornet, Alyssa; Rakic, Jean-Marie

2014-01-01

Color deficient (dichromat) and normal observers' recognition memory for colored and black-and-white natural scenes was evaluated through several parameters: the rate of recognition, discrimination (A'), response bias (B"D), response confidence, and the proportion of conscious recollections (Remember responses) among hits. At the encoding phase, 36 images of natural scenes were each presented for 1 sec. Half of the images were shown in color and half in black-and-white. At the recognition phase, these 36 pictures were intermixed with 36 new images. The participants' task was to indicate whether an image had been presented or not at the encoding phase, to rate their level of confidence in his her/his response, and in the case of a positive response, to classify the response as a Remember, a Know or a Guess response. Results indicated that accuracy, response discrimination, response bias and confidence ratings were higher for colored than for black-and-white images; this advantage for colored images was similar in both groups of participants. Rates of Remember responses were not higher for colored images than for black-and-white ones, whatever the group. However, interestingly, Remember responses were significantly more often based on color information for colored than for black-and-white images in normal observers only, not in dichromats.

Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model.

Science.gov (United States)

Jürgens, Tim; Brand, Thomas

2009-11-01

This study compares the phoneme recognition performance in speech-shaped noise of a microscopic model for speech recognition with the performance of normal-hearing listeners. "Microscopic" is defined in terms of this model twofold. First, the speech recognition rate is predicted on a phoneme-by-phoneme basis. Second, microscopic modeling means that the signal waveforms to be recognized are processed by mimicking elementary parts of human's auditory processing. The model is based on an approach by Holube and Kollmeier [J. Acoust. Soc. Am. 100, 1703-1716 (1996)] and consists of a psychoacoustically and physiologically motivated preprocessing and a simple dynamic-time-warp speech recognizer. The model is evaluated while presenting nonsense speech in a closed-set paradigm. Averaged phoneme recognition rates, specific phoneme recognition rates, and phoneme confusions are analyzed. The influence of different perceptual distance measures and of the model's a-priori knowledge is investigated. The results show that human performance can be predicted by this model using an optimal detector, i.e., identical speech waveforms for both training of the recognizer and testing. The best model performance is yielded by distance measures which focus mainly on small perceptual distances and neglect outliers.

Improving Mobile Phone Speech Recognition by Personalized Amplification: Application in People with Normal Hearing and Mild-to-Moderate Hearing Loss.

Science.gov (United States)

Kam, Anna Chi Shan; Sung, John Ka Keung; Lee, Tan; Wong, Terence Ka Cheong; van Hasselt, Andrew

In this study, the authors evaluated the effect of personalized amplification on mobile phone speech recognition in people with and without hearing loss. This prospective study used double-blind, within-subjects, repeated measures, controlled trials to evaluate the effectiveness of applying personalized amplification based on the hearing level captured on the mobile device. The personalized amplification settings were created using modified one-third gain targets. The participants in this study included 100 adults of age between 20 and 78 years (60 with age-adjusted normal hearing and 40 with hearing loss). The performance of the participants with personalized amplification and standard settings was compared using both subjective and speech-perception measures. Speech recognition was measured in quiet and in noise using Cantonese disyllabic words. Subjective ratings on the quality, clarity, and comfortableness of the mobile signals were measured with an 11-point visual analog scale. Subjective preferences of the settings were also obtained by a paired-comparison procedure. The personalized amplification application provided better speech recognition via the mobile phone both in quiet and in noise for people with hearing impairment (improved 8 to 10%) and people with normal hearing (improved 1 to 4%). The improvement in speech recognition was significantly better for people with hearing impairment. When the average device output level was matched, more participants preferred to have the individualized gain than not to have it. The personalized amplification application has the potential to improve speech recognition for people with mild-to-moderate hearing loss, as well as people with normal hearing, in particular when listening in noisy environments.

Trade off between variable and fixed size normalization in orthogonal polynomials based iris recognition system.

Science.gov (United States)

Krishnamoorthi, R; Anna Poorani, G

2016-01-01

Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

Motion Normalized Proportional Control for Improved Pattern Recognition-Based Myoelectric Control.

Science.gov (United States)

Scheme, Erik; Lock, Blair; Hargrove, Levi; Hill, Wendy; Kuruganti, Usha; Englehart, Kevin

2014-01-01

This paper describes two novel proportional control algorithms for use with pattern recognition-based myoelectric control. The systems were designed to provide automatic configuration of motion-specific gains and to normalize the control space to the user's usable dynamic range. Class-specific normalization parameters were calculated using data collected during classifier training and require no additional user action or configuration. The new control schemes were compared to the standard method of deriving proportional control using a one degree of freedom Fitts' law test for each of the wrist flexion/extension, wrist pronation/supination and hand close/open degrees of freedom. Performance was evaluated using the Fitts' law throughput value as well as more descriptive metrics including path efficiency, overshoot, stopping distance and completion rate. The proposed normalization methods significantly outperformed the incumbent method in every performance category for able bodied subjects (p < 0.001) and nearly every category for amputee subjects. Furthermore, one proposed method significantly outperformed both other methods in throughput (p < 0.0001), yielding 21% and 40% improvement over the incumbent method for amputee and able bodied subjects, respectively. The proposed control schemes represent a computationally simple method of fundamentally improving myoelectric control users' ability to elicit robust, and controlled, proportional velocity commands.

When family looks strange and strangers look normal : A case of impaired face perception and recognition after stroke

NARCIS (Netherlands)

Heutink, Joost; Brouwer, Wiebo H.; Kums, Evelien; Young, Andy; Bouma, Anke

2012-01-01

We describe a patient (JS) with impaired recognition and distorted visual perception of faces after an ischemic stroke. Strikingly, JS reports that the faces of family members look distorted, while faces of other people look normal. After neurological and neuropsychological examination, we assessed

Theory of mind and emotion-recognition functioning in autistic spectrum disorders and in psychiatric control and normal children.

Science.gov (United States)

Buitelaar, J K; van der Wees, M; Swaab-Barneveld, H; van der Gaag, R J

1999-01-01

The hypothesis was tested that weak theory of mind (ToM) and/or emotion recognition (ER) abilities are specific to subjects with autism. Differences in ToM and ER performance were examined between autistic (n = 20), pervasive developmental disorder-not otherwise specified (PDD-NOS) (n = 20), psychiatric control (n = 20), and normal children (n = 20). The clinical groups were matched person-to-person on age and verbal IQ. We used tasks for the matching and the context recognition of emotional expressions, and a set of first- and second-order ToM tasks. Autistic and PDD-NOS children could not be significantly differentiated from each other, nor could they be differentiated from the psychiatric controls with a diagnosis of ADHD (n = 9). The psychiatric controls with conduct disorder or dysthymia performed about as well as normal children. The variance in second-order ToM performance contributed most to differences between diagnostic groups.

Wire-guided (Seldinger technique intubation through a face mask in urgent, difficult and grossly distorted airways

Directory of Open Access Journals (Sweden)

Jake M Heier

2012-01-01

Full Text Available We report two cases of successful urgent intubation using a Seldinger technique for airway management through an anesthesia facemask, while maintaining ventilation in patients with difficult airways and grossly distorted airway anatomy. In both cases, conventional airway management techniques were predicted to be difficult or impossible, and a high likelihood for a surgical airway was present. This technique was chosen as it allows tracheal tube placement through the nares during spontaneous ventilation with the airway stented open and oxygen delivery with either continuous positive airway pressure and/or pressure support ventilation. This unhurried technique may allow intubation when other techniques are unsuitable, while maintaining control of the airway.

Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

KAUST Repository

Li, Huibin

2014-06-01

In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

Science.gov (United States)

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

Science.gov (United States)

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

The experience of weight management in normal weight adults.

Science.gov (United States)

Hernandez, Cheri Ann; Hernandez, David A; Wellington, Christine M; Kidd, Art

2016-11-01

No prior research has been done with normal weight persons specific to their experience of weight management. The purpose of this research was to discover the experience of weight management in normal weight individuals. Glaserian grounded theory was used. Qualitative data (focus group) and quantitative data (food diary, study questionnaire, and anthropometric measures) were collected. Weight management was an ongoing process of trying to focus on living (family, work, and social), while maintaining their normal weight targets through five consciously and unconsciously used strategies. Despite maintaining normal weights, the nutritional composition of foods eaten was grossly inadequate. These five strategies can be used to develop new weight management strategies that could be integrated into existing weight management programs, or could be developed into novel weight management interventions. Surprisingly, normal weight individuals require dietary assessment and nutrition education to prevent future negative health consequences. Copyright © 2016 Elsevier Inc. All rights reserved.

Speech Recognition in Real-Life Background Noise by Young and Middle-Aged Adults with Normal Hearing

OpenAIRE

Lee, Ji Young; Lee, Jin Tae; Heo, Hye Jeong; Choi, Chul-Hee; Choi, Seong Hee; Lee, Kyungjae

2015-01-01

Background and Objectives People usually converse in real-life background noise. They experience more difficulty understanding speech in noise than in a quiet environment. The present study investigated how speech recognition in real-life background noise is affected by the type of noise, signal-to-noise ratio (SNR), and age. Subjects and Methods Eighteen young adults and fifteen middle-aged adults with normal hearing participated in the present study. Three types of noise [subway noise, vacu...

Normal mere exposure effect with impaired recognition in Alzheimer's disease.

Science.gov (United States)

Willems, Sylvie; Adam, Stéphane; Van der Linden, Martial

2002-02-01

We investigated the mere exposure effect and the explicit memory in Alzheimer's disease (AD) patients and elderly control subjects, using unfamiliar faces. During the exposure phase, the subjects estimated the age of briefly flashed faces. The mere exposure effect was examined by presenting pairs of faces (old and new) and asking participants to select the face they liked. The participants were then presented with a forced-choice explicit recognition task. Controls subjects exhibited above-chance preference and recognition scores for old faces. The AD patients also showed the mere exposure effect but no explicit recognition. These results suggest that the processes involved in the mere exposure effect are preserved in AD patients despite their impaired explicit recognition. The results are discussed in terms of Seamon et al.'s (1995) proposal that processes involved in the mere exposure effect are equivalent to those subserving perceptual priming. These processes would depend on extrastriate areas which are relatively preserved in AD patients.

Searching for sources of variance in speech recognition: Young adults with normal hearing

Science.gov (United States)

Watson, Charles S.; Kidd, Gary R.

2005-04-01

In the present investigation, sensory-perceptual abilities of one thousand young adults with normal hearing are being evaluated with a range of auditory, visual, and cognitive measures. Four auditory measures were derived from factor-analytic analyses of previous studies with 18-20 speech and non-speech variables [G. R. Kidd et al., J. Acoust. Soc. Am. 108, 2641 (2000)]. Two measures of visual acuity are obtained to determine whether variation in sensory skills tends to exist primarily within or across sensory modalities. A working memory test, grade point average, and Scholastic Aptitude Test scores (Verbal and Quantitative) are also included. Preliminary multivariate analyses support previous studies of individual differences in auditory abilities (e.g., A. M. Surprenant and C. S. Watson, J. Acoust. Soc. Am. 110, 2085-2095 (2001)] which found that spectral and temporal resolving power obtained with pure tones and more complex unfamiliar stimuli have little or no correlation with measures of speech recognition under difficult listening conditions. The current findings show that visual acuity, working memory, and intellectual measures are also very poor predictors of speech recognition ability, supporting the independence of this processing skill. Remarkable performance by some exceptional listeners will be described. [Work supported by the Office of Naval Research, Award No. N000140310644.

Predicting word-recognition performance in noise by young listeners with normal hearing using acoustic, phonetic, and lexical variables.

Science.gov (United States)

McArdle, Rachel; Wilson, Richard H

2008-06-01

To analyze the 50% correct recognition data that were from the Wilson et al (this issue) study and that were obtained from 24 listeners with normal hearing; also to examine whether acoustic, phonetic, or lexical variables can predict recognition performance for monosyllabic words presented in speech-spectrum noise. The specific variables are as follows: (a) acoustic variables (i.e., effective root-mean-square sound pressure level, duration), (b) phonetic variables (i.e., consonant features such as manner, place, and voicing for initial and final phonemes; vowel phonemes), and (c) lexical variables (i.e., word frequency, word familiarity, neighborhood density, neighborhood frequency). The descriptive, correlational study will examine the influence of acoustic, phonetic, and lexical variables on speech recognition in noise performance. Regression analysis demonstrated that 45% of the variance in the 50% point was accounted for by acoustic and phonetic variables whereas only 3% of the variance was accounted for by lexical variables. These findings suggest that monosyllabic word-recognition-in-noise is more dependent on bottom-up processing than on top-down processing. The results suggest that when speech-in-noise testing is used in a pre- and post-hearing-aid-fitting format, the use of monosyllabic words may be sensitive to changes in audibility resulting from amplification.

Voice Recognition in Face-Blind Patients

Science.gov (United States)

Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

2016-01-01

Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

The Use of Lexical Neighborhood Test (LNT) in the Assessment of Speech Recognition Performance of Cochlear Implantees with Normal and Malformed Cochlea.

Science.gov (United States)

Kant, Anjali R; Banik, Arun A

2017-09-01

The present study aims to use the model-based test Lexical Neighborhood Test (LNT), to assess speech recognition performance in early and late implanted hearing impaired children with normal and malformed cochlea. The LNT was administered to 46 children with congenital (prelingual) bilateral severe-profound sensorineural hearing loss, using Nucleus 24 cochlear implant. The children were grouped into Group 1-(early implantees with normal cochlea-EI); n = 15, 31/2-61/2 years of age; mean age at implantation-3½ years. Group 2-(late implantees with normal cochlea-LI); n = 15, 6-12 years of age; mean age at implantation-5 years. Group 3-(early implantees with malformed cochlea-EIMC); n = 9; 4.9-10.6 years of age; mean age at implantation-3.10 years. Group 4-(late implantees with malformed cochlea-LIMC); n = 7; 7-12.6 years of age; mean age at implantation-6.3 years. The following were the malformations: dysplastic cochlea, common cavity, Mondini's, incomplete partition-1 and 2 (IP-1 and 2), enlarged IAC. The children were instructed to repeat the words on hearing them. Means of the word and phoneme scores were computed. The LNT can also be used to assess speech recognition performance of hearing impaired children with malformed cochlea. When both easy and hard lists of LNT are considered, although, late implantees (with or without normal cochlea), have achieved higher word scores than early implantees, the differences are not statistically significant. Using LNT for assessing speech recognition enables a quantitative as well as descriptive report of phonological processes used by the children.

Factors Affecting Sentence-in-Noise Recognition for Normal Hearing Listeners and Listeners with Hearing Loss.

Science.gov (United States)

Hwang, Jung Sun; Kim, Kyung Hyun; Lee, Jae Hee

2017-07-01

Despite amplified speech, listeners with hearing loss often report more difficulties understanding speech in background noise compared to normalhearing listeners. Various factors such as deteriorated hearing sensitivity, age, suprathreshold temporal resolution, and reduced capacity of working memory and attention can attribute to their sentence-in-noise problems. The present study aims to determine a primary explanatory factor for sentence-in-noise recognition difficulties in adults with or without hearing loss. Forty normal-hearing (NH) listeners (23-73 years) and thirty-four hearing-impaired (HI) listeners (24-80 years) participated for experimental testing. For both NH and HI group, the younger, middle-aged, older listeners were included. The sentence recognition score in noise was measured at 0 dB signal-to-noise ratio. The ability of temporal resolution was evaluated by gap detection performance using the Gaps-In-Noise test. Listeners' short-term auditory working memory span was measured by forward and backward digit spans. Overall, the HI listeners' sentence-in-noise recognition, temporal resolution abilities, and digit forward and backward spans were poorer compared to the NH listeners. Both NH and HI listeners had a substantial variability in performance. For NH listeners, only the digit backward span explained a small proportion of the variance in their sentence-in-noise performance. For the HI listeners, all the performance was influenced by age, and their sentence-in-noise difficulties were associated with various factors such as high-frequency hearing sensitivity, suprathreshold temporal resolution abilities, and working memory span. For the HI listeners, the critical predictors of the sentence-in-noise performance were composite measures of peripheral hearing sensitivity and suprathreshold temporal resolution abilities. The primary explanatory factors for the sentence-in-noise recognition performance differ between NH and HI listeners. Factors

Window Size Impact in Human Activity Recognition

Directory of Open Access Journals (Sweden)

Oresti Banos

2014-04-01

Full Text Available Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

Mice deficient for striatal Vesicular Acetylcholine Transporter (VAChT) display impaired short-term but normal long-term object recognition memory.

Science.gov (United States)

Palmer, Daniel; Creighton, Samantha; Prado, Vania F; Prado, Marco A M; Choleris, Elena; Winters, Boyer D

2016-09-15

Substantial evidence implicates Acetylcholine (ACh) in the acquisition of object memories. While most research has focused on the role of the cholinergic basal forebrain and its cortical targets, there are additional cholinergic networks that may contribute to object recognition. The striatum contains an independent cholinergic network comprised of interneurons. In the current study, we investigated the role of this cholinergic signalling in object recognition using mice deficient for Vesicular Acetylcholine Transporter (VAChT) within interneurons of the striatum. We tested whether these striatal VAChT(D2-Cre-flox/flox) mice would display normal short-term (5 or 15min retention delay) and long-term (3h retention delay) object recognition memory. In a home cage object recognition task, male and female VAChT(D2-Cre-flox/flox) mice were impaired selectively with a 15min retention delay. When tested on an object location task, VAChT(D2-Cre-flox/flox) mice displayed intact spatial memory. Finally, when object recognition was tested in a Y-shaped apparatus, designed to minimize the influence of spatial and contextual cues, only females displayed impaired recognition with a 5min retention delay, but when males were challenged with a 15min retention delay, they were also impaired; neither males nor females were impaired with the 3h delay. The pattern of results suggests that striatal cholinergic transmission plays a role in the short-term memory for object features, but not spatial location. Copyright © 2016 Elsevier B.V. All rights reserved.

SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

Institute of Scientific and Technical Information of China (English)

无

2008-01-01

Quadratic Discrimination Function(QDF)is commonly used in speech emotion recognition,which proceeds on the premise that the input data is normal distribution.In this Paper,we propose a transformation to normalize the emotional features,then derivate a Modified QDF(MQDF) to speech emotion recognition.Features based on prosody and voice quality are extracted and Principal Component Analysis Neural Network (PCANN) is used to reduce dimension of the feature vectors.The results show that voice quality features are effective supplement for recognition.and the method in this paper could improve the recognition ratio effectively.

Perceptual differentiation and category effects in normal object recognition

DEFF Research Database (Denmark)

Gerlach, Christian; Law, I; Gade, A

1999-01-01

The purpose of the present PET study was (i) to investigate the neural correlates of object recognition, i.e. the matching of visual forms to memory, and (ii) to test the hypothesis that this process is more difficult for natural objects than for artefacts. This was done by using object decision...... tasks where subjects decided whether pictures represented real objects or non-objects. The object decision tasks differed in their difficulty (the degree of perceptual differentiation needed to perform them) and in the category of the real objects used (natural objects versus artefacts). A clear effect...... be the neural correlate of matching visual forms to memory, and the amount of activation in these regions may correspond to the degree of perceptual differentiation required for recognition to occur. With respect to behaviour, it took significantly longer to make object decisions on natural objects than...

AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

Directory of Open Access Journals (Sweden)

K. Meena

2013-11-01

Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

The relationship between recognition memory for emotion-laden words and white matter microstructure in normal older individuals.

Science.gov (United States)

Saarela, Carina; Karrasch, Mira; Ilvesmäki, Tero; Parkkola, Riitta; Rinne, Juha O; Laine, Matti

2016-12-14

Functional neuroimaging studies have shown age-related differences in brain activation and connectivity patterns for emotional memory. Previous studies with middle-aged and older adults have reported associations between episodic memory and white matter (WM) microstructure obtained from diffusion tensor imaging, but such studies on emotional memory remain few. To our knowledge, this is the first study to explore associations between WM microstructure as measured by fractional anisotropy (FA) and recognition memory for intentionally encoded positive, negative, and emotionally neutral words using tract-based spatial statistics applied to diffusion tensor imaging images in an elderly sample (44 cognitively intact adults aged 50-79 years). The use of tract-based spatial statistics enables the identification of WM tracts important to emotional memory without a priori assumptions required for region-of-interest approaches that have been used in previous work. The behavioral analyses showed a positivity bias, that is, a preference for positive words, in recognition memory. No statistically significant associations emerged between FA and memory for negative or neutral words. Controlling for age and memory performance for negative and neutral words, recognition memory for positive words was negatively associated with FA in several projection, association, and commissural tracts in the left hemisphere. This likely reflects the complex interplay between the mnemonic positivity bias, structural WM integrity, and functional brain compensatory mechanisms in older age. Also, the unexpected directionality of the results indicates that the WM microstructural correlates of emotional memory show unique characteristics in normal older individuals.

Managing a grossly comminuted and infected mandibular fracture using a maxillary extra-oral distractor as stabilizing agent: A clinical case report

Directory of Open Access Journals (Sweden)

Ding Ming Chao

2017-06-01

Full Text Available Facial fracture management dates as early as Hippocratic era. Comminuted mandibular fractures are one of the challenging clinical condition requiring high surgical expertise to achieve a good functional and esthetic outcome. In presence of infection and other facial fractures managing comminuted mandibular fracture becomes more challenging.Here we present a case of grossly comminuted and infected mandibular fracture with delayed presentation managed by using maxillary distractor as stabilizing agent. Using a maxillary distractor for managing a fractured mandible has been seldom reported in literature. Current case report gives idea to practicing clinician about the possibility of treatment beyond the established principles. Keywords: Mandibular fracture, Maxillary distractor, Infection

Eye movements during object recognition in visual agnosia.

Science.gov (United States)

Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe

2012-07-01

This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effects of Noise on Speech Recognition and Listening Effort in Children with Normal Hearing and Children with Mild Bilateral or Unilateral Hearing Loss

Science.gov (United States)

Lewis, Dawna; Schmid, Kendra; O'Leary, Samantha; Spalding, Jody; Heinrichs-Graham, Elizabeth; High, Robin

2016-01-01

Purpose: This study examined the effects of stimulus type and hearing status on speech recognition and listening effort in children with normal hearing (NH) and children with mild bilateral hearing loss (MBHL) or unilateral hearing loss (UHL). Method Children (5-12 years of age) with NH (Experiment 1) and children (8-12 years of age) with MBHL,…

Automatic anatomy recognition on CT images with pathology

Science.gov (United States)

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.

Variability in the impairments of recognition memory in patients with frontal lobe lesions

OpenAIRE

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-01-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased...

The Effects of Musical and Linguistic Components in Recognition of Real-World Musical Excerpts by Cochlear Implant Recipients and Normal-Hearing Adults

Science.gov (United States)

Gfeller, Kate; Jiang, Dingfeng; Oleson, Jacob; Driscoll, Virginia; Olszewski, Carol; Knutson, John F.; Turner, Christopher; Gantz, Bruce

2011-01-01

Background Cochlear implants (CI) are effective in transmitting salient features of speech, especially in quiet, but current CI technology is not well suited in transmission of key musical structures (e.g., melody, timbre). It is possible, however, that sung lyrics, which are commonly heard in real-world music may provide acoustical cues that support better music perception. Objective The purpose of this study was to examine how accurately adults who use CIs (n=87) and those with normal hearing (NH) (n=17) are able to recognize real-world music excerpts based upon musical and linguistic (lyrics) cues. Results CI recipients were significantly less accurate than NH listeners on recognition of real-world music with or, in particular, without lyrics; however, CI recipients whose devices transmitted acoustic plus electric stimulation were more accurate than CI recipients reliant upon electric stimulation alone (particularly items without linguistic cues). Recognition by CI recipients improved as a function of linguistic cues. Methods Participants were tested on melody recognition of complex melodies (pop, country, classical styles). Results were analyzed as a function of: hearing status and history, device type (electric only or acoustic plus electric stimulation), musical style, linguistic and musical cues, speech perception scores, cognitive processing, music background, age, and in relation to self-report on listening acuity and enjoyment. Age at time of testing was negatively correlated with recognition performance. Conclusions These results have practical implications regarding successful participation of CI users in music-based activities that include recognition and accurate perception of real-world songs (e.g., reminiscence, lyric analysis, listening for enjoyment). PMID:22803258

The effects of musical and linguistic components in recognition of real-world musical excerpts by cochlear implant recipients and normal-hearing adults.

Science.gov (United States)

Gfeller, Kate; Jiang, Dingfeng; Oleson, Jacob J; Driscoll, Virginia; Olszewski, Carol; Knutson, John F; Turner, Christopher; Gantz, Bruce

2012-01-01

Cochlear implants (CI) are effective in transmitting salient features of speech, especially in quiet, but current CI technology is not well suited in transmission of key musical structures (e.g., melody, timbre). It is possible, however, that sung lyrics, which are commonly heard in real-world music may provide acoustical cues that support better music perception. The purpose of this study was to examine how accurately adults who use CIs (n = 87) and those with normal hearing (NH) (n = 17) are able to recognize real-world music excerpts based upon musical and linguistic (lyrics) cues. CI recipients were significantly less accurate than NH listeners on recognition of real-world music with or, in particular, without lyrics; however, CI recipients whose devices transmitted acoustic plus electric stimulation were more accurate than CI recipients reliant upon electric stimulation alone (particularly items without linguistic cues). Recognition by CI recipients improved as a function of linguistic cues. Participants were tested on melody recognition of complex melodies (pop, country, & classical styles). Results were analyzed as a function of: hearing status and history, device type (electric only or acoustic plus electric stimulation), musical style, linguistic and musical cues, speech perception scores, cognitive processing, music background, age, and in relation to self-report on listening acuity and enjoyment. Age at time of testing was negatively correlated with recognition performance. These results have practical implications regarding successful participation of CI users in music-based activities that include recognition and accurate perception of real-world songs (e.g., reminiscence, lyric analysis, & listening for enjoyment).

Acute effects of triazolam on false recognition.

Science.gov (United States)

Mintzer, M Z; Griffiths, R R

2000-12-01

Neuropsychological, neuroimaging, and electrophysiological techniques have been applied to the study of false recognition; however, psychopharmacological techniques have not been applied. Benzodiazepine sedative/anxiolytic drugs produce memory deficits similar to those observed in organic amnesia and may be useful tools for studying normal and abnormal memory mechanisms. The present double-blind, placebo-controlled repeated measures study examined the acute effects of orally administered triazolam (Halcion; 0.125 and 0.25 mg/70 kg), a benzodiazepine hypnotic, on performance in the Deese (1959)/Roediger-McDermott (1995) false recognition paradigm in 24 healthy volunteers. Paralleling previous demonstrations in amnesic patients, triazolam produced significant dose-related reductions in false recognition rates to nonstudied words associatively related to studied words, suggesting that false recognition relies on normal memory mechanisms impaired in benzodiazepine-induced amnesia. The results also suggested that relative to placebo, triazolam reduced participants' reliance on memory for item-specific versus list-common semantic information and reduced participants' use of remember versus know responses.

Novel Techniques for Dialectal Arabic Speech Recognition

CERN Document Server

Elmahdy, Mohamed; Minker, Wolfgang

2012-01-01

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

Efficient CEPSTRAL Normalization for Robust Speech Recognition

National Research Council Canada - National Science Library

Liu, Fu-Hua; Stern, Richard M; Huang, Xuedong; Acero, Alejandro

1993-01-01

.... We compare the performance of these algorithms with the very simple RASTA and cepstral mean normalization procedures, describing the performance of these algorithms in the context of the 1992 DARPA...

Bidirectional Modulation of Recognition Memory.

Science.gov (United States)

Ho, Jonathan W; Poeta, Devon L; Jacobson, Tara K; Zolnik, Timothy A; Neske, Garrett T; Connors, Barry W; Burwell, Rebecca D

2015-09-30

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30-40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30-40 Hz was not effective in increasing exploration of novel images. Stimulation at 10-15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. Significance statement: Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of

Automatic speech recognition (zero crossing method). Automatic recognition of isolated vowels

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1975-01-01

This note describes a recognition method of isolated vowels, using a preprocessing of the vocal signal. The processing extracts the extrema of the vocal signal and the interval time separating them (Zero crossing distances of the first derivative of the signal). The recognition of vowels uses normalized histograms of the values of these intervals. The program determines a distance between the histogram of the sound to be recognized and histograms models built during a learning phase. The results processed on real time by a minicomputer, are relatively independent of the speaker, the fundamental frequency being not allowed to vary too much (i.e. speakers of the same sex). (author) [fr

Individual differences in language and working memory affect children's speech recognition in noise.

Science.gov (United States)

McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-05-01

We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion

Science.gov (United States)

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13. Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract PMID:27504009

Indonesian Sign Language Number Recognition using SIFT Algorithm

Science.gov (United States)

Mahfudi, Isa; Sarosa, Moechammad; Andrie Asmara, Rosa; Azrino Gustalika, M.

2018-04-01

Indonesian sign language (ISL) is generally used for deaf individuals and poor people communication in communicating. They use sign language as their primary language which consists of 2 types of action: sign and finger spelling. However, not all people understand their sign language so that this becomes a problem for them to communicate with normal people. this problem also becomes a factor they are isolated feel from the social life. It needs a solution that can help them to be able to interacting with normal people. Many research that offers a variety of methods in solving the problem of sign language recognition based on image processing. SIFT (Scale Invariant Feature Transform) algorithm is one of the methods that can be used to identify an object. SIFT is claimed very resistant to scaling, rotation, illumination and noise. Using SIFT algorithm for Indonesian sign language recognition number result rate recognition to 82% with the use of a total of 100 samples image dataset consisting 50 sample for training data and 50 sample images for testing data. Change threshold value get affect the result of the recognition. The best value threshold is 0.45 with rate recognition of 94%.

Investigation of normal organ development with fetal MRI

International Nuclear Information System (INIS)

Prayer, Daniela; Brugger, Peter C.

2007-01-01

The understanding of the presentation of normal organ development on fetal MRI forms the basis for recognition of pathological states. During the second and third trimesters, maturational processes include changes in size, shape and signal intensities of organs. Visualization of these developmental processes requires tailored MR protocols. Further prerequisites for recognition of normal maturational states are unequivocal intrauterine orientation with respect to left and right body halves, fetal proportions, and knowledge about the MR presentation of extrafetal/intrauterine organs. Emphasis is laid on the demonstration of normal MR appearance of organs that are frequently involved in malformation syndromes. In addition, examples of time-dependent contrast enhancement of intrauterine structures are given. (orig.)

Investigation of normal organ development with fetal MRI

Energy Technology Data Exchange (ETDEWEB)

Prayer, Daniela [Medical University of Vienna, Department of Radiology, Vienna (Austria); Brugger, Peter C. [Medical University of Vienna, Center of Anatomy and Cell Biology, Integrative Morphology Group, Vienna (Austria)

2007-10-15

The understanding of the presentation of normal organ development on fetal MRI forms the basis for recognition of pathological states. During the second and third trimesters, maturational processes include changes in size, shape and signal intensities of organs. Visualization of these developmental processes requires tailored MR protocols. Further prerequisites for recognition of normal maturational states are unequivocal intrauterine orientation with respect to left and right body halves, fetal proportions, and knowledge about the MR presentation of extrafetal/intrauterine organs. Emphasis is laid on the demonstration of normal MR appearance of organs that are frequently involved in malformation syndromes. In addition, examples of time-dependent contrast enhancement of intrauterine structures are given. (orig.)

Normal mere exposure effect with impaired recognition in Alzheimer's disease

OpenAIRE

Willems, Sylvie; Adam, Stéphane; Van der Linden, Martial

2002-01-01

We investigated the mere exposure effect and the explicit memory in Alzheimer's disease (AD) patients and elderly control subjects, using unfamiliar faces. During the exposure phase, the subjects estimated the age of briefly flashed faces. The mere exposure effect was examined by presenting pairs of faces (old and new) and asking participants to select the face they liked. The participants were then presented with a forced-choice explicit recognition task. Controls subjects exhibited above-ch...

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

Science.gov (United States)

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

Individual differences in language and working memory affect children’s speech recognition in noise

Science.gov (United States)

McCreery, Ryan W.; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-01-01

Objective We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. Design As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Study sample Ninety-six children with normal hearing, who were between 5 and 12 years of age. Results Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Conclusions Working memory and language both influence children’s speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child’s auditory skills, consistent with the Ease of Language Understanding model. PMID:27981855

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion.

Science.gov (United States)

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13.Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract. © The Author(s) 2016. Published by Oxford University Press.

Flexible Piezoelectric Sensor-Based Gait Recognition

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Youngsu Cha

2018-02-01

Full Text Available 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 %.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

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Heracleous Panikos

2007-01-01

Full Text Available 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 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.

Lexicon Optimization for Dutch Speech Recognition in Spoken Document Retrieval

NARCIS (Netherlands)

Ordelman, Roeland J.F.; van Hessen, Adrianus J.; de Jong, Franciska M.G.

In this paper, ongoing work concerning the language modelling and lexicon optimization of a Dutch speech recognition system for Spoken Document Retrieval is described: the collection and normalization of a training data set and the optimization of our recognition lexicon. Effects on lexical coverage

Lexicon optimization for Dutch speech recognition in spoken document retrieval

NARCIS (Netherlands)

Ordelman, Roeland J.F.; van Hessen, Adrianus J.; de Jong, Franciska M.G.; Dalsgaard, P.; Lindberg, B.; Benner, H.

2001-01-01

In this paper, ongoing work concerning the language modelling and lexicon optimization of a Dutch speech recognition system for Spoken Document Retrieval is described: the collection and normalization of a training data set and the optimization of our recognition lexicon. Effects on lexical coverage

Machine learning techniques for gait biometric recognition using the ground reaction force

CERN Document Server

Mason, James Eric; Woungang, Isaac

2016-01-01

This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

Revisiting vocal perception in non-human animals: a review of vowel discrimination, speaker voice recognition, and speaker normalization

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Buddhamas eKriengwatana

2015-01-01

Full Text Available The extent to which human speech perception evolved by taking advantage of predispositions and pre-existing features of vertebrate auditory and cognitive systems remains a central question in the evolution of speech. This paper reviews asymmetries in vowel perception, speaker voice recognition, and speaker normalization in non-human animals – topics that have not been thoroughly discussed in relation to the abilities of non-human animals, but are nonetheless important aspects of vocal perception. Throughout this paper we demonstrate that addressing these issues in non-human animals is relevant and worthwhile because many non-human animals must deal with similar issues in their natural environment. That is, they must also discriminate between similar-sounding vocalizations, determine signaler identity from vocalizations, and resolve signaler-dependent variation in vocalizations from conspecifics. Overall, we find that, although plausible, the current evidence is insufficiently strong to conclude that directional asymmetries in vowel perception are specific to humans, or that non-human animals can use voice characteristics to recognize human individuals. However, we do find some indication that non-human animals can normalize speaker differences. Accordingly, we identify avenues for future research that would greatly improve and advance our understanding of these topics.

Covert face recognition in congenital prosopagnosia: a group study.

Science.gov (United States)

Rivolta, Davide; Palermo, Romina; Schmalzl, Laura; Coltheart, Max

2012-03-01

Even though people with congenital prosopagnosia (CP) never develop a normal ability to "overtly" recognize faces, some individuals show indices of "covert" (or implicit) face recognition. The aim of this study was to demonstrate covert face recognition in CP when participants could not overtly recognize the faces. Eleven people with CP completed three tasks assessing their overt face recognition ability, and three tasks assessing their "covert" face recognition: a Forced choice familiarity task, a Forced choice cued task, and a Priming task. Evidence of covert recognition was observed with the Forced choice familiarity task, but not the Priming task. In addition, we propose that the Forced choice cued task does not measure covert processing as such, but instead "provoked-overt" recognition. Our study clearly shows that people with CP demonstrate covert recognition for faces that they cannot overtly recognize, and that behavioural tasks vary in their sensitivity to detect covert recognition in CP. Copyright © 2011 Elsevier Srl. All rights reserved.

NCBI disease corpus: a resource for disease name recognition and concept normalization.

Science.gov (United States)

Doğan, Rezarta Islamaj; Leaman, Robert; Lu, Zhiyong

2014-02-01

knowledge-based disease normalization methods with a best performance in F-measure of 63.7%. These results show that the NCBI disease corpus has the potential to significantly improve the state-of-the-art in disease name recognition and normalization research, by providing a high-quality gold standard thus enabling the development of machine-learning based approaches for such tasks. The NCBI disease corpus, guidelines and other associated resources are available at: http://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/. Published by Elsevier Inc.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Hiroshi Saruwatari

2007-01-01

Full Text Available 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 93.9% 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.

75 FR 21666 - Canadian Standards Association; Application for Expansion of Recognition

Science.gov (United States)

2010-04-26

...] Canadian Standards Association; Application for Expansion of Recognition AGENCY: Occupational Safety and... the Canadian Standards Association for expansion of its recognition and presents the Agency's... Office's normal business hours, 8:15 a.m.-4:45 p.m., e.t. Instructions: All submissions must include the...

Positron emission tomography studies in the normal and abnormal ageing of human brain

International Nuclear Information System (INIS)

Comar, D.; Baron, J.C.

1987-01-01

Until recently, the investigation of the neurophysiological correlates of normal and abnormal ageing of the human brain was limited by methodological constraints, as the technics available provided only a few parameters (e.g. electroencephalograms, cerebral blood flow) monitored in superficial brain structures in a grossly regional and poorly quantitative way. Lately several non invasive techniques have been developed which allow to investigate in vivo both quantitatively and on local basis a number of previously inaccessible important aspects of brain function. Among these techniques, such as single photon emission tomography imaging of computerized electric events, nuclear magnetic resonance, positron emission tomography stands out as the most powerful and promising method since it allows the in vivo measurement of biochemical and pharmacological parameters

Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network

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Fatchul Arifin

2010-08-01

Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.

Localization and Recognition of Dynamic Hand Gestures Based on Hierarchy of Manifold Classifiers

Science.gov (United States)

Favorskaya, M.; Nosov, A.; Popov, A.

2015-05-01

Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case). Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset "Multi-modal Gesture Recognition Challenge 2013: Dataset and Results" including 393 dynamic hand-gestures was chosen. The proposed method yielded 84-91% recognition accuracy, in average, for restricted set of dynamic gestures.

LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

Directory of Open Access Journals (Sweden)

M. Favorskaya

2015-05-01

Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.

The principles of the pattern recognition of skeletal structures

International Nuclear Information System (INIS)

Motto, J.A.

2006-01-01

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

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

NARCIS (Netherlands)

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

2003-01-01

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

Automated pattern recognition system for noise analysis

International Nuclear Information System (INIS)

Sides, W.H. Jr.; Piety, K.R.

1980-01-01

A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

Static facial expression recognition with convolution neural networks

Science.gov (United States)

Zhang, Feng; Chen, Zhong; Ouyang, Chao; Zhang, Yifei

2018-03-01

Facial expression recognition is a currently active research topic in the fields of computer vision, pattern recognition and artificial intelligence. In this paper, we have developed a convolutional neural networks (CNN) for classifying human emotions from static facial expression into one of the seven facial emotion categories. We pre-train our CNN model on the combined FER2013 dataset formed by train, validation and test set and fine-tune on the extended Cohn-Kanade database. In order to reduce the overfitting of the models, we utilized different techniques including dropout and batch normalization in addition to data augmentation. According to the experimental result, our CNN model has excellent classification performance and robustness for facial expression recognition.

The Functional Architecture of Visual Object Recognition

Science.gov (United States)

1991-07-01

different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

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

Science.gov (United States)

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

2016-06-01

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

Enhancement of Iris Recognition System Based on Phase Only Correlation

Directory of Open Access Journals (Sweden)

Nuriza Pramita

2011-08-01

Full Text Available Iris recognition system is one of biometric based recognition/identification systems. Numerous techniques have been implemented to achieve a good recognition rate, including the ones based on Phase Only Correlation (POC. Significant and higher correlation peaks suggest that the system recognizes iris images of the same subject (person, while lower and unsignificant peaks correspond to recognition of those of difference subjects. Current POC methods have not investigated minimum iris point that can be used to achieve higher correlation peaks. This paper proposed a method that used only one-fourth of full normalized iris size to achieve higher (or at least the same recognition rate. Simulation on CASIA version 1.0 iris image database showed that averaged recognition rate of the proposed method achieved 67%, higher than that of using one-half (56% and full (53% iris point. Furthermore, all (100% POC peak values of the proposed method was higher than that of the method with full iris points.

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

Science.gov (United States)

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.

Face and emotion recognition deficits in Turner syndrome: a possible role for X-linked genes in amygdala development.

Science.gov (United States)

Lawrence, Kate; Kuntsi, Jonna; Coleman, Michael; Campbell, Ruth; Skuse, David

2003-01-01

Face recognition is thought to rely on configural visual processing. Where face recognition impairments have been identified, qualitatively delayed or anomalous configural processing has also been found. A group of women with Turner syndrome (TS) with monosomy for a single maternal X chromosome (45, Xm) showed an impairment in face recognition skills compared with normally developing women. However, normal configural face-processing abilities were apparent. The ability to recognize facial expressions of emotion, particularly fear, was also impaired in this TS subgroup. Face recognition and fear recognition accuracy were significantly correlated in the female control group but not in women with TS. The authors therefore suggest that anomalies in amygdala function may be a neurological feature of TS of this karyotype.

Named entity normalization in user generated content

NARCIS (Netherlands)

Jijkoun, V.; Khalid, M.A.; Marx, M.; de Rijke, M.

2008-01-01

Named entity recognition is important for semantically oriented retrieval tasks, such as question answering, entity retrieval, biomedical retrieval, trend detection, and event and entity tracking. In many of these tasks it is important to be able to accurately normalize the recognized entities,

Identification, recognition and misidentification syndromes. A psychoanalytical perspective.

Directory of Open Access Journals (Sweden)

Stéphane eThibierge

2013-11-01

Full Text Available Misidentification syndromes are currently often understood as cognitive disorders of either the sense of uniqueness (Margariti & Kontaxakis, 2006 or the recognition of people (Ellis, Lewis, 2001. It is however necessary to consider how a normal sense of uniqueness or a normal people recognition are acquired by normal or neurotic subjects. It will be shown here that the normal conditions of cognition can be considered as one of the possible forms of a complex structure and not as just a setting for our sense and perception data. The consistency and the permanency of the body image in neurosis is what permits that we recognize other people and ourselves as unique beings. These consistency and permanency are related to object repression, as shown by neurological disorders of body image (somatoparaphrenia, which cause the object to come to the foreground in the patient’s words (Thibierge and Morin, 2010. In misidentification syndromes, as in other psychotic syndromes, one can also observe a damage of the specular image as well as an absence of object repression. This leads us to question whether, in the psychiatric disorders related to a damaged specular image, cognition disorders can be studied and managed using the same methods as for neurotic patients.

Improved word recognition for observers with age-related maculopathies using compensation filters

Science.gov (United States)

Lawton, Teri B.

1988-01-01

A method for improving word recognition for people with age-related maculopathies, which cause a loss of central vision, is discussed. It is found that the use of individualized compensation filters based on an person's normalized contrast sensitivity function can improve word recognition for people with age-related maculopathies. It is shown that 27-70 pct more magnification is needed for unfiltered words compared to filtered words. The improvement in word recognition is positively correlated with the severity of vision loss.

The cingulo-opercular network provides word-recognition benefit.

Science.gov (United States)

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.

The asymmetric distribution of informative face information during gender recognition.

Science.gov (United States)

Hu, Fengpei; Hu, Huan; Xu, Lian; Qin, Jungang

2013-02-01

Recognition of the gender of a face is important in social interactions. In the current study, the distribution of informative facial information was systematically examined during gender judgment using two methods, Bubbles and Focus windows techniques. Two experiments found that the most informative information was around the eyes, followed by the mouth and nose. Other parts of the face contributed to the gender recognition but were less important. The left side of the face was used more during gender recognition in two experiments. These results show mainly areas around the eyes are used for gender judgment and demonstrate perceptual asymmetry with a normal (non-chimeric) face.

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

Science.gov (United States)

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

1984-02-01

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

A Proposed Arabic Handwritten Text Normalization Method

Directory of Open Access Journals (Sweden)

Tarik Abu-Ain

2014-11-01

Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

USE OF IMAGE ENHANCEMENT TECHNIQUES FOR IMPROVING REAL TIME FACE RECOGNITION EFFICIENCY ON WEARABLE GADGETS

Directory of Open Access Journals (Sweden)

MUHAMMAD EHSAN RANA

2017-01-01

Full Text Available The objective of this research is to study the effects of image enhancement techniques on face recognition performance of wearable gadgets with an emphasis on recognition rate.In this research, a number of image enhancement techniques are selected that include brightness normalization, contrast normalization, sharpening, smoothing, and various combinations of these. Subsequently test images are obtained from AT&T database and Yale Face Database B to investigate the effect of these image enhancement techniques under various conditions such as change of illumination and face orientation and expression.The evaluation of data, collected during this research, revealed that the effect of image pre-processing techniques on face recognition highly depends on the illumination condition under which these images are taken. It is revealed that the benefit of applying image enhancement techniques on face images is best seen when there is high variation of illumination among images. Results also indicate that highest recognition rate is achieved when images are taken under low light condition and image contrast is enhanced using histogram equalization technique and then image noise is reduced using median smoothing filter. Additionally combination of contrast normalization and mean smoothing filter shows good result in all scenarios. Results obtained from test cases illustrate up to 75% improvement in face recognition rate when image enhancement is applied to images in given scenarios.

Reliable Gait Recognition Using 3D Reconstructions and Random Forests - An Anthropometric Approach

DEFF Research Database (Denmark)

Sandau, Martin; Heimbürger, Rikke V.; Jensen, Karl E.

2016-01-01

reliable recognition. Sixteen participants performed normal walking where 3D reconstructions were obtained continually. Segment lengths and kinematics from the extremities were manually extracted by eight expert observers. The results showed that all the participants were recognized, assuming the same...... expert annotated the data. Recognition based on data annotated by different experts was less reliable achieving 72.6% correct recognitions as some parameters were heavily affected by interobserver variability. This study verified that 3D reconstructions are feasible for forensic gait analysis...

Facial Expression Recognition Through Machine Learning

Directory of Open Access Journals (Sweden)

Nazia Perveen

2015-08-01

Full Text Available Facial expressions communicate non-verbal cues which play an important role in interpersonal relations. Automatic recognition of facial expressions can be an important element of normal human-machine interfaces it might likewise be utilized as a part of behavioral science and in clinical practice. In spite of the fact that people perceive facial expressions for all intents and purposes immediately solid expression recognition by machine is still a challenge. From the point of view of automatic recognition a facial expression can be considered to comprise of disfigurements of the facial parts and their spatial relations or changes in the faces pigmentation. Research into automatic recognition of the facial expressions addresses the issues encompassing the representation and arrangement of static or dynamic qualities of these distortions or face pigmentation. We get results by utilizing the CVIPtools. We have taken train data set of six facial expressions of three persons and for train data set purpose we have total border mask sample 90 and 30 border mask sample for test data set purpose and we use RST- Invariant features and texture features for feature analysis and then classified them by using k- Nearest Neighbor classification algorithm. The maximum accuracy is 90.

Character context: a shape descriptor for Arabic handwriting recognition

Science.gov (United States)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Use of digital speech recognition in diagnostics radiology

International Nuclear Information System (INIS)

Arndt, H.; Stockheim, D.; Mutze, S.; Petersein, J.; Gregor, P.; Hamm, B.

1999-01-01

Purpose: Applicability and benefits of digital speech recognition in diagnostic radiology were tested using the speech recognition system SP 6000. Methods: The speech recognition system SP 6000 was integrated into the network of the institute and connected to the existing Radiological Information System (RIS). Three subjects used this system for writing 2305 findings from dictation. After the recognition process the date, length of dictation, time required for checking/correction, kind of examination and error rate were recorded for every dictation. With the same subjects, a correlation was performed with 625 conventionally written finding. Results: After an 1-hour initial training the average error rates were 8.4 to 13.3%. The first adaptation of the speech recognition system (after nine days) decreased the average error rates to 2.4 to 10.7% due to the ability of the program to learn. The 2 nd and 3 rd adaptations resulted only in small changes of the error rate. An individual comparison of the error rate developments in the same kind of investigation showed the relative independence of the error rate on the individual user. Conclusion: The results show that the speech recognition system SP 6000 can be evaluated as an advantageous alternative for quickly recording radiological findings. A comparison between manually writing and dictating the findings verifies the individual differences of the writing speeds and shows the advantage of the application of voice recognition when faced with normal keyboard performance. (orig.) [de

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

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2010-01-01

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Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

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

Face Recognition by Metropolitan Police Super-Recognisers.

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Robertson, David J; Noyes, Eilidh; Dowsett, Andrew J; Jenkins, Rob; Burton, A Mike

2016-01-01

Face recognition is used to prove identity across a wide variety of settings. Despite this, research consistently shows that people are typically rather poor at matching faces to photos. Some professional groups, such as police and passport officers, have been shown to perform just as poorly as the general public on standard tests of face recognition. However, face recognition skills are subject to wide individual variation, with some people showing exceptional ability-a group that has come to be known as 'super-recognisers'. The Metropolitan Police Force (London) recruits 'super-recognisers' from within its ranks, for deployment on various identification tasks. Here we test four working super-recognisers from within this police force, and ask whether they are really able to perform at levels above control groups. We consistently find that the police 'super-recognisers' perform at well above normal levels on tests of unfamiliar and familiar face matching, with degraded as well as high quality images. Recruiting employees with high levels of skill in these areas, and allocating them to relevant tasks, is an efficient way to overcome some of the known difficulties associated with unfamiliar face recognition.

Recognition of Face and Emotional Facial Expressions in Autism

Directory of Open Access Journals (Sweden)

Muhammed Tayyib Kadak

2013-03-01

Full Text Available Autism is a genetically transferred neurodevelopmental disorder characterized by severe and permanent deficits in many interpersonal relation areas like communication, social interaction and emotional responsiveness. Patients with autism have deficits in face recognition, eye contact and recognition of emotional expression. Both recognition of face and expression of facial emotion carried on face processing. Structural and functional impairment in fusiform gyrus, amygdala, superior temporal sulcus and other brain regions lead to deficits in recognition of face and facial emotion. Therefore studies suggest that face processing deficits resulted in problems in areas of social interaction and emotion in autism. Studies revealed that children with autism had problems in recognition of facial expression and used mouth region more than eye region. It was also shown that autistic patients interpreted ambiguous expressions as negative emotion. In autism, deficits related in various stages of face processing like detection of gaze, face identity, recognition of emotional expression were determined, so far. Social interaction impairments in autistic spectrum disorders originated from face processing deficits during the periods of infancy, childhood and adolescence. Recognition of face and expression of facial emotion could be affected either automatically by orienting towards faces after birth, or by “learning” processes in developmental periods such as identity and emotion processing. This article aimed to review neurobiological basis of face processing and recognition of emotional facial expressions during normal development and in autism.

Emotion effects on implicit and explicit musical memory in normal aging.

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Narme, Pauline; Peretz, Isabelle; Strub, Marie-Laure; Ergis, Anne-Marie

2016-12-01

Normal aging affects explicit memory while leaving implicit memory relatively spared. Normal aging also modifies how emotions are processed and experienced, with increasing evidence that older adults (OAs) focus more on positive information than younger adults (YAs). The aim of the present study was to investigate how age-related changes in emotion processing influence explicit and implicit memory. We used emotional melodies that differed in terms of valence (positive or negative) and arousal (high or low). Implicit memory was assessed with a preference task exploiting exposure effects, and explicit memory with a recognition task. Results indicated that effects of valence and arousal interacted to modulate both implicit and explicit memory in YAs. In OAs, recognition was poorer than in YAs; however, recognition of positive and high-arousal (happy) studied melodies was comparable. Insofar as socioemotional selectivity theory (SST) predicts a preservation of the recognition of positive information, our findings are not fully consistent with the extension of this theory to positive melodies since recognition of low-arousal (peaceful) studied melodies was poorer in OAs. In the preference task, YAs showed stronger exposure effects than OAs, suggesting an age-related decline of implicit memory. This impairment is smaller than the one observed for explicit memory (recognition), extending to the musical domain the dissociation between explicit memory decline and implicit memory relative preservation in aging. Finally, the disproportionate preference for positive material seen in OAs did not translate into stronger exposure effects for positive material suggesting no age-related emotional bias in implicit memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Chinese character recognition based on Gabor feature extraction and CNN

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Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Delayed Face Recognition in Children and Adolescents with Autism Spectrum Disorders

Directory of Open Access Journals (Sweden)

Zahra Shahrivar

2012-06-01

Full Text Available Objective: Children with autism spectrum disorders (ASDs have great problems in social interactions including face recognition. There are many studies reporting deficits in face memory in individuals with ASDs. On the other hand, some studies indicate that this kind of memory is intact in this group. In the present study, delayed face recognition has been investigated in children and adolescents with ASDs compared to the age and sex matched typically developing group.Methods: In two sessions, Benton Facial Recognition Test was administered to 15 children and adolescents with ASDs (high functioning autism and Asperger syndrome and to 15 normal participants, ages 8-17 years. In the first condition, the long form of Benton Facial Recognition Test was used without any delay. In the second session, this test was administered with 15 seconds delay after one week. The reaction times and correct responses were measured in both conditions as the dependent variables.Results: Comparison of the reaction times and correct responses in the two groups revealed no significant difference in delayed and non-delayed conditions. Furthermore, no significant difference was observed between the two conditions in ASDs patients when comparing the variables. Although a significant correlation (p<0.05 was found between delayed and non-delayed conditions, it was not significant in the normal group. Moreover, data analysis revealed no significant difference between the two groups in the two conditions when the IQ was considered as covariate. Conclusion: In this study, it was found that the ability to recognize faces in simultaneous and delayed conditions is similar between adolescents with ASDs and their normal counterparts.

Implementation of age and gender recognition system for intelligent digital signage

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

2015-12-01

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

Neural network application for thermal image recognition of low-resolution objects

Science.gov (United States)

Fang, Yi-Chin; Wu, Bo-Wen

2007-02-01

In the ever-changing situation on a battle field, accurate recognition of a distant object is critical to a commander's decision-making and the general public's safety. Efficiently distinguishing between an enemy's armoured vehicles and ordinary civilian houses under all weather conditions has become an important research topic. This study presents a system for recognizing an armoured vehicle by distinguishing marks and contours. The characteristics of 12 different shapes and 12 characters are used to explore thermal image recognition under the circumstance of long distance and low resolution. Although the recognition capability of human eyes is superior to that of artificial intelligence under normal conditions, it tends to deteriorate substantially under long-distance and low-resolution scenarios. This study presents an effective method for choosing features and processing images. The artificial neural network technique is applied to further improve the probability of accurate recognition well beyond the limit of the recognition capability of human eyes.

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

Science.gov (United States)

Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. To develop our ML-based Bio-NER system, we employ conditional

Standard-Chinese Lexical Neighborhood Test in normal-hearing young children.

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Liu, Chang; Liu, Sha; Zhang, Ning; Yang, Yilin; Kong, Ying; Zhang, Luo

2011-06-01

The purposes of the present study were to establish the Standard-Chinese version of Lexical Neighborhood Test (LNT) and to examine the lexical and age effects on spoken-word recognition in normal-hearing children. Six lists of monosyllabic and six lists of disyllabic words (20 words/list) were selected from the database of daily speech materials for normal-hearing (NH) children of ages 3-5 years. The lists were further divided into "easy" and "hard" halves according to the word frequency and neighborhood density in the database based on the theory of Neighborhood Activation Model (NAM). Ninety-six NH children (age ranged between 4.0 and 7.0 years) were divided into three different age groups of 1-year intervals. Speech-perception tests were conducted using the Standard-Chinese monosyllabic and disyllabic LNT. The inter-list performance was found to be equivalent and inter-rater reliability was high with 92.5-95% consistency. Results of word-recognition scores showed that the lexical effects were all significant. Children scored higher with disyllabic words than with monosyllabic words. "Easy" words scored higher than "hard" words. The word-recognition performance also increased with age in each lexical category. A multiple linear regression analysis showed that neighborhood density, age, and word frequency appeared to have increasingly more contributions to Chinese word recognition. The results of the present study indicated that performances of Chinese word recognition were influenced by word frequency, age, and neighborhood density, with word frequency playing a major role. These results were consistent with those in other languages, supporting the application of NAM in the Chinese language. The development of Standard-Chinese version of LNT and the establishment of a database of children of 4-6 years old can provide a reliable means for spoken-word recognition test in children with hearing impairment. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Lexical-Access Ability and Cognitive Predictors of Speech Recognition in Noise in Adult Cochlear Implant Users

OpenAIRE

Kaandorp, Marre W.; Smits, Cas; Merkus, Paul; Festen, Joost M.; Goverts, S. Theo

2017-01-01

Not all of the variance in speech-recognition performance of cochlear implant (CI) users can be explained by biographic and auditory factors. In normal-hearing listeners, linguistic and cognitive factors determine most of speech-in-noise performance. The current study explored specifically the influence of visually measured lexical-access ability compared with other cognitive factors on speech recognition of 24 postlingually deafened CI users. Speech-recognition performance was measured with ...

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

Visual recognition of permuted words

Science.gov (United States)

Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

2010-02-01

In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

Priming effects in Chinese character recognition for Chinese children with developmental dyslexia

Institute of Scientific and Technical Information of China (English)

Yuliang Zou; Jing Wang; Hanrong Wu

2009-01-01

BACKGROUND:Dyslexic children exhibit reading ability unmatched to age,although they possess normal intelligence and are well educated.OBJECTIVE:To examine the performance of dyslexic children in Chinese characters visual recognition tasks and to investigate the relationship between priming effect in character recognition and dyslexia.DESIGN,TIME AND SETTING:A case-control study was performed at the Department of Children and Adolescent Health and Maternal Care,School of Public Health,Tongji Medical College,Huazhong University of Science and Technology between March and June 2007.PARTICIPANTS:A total of 75 primary school students in grades 3 and 5 were selected from two primary schools in Wuhan City,Hubei province,China,and were assigned to three groups.(1) Reading disability (RD,n=25);(2) chronological age (CA) group (n=25 normal readers that were intelligence quotient and age-matched to the RD group);(3) reading level (RL) group (n=25 normal readers that were intelligence quotient and RL-matched to the RD group).All children were right-handed and had normal or corrected-to-normal vision.METHODS:Recognition of target characters was performed in each child using a masked prime paradigm.Recognition speed and accuracy of graphic,phonological,and semantic characters were examined.Simultaneously,data,with respect to response time for each target character and error rate,were recorded to calculate facilitation values (unrelated RT-related RT).MAIN OUTCOME MEASURES:Response time,facilitation,and error rate in Chinese character recognition task were calculated.RESULTS:The baseline-adjusted facilitation of graphic,phonological,and semantic priming for dyslexic children was -0.010,-0.010,and 0.001,respectively.Dyslexic children displayed inhibition in graphic and phonological prime conditions.Facilitations under the three prime conditions were 0.026,0.026,and 0.022 for the CA group.In the RL group,results were 0.062,0.058,and 0.031 respectively.The differences of baseline

Normal composite face effects in developmental prosopagnosia.

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Biotti, Federica; Wu, Esther; Yang, Hua; Jiahui, Guo; Duchaine, Bradley; Cook, Richard

2017-10-01

Upright face perception is thought to involve holistic processing, whereby local features are integrated into a unified whole. Consistent with this view, the top half of one face appears to fuse perceptually with the bottom half of another, when aligned spatially and presented upright. This 'composite face effect' reveals a tendency to integrate information from disparate regions when faces are presented canonically. In recent years, the relationship between susceptibility to the composite effect and face recognition ability has received extensive attention both in participants with normal face recognition and participants with developmental prosopagnosia. Previous results suggest that individuals with developmental prosopagnosia may show reduced susceptibility to the effect suggestive of diminished holistic face processing. Here we describe two studies that examine whether developmental prosopagnosia is associated with reduced composite face effects. Despite using independent samples of developmental prosopagnosics and different composite procedures, we find no evidence for reduced composite face effects. The experiments yielded similar results; highly significant composite effects in both prosopagnosic groups that were similar in magnitude to the effects found in participants with normal face processing. The composite face effects exhibited by both samples and the controls were greatly diminished when stimulus arrangements were inverted. Our finding that the whole-face binding process indexed by the composite effect is intact in developmental prosopagnosia indicates that other factors are responsible for developmental prosopagnosia. These results are also inconsistent with suggestions that susceptibility to the composite face effect and face recognition ability are tightly linked. While the holistic process revealed by the composite face effect may be necessary for typical face perception, it is not sufficient; individual differences in face recognition ability

Examination of the neighborhood activation theory in normal and hearing-impaired listeners.

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Dirks, D D; Takayanagi, S; Moshfegh, A; Noffsinger, P D; Fausti, S A

2001-02-01

Experiments were conducted to examine the effects of lexical information on word recognition among normal hearing listeners and individuals with sensorineural hearing loss. The lexical factors of interest were incorporated in the Neighborhood Activation Model (NAM). Central to this model is the concept that words are recognized relationally in the context of other phonemically similar words. NAM suggests that words in the mental lexicon are organized into similarity neighborhoods and the listener is required to select the target word from competing lexical items. Two structural characteristics of similarity neighborhoods that influence word recognition have been identified; "neighborhood density" or the number of phonemically similar words (neighbors) for a particular target item and "neighborhood frequency" or the average frequency of occurrence of all the items within a neighborhood. A third lexical factor, "word frequency" or the frequency of occurrence of a target word in the language, is assumed to optimize the word recognition process by biasing the system toward choosing a high frequency over a low frequency word. Three experiments were performed. In the initial experiments, word recognition for consonant-vowel-consonant (CVC) monosyllables was assessed in young normal hearing listeners by systematically partitioning the items into the eight possible lexical conditions that could be created by two levels of the three lexical factors, word frequency (high and low), neighborhood density (high and low), and average neighborhood frequency (high and low). Neighborhood structure and word frequency were estimated computationally using a large, on-line lexicon-based Webster's Pocket Dictionary. From this program 400 highly familiar, monosyllables were selected and partitioned into eight orthogonal lexical groups (50 words/group). The 400 words were presented randomly to normal hearing listeners in speech-shaped noise (Experiment 1) and "in quiet" (Experiment 2) as

Speech Recognition in Adults With Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging.

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Moberly, Aaron C; Harris, Michael S; Boyce, Lauren; Nittrouer, Susan

2017-04-14

Models of speech recognition suggest that "top-down" linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced years of hearing loss obtains a cochlear implant. Thirty adults with cochlear implants and 30 age-matched controls with age-normal hearing underwent testing of verbal working memory using digit span and serial recall of words. Phonological capacities were assessed using a lexical decision task and nonword repetition. Recognition of words in sentences in speech-shaped noise was measured. Implant users had only slightly poorer working memory accuracy than did controls and only on serial recall of words; however, phonological sensitivity was highly impaired. Working memory did not facilitate speech recognition in noise for either group. Phonological sensitivity predicted sentence recognition for implant users but not for listeners with normal hearing. Clinical speech recognition outcomes for adult implant users relate to the ability of these users to process phonological information. Results suggest that phonological capacities may serve as potential clinical targets through rehabilitative training. Such novel interventions may be particularly helpful for older adult implant users.

PEAK TRACKING WITH A NEURAL NETWORK FOR SPECTRAL RECOGNITION

NARCIS (Netherlands)

COENEGRACHT, PMJ; METTING, HJ; VANLOO, EM; SNOEIJER, GJ; DOORNBOS, DA

1993-01-01

A peak tracking method based on a simulated feed-forward neural network with back-propagation is presented. The network uses the normalized UV spectra and peak areas measured in one chromatogram for peak recognition. It suffices to train the network with only one set of spectra recorded in one

Infliximab ameliorates AD-associated object recognition memory impairment.

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Kim, Dong Hyun; Choi, Seong-Min; Jho, Jihoon; Park, Man-Seok; Kang, Jisu; Park, Se Jin; Ryu, Jong Hoon; Jo, Jihoon; Kim, Hyun Hee; Kim, Byeong C

2016-09-15

Dysfunctions in the perirhinal cortex (PRh) are associated with visual recognition memory deficit, which is frequently detected in the early stage of Alzheimer's disease. Muscarinic acetylcholine receptor-dependent long-term depression (mAChR-LTD) of synaptic transmission is known as a key pathway in eliciting this type of memory, and Tg2576 mice expressing enhanced levels of Aβ oligomers are found to have impaired mAChR-LTD in this brain area at as early as 3 months of age. We found that the administration of Aβ oligomers in young normal mice also induced visual recognition memory impairment and perturbed mAChR-LTD in mouse PRh slices. In addition, when mice were treated with infliximab, a monoclonal antibody against TNF-α, visual recognition memory impaired by pre-administered Aβ oligomers dramatically improved and the detrimental Aβ effect on mAChR-LTD was annulled. Taken together, these findings suggest that Aβ-induced inflammation is mediated through TNF-α signaling cascades, disturbing synaptic transmission in the PRh, and leading to visual recognition memory deficits. Copyright © 2016 Elsevier B.V. All rights reserved.

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

International Nuclear Information System (INIS)

Invernizzi, Michel.

1982-07-01

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

Automatic identification of otological drilling faults: an intelligent recognition algorithm.

Science.gov (United States)

Cao, Tianyang; Li, Xisheng; Gao, Zhiqiang; Feng, Guodong; Shen, Peng

2010-06-01

This article presents an intelligent recognition algorithm that can recognize milling states of the otological drill by fusing multi-sensor information. An otological drill was modified by the addition of sensors. The algorithm was designed according to features of the milling process and is composed of a characteristic curve, an adaptive filter and a rule base. The characteristic curve can weaken the impact of the unstable normal milling process and reserve the features of drilling faults. The adaptive filter is capable of suppressing interference in the characteristic curve by fusing multi-sensor information. The rule base can identify drilling faults through the filtering result data. The experiments were repeated on fresh porcine scapulas, including normal milling and two drilling faults. The algorithm has high rates of identification. This study shows that the intelligent recognition algorithm can identify drilling faults under interference conditions. (c) 2010 John Wiley & Sons, Ltd.

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

Science.gov (United States)

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...

Developmental prosopagnosia and super-recognition: no special role for surface reflectance processing.

Science.gov (United States)

Russell, Richard; Chatterjee, Garga; Nakayama, Ken

2012-01-01

Face recognition by normal subjects depends in roughly equal proportions on shape and surface reflectance cues, while object recognition depends predominantly on shape cues. It is possible that developmental prosopagnosics are deficient not in their ability to recognize faces per se, but rather in their ability to use reflectance cues. Similarly, super-recognizers' exceptional ability with face recognition may be a result of superior surface reflectance perception and memory. We tested this possibility by administering tests of face perception and face recognition in which only shape or reflectance cues are available to developmental prosopagnosics, super-recognizers, and control subjects. Face recognition ability and the relative use of shape and pigmentation were unrelated in all the tests. Subjects who were better at using shape or reflectance cues were also better at using the other type of cue. These results do not support the proposal that variation in surface reflectance perception ability is the underlying cause of variation in face recognition ability. Instead, these findings support the idea that face recognition ability is related to neural circuits using representations that integrate shape and pigmentation information. Copyright © 2011 Elsevier Ltd. All rights reserved.

Toward noncooperative iris recognition: a classification approach using multiple signatures.

Science.gov (United States)

Proença, Hugo; Alexandre, Luís A

2007-04-01

This paper focuses on noncooperative iris recognition, i.e., the capture of iris images at large distances, under less controlled lighting conditions, and without active participation of the subjects. This increases the probability of capturing very heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstructions and reflections). Current iris recognition systems are unable to deal with noisy data and substantially increase their error rates, especially the false rejections, in these conditions. We propose an iris classification method that divides the segmented and normalized iris image into six regions, makes an independent feature extraction and comparison for each region, and combines each of the dissimilarity values through a classification rule. Experiments show a substantial decrease, higher than 40 percent, of the false rejection rates in the recognition of noisy iris images.

Dopamine D4 receptor stimulation contributes to novel object recognition: Relevance to cognitive impairment in schizophrenia.

Science.gov (United States)

Miyauchi, Masanori; Neugebauer, Nichole M; Meltzer, Herbert Y

2017-04-01

Several atypical antipsychotic drugs (APDs) have high affinity for the dopamine (DA) D 4 receptor, but the relevance to the efficacy for the treatment of cognitive impairment associated with schizophrenia (CIAS) is poorly understood. The aim of this study was to investigate the effects of D 4 receptor stimulation or blockade on novel object recognition (NOR) in normal rats and on the sub-chronic phencyclidine (PCP)-induced novel object recognition deficit. The effect of the D 4 agonist, PD168077, and the D 4 antagonist, L-745,870, were studied alone, and in combination with clozapine and lurasidone. In normal rats, L-745,870 impaired novel object recognition, whereas PD168077 had no effect. PD168077 acutely reversed the sub-chronic phencyclidine-induced novel object recognition deficit. Co-administration of a sub-effective dose (SED) of PD168077 with a sub-effective dose of lurasidone also reversed this deficit, but a sub-effective dose of PD168077 with a sub-effective dose of clozapine, a more potent D 4 antagonist than lurasidone, did not reverse the sub-chronic phencyclidine-induced novel object recognition deficit. At a dose that did not induce a novel object recognition deficit, L-745,870 blocked the ability of clozapine, but not lurasidone, to reverse the novel object recognition deficit. D 4 receptor agonism has a beneficial effect on novel object recognition in sub-chronic PCP-treated rats and augments the cognitive enhancing efficacy of an atypical antipsychotic drug that lacks affinity for the D 4 receptor, lurasidone.

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

Science.gov (United States)

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.

Limiares de reconhecimento de sentenças no ruído, em campo livre: valores de referência para adultos normo-ouvintes Speech recognition thresholds in noisy areas: reference values for normal hearing adults

Directory of Open Access Journals (Sweden)

Marília Oliveira Henriques

2008-04-01

Full Text Available Nas clínicas de audiologia, as queixas de dificuldade de compreensão da fala em ambientes ruidosos são freqüentes, mesmo para indivíduos normo-ouvintes. Assim, o audiologista deve não só identificar uma perda auditiva, mas também analisar a compreensão da fala, em condições de comunicação próximas às encontradas no cotidiano. OBJETIVO: Determinar o valor de referência para os limiares de reconhecimento de sentenças no ruído, em campo livre, para indivíduos adultos normo-ouvintes. MATERIAL E MÉTODO: O experimento foi realizado nos anos de 2005 e 2006. Participaram da pesquisa 150 indivíduos adultos normo-ouvintes, com idade entre 18 e 64 anos, avaliados em cabine acusticamente tratada. Realizou-se a avaliação a partir da aplicação do teste Listas de Sentenças em Português. As listas de sentenças foram apresentadas em campo livre, na presença de um ruído competitivo, na intensidade fixa de 65 dB A. O ângulo de incidência de ambos os estímulos foi de 0º- 0º azimute. RESULTADOS E CONCLUSÃO: Os limiares de reconhecimento de sentenças em campo-livre foram obtidos na relação sinal-ruído de -8,14 dB A, sendo este o valor de referência para indivíduos normo-ouvintes.In audiology clinics, complaints about difficulties in speech recognition in noise environments are frequent, even for normal-hearing individuals. Thus, the audiologist must not only identify a hearing loss, but also analyze speech recognition, under noisy conditions similar to those found in our daily lives. AIM: Determine the reference value for the recognition of phrases under noisy conditions, in the free field, for adult normal hearing patients. MATERIALS AND METHODS: This study was carried out in 2005 and 2006. We had 150 adult normal hearing individuals participating, with ages between 18 and 64 years, assessed in a sound-proof booth. We evaluation was based on lists of phrases in Portuguese. The phrases lists were presented in the free field

Development of the Word Auditory Recognition and Recall Measure: A Working Memory Test for Use in Rehabilitative Audiology.

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Smith, Sherri L; Pichora-Fuller, M Kathleen; Alexander, Genevieve

The purpose of this study was to develop the Word Auditory Recognition and Recall Measure (WARRM) and to conduct the inaugural evaluation of the performance of younger adults with normal hearing, older adults with normal to near-normal hearing, and older adults with pure-tone hearing loss on the WARRM. The WARRM is a new test designed for concurrently assessing word recognition and auditory working memory performance in adults who may have pure-tone hearing loss. The test consists of 100 monosyllabic words based on widely used speech-recognition test materials. The 100 words are presented in recall set sizes of 2, 3, 4, 5, and 6 items, with 5 trials in each set size. The WARRM yields a word-recognition score and a recall score. The WARRM was administered to all participants in three listener groups under two processing conditions in a mixed model (between-subjects, repeated measures) design. The between-subjects factor was group, with 48 younger listeners with normal audiometric thresholds (younger listeners with normal hearing [YNH]), 48 older listeners with normal thresholds through 3000 Hz (older listeners with normal hearing [ONH]), and 48 older listeners with sensorineural hearing loss (older listeners with hearing loss [OHL]). The within-subjects factor was WARRM processing condition (no additional task or with an alphabet judgment task). The associations between results on the WARRM test and results on a battery of other auditory and memory measures were examined. Word-recognition performance on the WARRM was not affected by processing condition or set size and was near ceiling for the YNH and ONH listeners (99 and 98%, respectively) with both groups performing significantly better than the OHL listeners (83%). The recall results were significantly better for the YNH, ONH, and OHL groups with no processing (93, 84, and 75%, respectively) than with the alphabet processing (86, 77, and 70%). In both processing conditions, recall was best for YNH, followed by

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

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Hung Hsieh-Chuan

2006-12-01

Full Text Available Abstract Background Biomedical named entity recognition (Bio-NER is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized and at least one class tag (e.g., B-protein, the beginning of a protein name. However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2 cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words. We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. Results To develop our ML

Cognition and speech-in-noise recognition: the role of proactive interference.

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Ellis, Rachel J; Rönnberg, Jerker

2014-01-01

Complex working memory (WM) span tasks have been shown to predict speech-in-noise (SIN) recognition. Studies of complex WM span tasks suggest that, rather than indexing a single cognitive process, performance on such tasks may be governed by separate cognitive subprocesses embedded within WM. Previous research has suggested that one such subprocess indexed by WM tasks is proactive interference (PI), which refers to difficulties memorizing current information because of interference from previously stored long-term memory representations for similar information. The aim of the present study was to investigate phonological PI and to examine the relationship between PI (semantic and phonological) and SIN perception. A within-subjects experimental design was used. An opportunity sample of 24 young listeners with normal hearing was recruited. Measures of resistance to, and release from, semantic and phonological PI were calculated alongside the signal-to-noise ratio required to identify 50% of keywords correctly in a SIN recognition task. The data were analyzed using t-tests and correlations. Evidence of release from and resistance to semantic interference was observed. These measures correlated significantly with SIN recognition. Limited evidence of phonological PI was observed. The results show that capacity to resist semantic PI can be used to predict SIN recognition scores in young listeners with normal hearing. On the basis of these findings, future research will focus on investigating whether tests of PI can be used in the treatment and/or rehabilitation of hearing loss. American Academy of Audiology.

Does comorbid anxiety counteract emotion recognition deficits in conduct disorder?

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Short, Roxanna M L; Sonuga-Barke, Edmund J S; Adams, Wendy J; Fairchild, Graeme

2016-08-01

Previous research has reported altered emotion recognition in both conduct disorder (CD) and anxiety disorders (ADs) - but these effects appear to be of different kinds. Adolescents with CD often show a generalised pattern of deficits, while those with ADs show hypersensitivity to specific negative emotions. Although these conditions often cooccur, little is known regarding emotion recognition performance in comorbid CD+ADs. Here, we test the hypothesis that in the comorbid case, anxiety-related emotion hypersensitivity counteracts the emotion recognition deficits typically observed in CD. We compared facial emotion recognition across four groups of adolescents aged 12-18 years: those with CD alone (n = 28), ADs alone (n = 23), cooccurring CD+ADs (n = 20) and typically developing controls (n = 28). The emotion recognition task we used systematically manipulated the emotional intensity of facial expressions as well as fixation location (eye, nose or mouth region). Conduct disorder was associated with a generalised impairment in emotion recognition; however, this may have been modulated by group differences in IQ. AD was associated with increased sensitivity to low-intensity happiness, disgust and sadness. In general, the comorbid CD+ADs group performed similarly to typically developing controls. Although CD alone was associated with emotion recognition impairments, ADs and comorbid CD+ADs were associated with normal or enhanced emotion recognition performance. The presence of comorbid ADs appeared to counteract the effects of CD, suggesting a potentially protective role, although future research should examine the contribution of IQ and gender to these effects. © 2016 Association for Child and Adolescent Mental Health.

Impact of novelty and type of material on recognition in healthy older adults and persons with mild cognitive impairment.

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Belleville, Sylvie; Ménard, Marie-Claude; Lepage, Emilie

2011-08-01

The goal of this study was to assess the effect of novelty on correct recognition (hit minus false alarms) and on recollection and familiarity processes in normal aging and amnestic mild cognitive impairment (MCI). Recognition tasks compared well-known and novel stimuli in the verbal domain (words vs. pseudowords) and in the musical domain (well-known vs. novel melodies). Results indicated that novel materials associated with lower correct recognition and lower recollection, an effect that can be related to its lower amenability to elaborative encoding in comparison with well-known items. Results also indicated that normal aging impairs recognition of well-known items, whereas MCI impairs recognition of novel items only. Healthy older adults showed impaired recollection and familiarity relative to younger controls and individuals with MCI showed impaired recollection relative to healthy older adults. The recollection deficit in healthy older adults and persons with MCI and their impaired recognition of well-known items is compatible with the difficulty both groups have in encoding information in an elaborate manner. In turn, familiarity deficit could be related to impaired frontal functioning. Therefore, novelty of material has a differential impact on recognition in persons with age-related memory disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

New methods in iris recognition.

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Daugman, John

2007-10-01

This paper presents the following four advances in iris recognition: 1) more disciplined methods for detecting and faithfully modeling the iris inner and outer boundaries with active contours, leading to more flexible embedded coordinate systems; 2) Fourier-based methods for solving problems in iris trigonometry and projective geometry, allowing off-axis gaze to be handled by detecting it and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations, depending on the amount of iris data that is available in images and the required scale of database search. Statistical results are presented based on 200 billion iris cross-comparisons that were generated from 632500 irises in the United Arab Emirates database to analyze the normalization issues raised in different regions of receiver operating characteristic curves.

Object recognition with hierarchical discriminant saliency networks.

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Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

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

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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.

Reactor noise analysis by statistical pattern recognition methods

International Nuclear Information System (INIS)

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

1976-01-01

A multivariate statistical pattern recognition system for reactor noise analysis is presented. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system

Recognition Memory in Amnestic-Mild Cognitive Impairment: Insights from Event-Related Potentials

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David A Wolk

2013-12-01

Full Text Available Episodic memory loss is the hallmark cognitive dysfunction associated with Alzheimer’s Disease (AD. Amnestic Mild Cognitive Impairment (a-MCI frequently represents a transitional stage between normal aging and early AD. A better understanding of the qualitative features of memory loss in a-MCI may have important implications for predicting those most likely to harbor AD-related pathology and for disease monitoring. Dual process models of memory argue that recognition memory is subserved by the dissociable processes of recollection and familiarity. Work studying recognition memory in a-MCI from this perspective has been controversial, particularly with regard to the integrity of familiarity. Event-related potentials (ERPs offer an alternative means for assessing these functions without the associated assumptions of behavioral estimation methods. ERPs were recorded while a-MCI patients and cognitively normal (CN age-matched adults performed a recognition memory task. When retrieval success was measured (hits versus correct rejections in which performance was matched by group, a-MCI patients displayed similar neural correlates to that of the CN group, including modulation of the FN400 and the late parietal complex (LPC which are thought to index familiarity and recollection, respectively. Alternatively, when the integrity of these components were measured based on retrieval attempts (studied versus unstudied items, a-MCI patients displayed a reduced FN400 and LPC. Furthermore, modulation of the FN400 correlated with a behavioral estimate of familiarity and the LPC with a behavioral estimates of recollection obtained in a separate experiment in the same individuals, consistent with the proposed mappings of these indices. These results support a global decline of recognition memory in a-MCI, which suggests that the memory loss of prodromal AD may be qualitatively distinct from normal aging.

Gaze recognition in high-functioning autistic patients. Evidence from functional MRI

International Nuclear Information System (INIS)

Takebayashi, Hiroko; Ogai, Masahiro; Matsumoto, Hideo

2006-01-01

We examined whether patients with high-functioning autistic disorder (AD) would exhibit abnormal activation in brain regions implicated in the functioning of theory of mind (TOM) during gaze recognition. We investigated brain activity during gaze recognition in 5 patients with high-functioning AD and 9 normal subjects, using functional magnetic resonance imaging. On the gaze task, more activation was found in the left middle frontal gyrus, the right intraparietal sulcus, and the precentral and inferior parietal gyri bilaterally in controls than in AD patients, whereas the patient group showed more powerful signal changes in the left superior temporal gyrus, the right insula, and the right medial frontal gyrus. These results suggest that high-functioning AD patients have functional abnormalities not only in TOM-related brain regions, but also in widely distributed brain regions that are not normally activated upon the processing of information from another person's gaze. (author)

Gait Recognition Based on Outermost Contour

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Lili Liu

2011-10-01

Full Text Available Gait recognition aims to identify people by the way they walk. In this paper, a simple but e ective gait recognition method based on Outermost Contour is proposed. For each gait image sequence, an adaptive silhouette extraction algorithm is firstly used to segment the frames of the sequence and a series of postprocessing is applied to obtain the normalized silhouette images with less noise. Then a novel feature extraction method based on Outermost Contour is performed. Principal Component Analysis (PCA is adopted to reduce the dimensionality of the distance signals derived from the Outermost Contours of silhouette images. Then Multiple Discriminant Analysis (MDA is used to optimize the separability of gait features belonging to di erent classes. Nearest Neighbor (NN classifier and Nearest Neighbor classifier with respect to class Exemplars (ENN are used to classify the final feature vectors produced by MDA. In order to verify the e ectiveness and robustness of our feature extraction algorithm, we also use two other classifiers: Backpropagation Neural Network (BPNN and Support Vector Machine (SVM for recognition. Experimental results on a gait database of 100 people show that the accuracy of using MDA, BPNN and SVM can achieve 97.67%, 94.33% and 94.67%, respectively.

Does viotin activate violin more than viocin? On the use of visual cues during visual-word recognition.

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Perea, Manuel; Panadero, Victoria

2014-01-01

The vast majority of neural and computational models of visual-word recognition assume that lexical access is achieved via the activation of abstract letter identities. Thus, a word's overall shape should play no role in this process. In the present lexical decision experiment, we compared word-like pseudowords like viotín (same shape as its base word: violín) vs. viocín (different shape) in mature (college-aged skilled readers), immature (normally reading children), and immature/impaired (young readers with developmental dyslexia) word-recognition systems. Results revealed similar response times (and error rates) to consistent-shape and inconsistent-shape pseudowords for both adult skilled readers and normally reading children - this is consistent with current models of visual-word recognition. In contrast, young readers with developmental dyslexia made significantly more errors to viotín-like pseudowords than to viocín-like pseudowords. Thus, unlike normally reading children, young readers with developmental dyslexia are sensitive to a word's visual cues, presumably because of poor letter representations.

Effects of level of processing but not of task enactment on recognition memory in a case of developmental amnesia.

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Gardiner, John M; Brandt, Karen R; Vargha-Khadem, Faraneh; Baddeley, Alan; Mishkin, Mortimer

2006-09-01

We report the performance in four recognition memory experiments of Jon, a young adult with early-onset developmental amnesia whose episodic memory is gravely impaired in tests of recall, but seems relatively preserved in tests of recognition, and who has developed normal levels of performance in tests of intelligence and general knowledge. Jon's recognition performance was enhanced by deeper levels of processing in comparing a more meaningful study task with a less meaningful one, but not by task enactment in comparing performance of an action with reading an action phrase. Both of these variables normally enhance episodic remembering, which Jon claimed to experience. But Jon was unable to support that claim by recollecting what it was that he remembered. Taken altogether, the findings strongly imply that Jon's recognition performance entailed little genuine episodic remembering and that the levels-of-processing effects in Jon reflected semantic, not episodic, memory.

The effects of reverberant self- and overlap-masking on speech recognition in cochlear implant listeners.

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Desmond, Jill M; Collins, Leslie M; Throckmorton, Chandra S

2014-06-01

Many cochlear implant (CI) listeners experience decreased speech recognition in reverberant environments [Kokkinakis et al., J. Acoust. Soc. Am. 129(5), 3221-3232 (2011)], which may be caused by a combination of self- and overlap-masking [Bolt and MacDonald, J. Acoust. Soc. Am. 21(6), 577-580 (1949)]. Determining the extent to which these effects decrease speech recognition for CI listeners may influence reverberation mitigation algorithms. This study compared speech recognition with ideal self-masking mitigation, with ideal overlap-masking mitigation, and with no mitigation. Under these conditions, mitigating either self- or overlap-masking resulted in significant improvements in speech recognition for both normal hearing subjects utilizing an acoustic model and for CI listeners using their own devices.

Optical Pattern Recognition

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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.

Right-Ear Advantage for Speech-in-Noise Recognition in Patients with Nonlateralized Tinnitus and Normal Hearing Sensitivity.

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Tai, Yihsin; Husain, Fatima T

2018-04-01

Despite having normal hearing sensitivity, patients with chronic tinnitus may experience more difficulty recognizing speech in adverse listening conditions as compared to controls. However, the association between the characteristics of tinnitus (severity and loudness) and speech recognition remains unclear. In this study, the Quick Speech-in-Noise test (QuickSIN) was conducted monaurally on 14 patients with bilateral tinnitus and 14 age- and hearing-matched adults to determine the relation between tinnitus characteristics and speech understanding. Further, Tinnitus Handicap Inventory (THI), tinnitus loudness magnitude estimation, and loudness matching were obtained to better characterize the perceptual and psychological aspects of tinnitus. The patients reported low THI scores, with most participants in the slight handicap category. Significant between-group differences in speech-in-noise performance were only found at the 5-dB signal-to-noise ratio (SNR) condition. The tinnitus group performed significantly worse in the left ear than in the right ear, even though bilateral tinnitus percept and symmetrical thresholds were reported in all patients. This between-ear difference is likely influenced by a right-ear advantage for speech sounds, as factors related to testing order and fatigue were ruled out. Additionally, significant correlations found between SNR loss in the left ear and tinnitus loudness matching suggest that perceptual factors related to tinnitus had an effect on speech-in-noise performance, pointing to a possible interaction between peripheral and cognitive factors in chronic tinnitus. Further studies, that take into account both hearing and cognitive abilities of patients, are needed to better parse out the effect of tinnitus in the absence of hearing impairment.

Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition.

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Stevenson, Ryan A; Nelms, Caitlin E; Baum, Sarah H; Zurkovsky, Lilia; Barense, Morgan D; Newhouse, Paul A; Wallace, Mark T

2015-01-01

Over the next 2 decades, a dramatic shift in the demographics of society will take place, with a rapid growth in the population of older adults. One of the most common complaints with healthy aging is a decreased ability to successfully perceive speech, particularly in noisy environments. In such noisy environments, the presence of visual speech cues (i.e., lip movements) provide striking benefits for speech perception and comprehension, but previous research suggests that older adults gain less from such audiovisual integration than their younger peers. To determine at what processing level these behavioral differences arise in healthy-aging populations, we administered a speech-in-noise task to younger and older adults. We compared the perceptual benefits of having speech information available in both the auditory and visual modalities and examined both phoneme and whole-word recognition across varying levels of signal-to-noise ratio. For whole-word recognition, older adults relative to younger adults showed greater multisensory gains at intermediate SNRs but reduced benefit at low SNRs. By contrast, at the phoneme level both younger and older adults showed approximately equivalent increases in multisensory gain as signal-to-noise ratio decreased. Collectively, the results provide important insights into both the similarities and differences in how older and younger adults integrate auditory and visual speech cues in noisy environments and help explain some of the conflicting findings in previous studies of multisensory speech perception in healthy aging. These novel findings suggest that audiovisual processing is intact at more elementary levels of speech perception in healthy-aging populations and that deficits begin to emerge only at the more complex word-recognition level of speech signals. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of equally intelligible Telugu sentence-lists to test speech recognition in noise.

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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.

A comparison of 1D and 2D LSTM architectures for the recognition of handwritten Arabic

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Yousefi, Mohammad Reza; Soheili, Mohammad Reza; Breuel, Thomas M.; Stricker, Didier

2015-01-01

In this paper, we present an Arabic handwriting recognition method based on recurrent neural network. We use the Long Short Term Memory (LSTM) architecture, that have proven successful in different printed and handwritten OCR tasks. Applications of LSTM for handwriting recognition employ the two-dimensional architecture to deal with the variations in both vertical and horizontal axis. However, we show that using a simple pre-processing step that normalizes the position and baseline of letters, we can make use of 1D LSTM, which is faster in learning and convergence, and yet achieve superior performance. In a series of experiments on IFN/ENIT database for Arabic handwriting recognition, we demonstrate that our proposed pipeline can outperform 2D LSTM networks. Furthermore, we provide comparisons with 1D LSTM networks trained with manually crafted features to show that the automatically learned features in a globally trained 1D LSTM network with our normalization step can even outperform such systems.

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

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Oresti Banos

2014-06-01

Full Text Available Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements.

Odour recognition memory and odour identification in patients with mild and severe major depressive disorders.

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Zucco, Gesualdo M; Bollini, Fabiola

2011-12-30

Olfactory deficits, in detection, recognition and identification of odorants have been documented in ageing and in several neurodegenerative and psychiatric conditions. However, olfactory abilities in Major Depressive Disorder (MDD) have been less investigated, and available studies have provided inconsistent results. The present study assessed odour recognition memory and odour identification in two groups of 12 mild MDD patients (M age 41.3, range 25-57) and 12 severe MDD patients (M age, 41.9, range 23-58) diagnosed according to DSM-IV criteria and matched for age and gender to 12 healthy normal controls. The suitability of olfactory identification and recognition memory tasks as predictors of the progression of MDD was also addressed. Data analyses revealed that Severe MDD patients performed significantly worse than Mild MDD patients and Normal controls on both tasks, with these last groups not differing significantly from one another. The present outcomes are consistent with previous studies in other domains which have shown reliable, although not conclusive, impairments in cognitive function, including memory, in patients with MDD, and highlight the role of olfactory identification and recognition tasks as an important additional tool to discriminate between patients characterised by different levels of severity of MDD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of training on recognition of musical instruments presented through cochlear implant simulations.

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Driscoll, Virginia D; Oleson, Jacob; Jiang, Dingfeng; Gfeller, Kate

2009-01-01

The simulation of the CI (cochlear implant) signal presents a degraded representation of each musical instrument, which makes recognition difficult. To examine the efficiency and effectiveness of three types of training on recognition of musical instruments as presented through simulations of the sounds transmitted through a CI. Participants were randomly assigned to one of three training conditions: repeated exposure, feedback, and direct instruction. Sixty-six adults with normal hearing. Each participant completed three training sessions per week, over a five-week time period, in which they listened to the CI simulations of eight different musical instruments. Analyses on percent of instruments identified correctly showed statistically significant differences between recognition accuracy of the three training conditions (p different types of training are differentially effective with regard to improving recognition of musical instruments presented through a degraded signal, which has practical implications for the auditory rehabilitation of persons who use cochlear implants.

Iris Recognition Using Feature Extraction of Box Counting Fractal Dimension

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Khotimah, C.; Juniati, D.

2018-01-01

Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition consists of three step: pre-processing of data, feature extraction, and feature matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman’s rubber sheet model to normalize the iris data set into rectangular blocks. To find the characteristics of the iris, it was used box counting method to get the fractal dimension value of the iris. Tests carried out by used k-fold cross method with k = 5. In each test used 10 different grade K of K-Nearest Neighbor (KNN). The result of iris recognition was obtained with the best accuracy was 92,63 % for K = 3 value on K-Nearest Neighbor (KNN) method.

Optogenetic Stimulation of Prefrontal Glutamatergic Neurons Enhances Recognition Memory.

Science.gov (United States)

Benn, Abigail; Barker, Gareth R I; Stuart, Sarah A; Roloff, Eva V L; Teschemacher, Anja G; Warburton, E Clea; Robinson, Emma S J

2016-05-04

Finding effective cognitive enhancers is a major health challenge; however, modulating glutamatergic neurotransmission has the potential to enhance performance in recognition memory tasks. Previous studies using glutamate receptor antagonists have revealed that the medial prefrontal cortex (mPFC) plays a central role in associative recognition memory. The present study investigates short-term recognition memory using optogenetics to target glutamatergic neurons within the rodent mPFC specifically. Selective stimulation of glutamatergic neurons during the online maintenance of information enhanced associative recognition memory in normal animals. This cognitive enhancing effect was replicated by local infusions of the AMPAkine CX516, but not CX546, which differ in their effects on EPSPs. This suggests that enhancing the amplitude, but not the duration, of excitatory synaptic currents improves memory performance. Increasing glutamate release through infusions of the mGluR7 presynaptic receptor antagonist MMPIP had no effect on performance. These results provide new mechanistic information that could guide the targeting of future cognitive enhancers. Our work suggests that improved associative-recognition memory can be achieved by enhancing endogenous glutamatergic neuronal activity selectively using an optogenetic approach. We build on these observations to recapitulate this effect using drug treatments that enhance the amplitude of EPSPs; however, drugs that alter the duration of the EPSP or increase glutamate release lack efficacy. This suggests that both neural and temporal specificity are needed to achieve cognitive enhancement. Copyright © 2016 Benn et al.

How can professionals carry out recognition towards children of parents with alcohol problems? A qualitative interview study.

Science.gov (United States)

Werner, Anne; Malterud, Kirsti

2017-02-01

The aim of this study was to explore informal adult support experienced by children with parental alcohol problems to understand how professionals can show recognition in a similar way. We conducted a qualitative interview study with retrospective accounts from nine adults growing up with problem-drinking parents. Data were analysed with systematic text condensation. Goffman's concept "frame" offered a lens to study how supportive situations were defined and to understand opportunities and limitations for translation of recognition acts and attitudes to professional contexts. Analysis demonstrated frames of commonplace interaction where children experienced that adults recognised and responded to their needs. However, the silent support from an adult who recognised the problems without responding was an ambiguous frame. The child sometimes felt betrayed. Concentrating on frames of recognition which could be passed over to professional interactions, we noticed that participants called for a safe harbour, providing a sense of normality. Being with friends and their families, escaping difficulties at home without having to tell, was emphasised as important. Recognition was experienced when an adult with respect and dignity offered an open opportunity to address the problems, without pushing towards further communication. Our study indicates some specific lessons to be learnt about recognition for professional service providers from everyday situations. Frames of recognition, communicating availability and normality, and also unconditional confidentiality and safety when sharing problems may also be offered by professionals in public healthcare within their current frames of competency and time.

Speech Recognition

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Adrian Morariu

2009-01-01

Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

National survey data for zoonotic schistosomiasis in the Philippines grossly underestimates the true burden of disease within endemic zones: implications for future control

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Remigio M. Olveda

2016-04-01

Full Text Available Zoonotic schistosomiasis has a long endemic history in the Philippines. Human mass drug administration has been the cornerstone of schistosomiasis control in the country for the past three decades. Recent publications utilizing retrospective national survey data have indicated that the national human prevalence of the disease is <1%, hence the disease is now close to elimination. However, the evidence for such a claim is weak, given that less than a third of the human population is currently being treated annually within endemic zones and only a third of those treated actually swallow the tablets. For those who consume the drug at the single oral dose of 40 mg/kg, the estimated cure rate is 52% based on a recent meta-analysis. Thus, approximately 5% of the endemic human population is in reality receiving the appropriate treatment. To compound this public health problem, most of the bovines in the endemic communities are concurrently infected but are not treated under the current national control programme. Given this evidence, it is believed that the human prevalence of schistosomiasis within endemic regions has been grossly underestimated. Inherent flaws in the reporting of national schistosomiasis prevalence data are reported here, and the problems of utilizing national retrospective data in making geographic information system (GIS risk maps and advising policy makers of the outcomes are highlighted.

Recognition and Toleration

DEFF Research Database (Denmark)

Lægaard, Sune

2010-01-01

Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...

Speech recognition and parent-ratings from auditory development questionnaires in children who are hard of hearing

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McCreery, Ryan W.; Walker, Elizabeth A.; Spratford, Meredith; Oleson, Jacob; Bentler, Ruth; Holte, Lenore; Roush, Patricia

2015-01-01

Objectives Progress has been made in recent years in the provision of amplification and early intervention for children who are hard of hearing. However, children who use hearing aids (HA) may have inconsistent access to their auditory environment due to limitations in speech audibility through their HAs or limited HA use. The effects of variability in children’s auditory experience on parent-report auditory skills questionnaires and on speech recognition in quiet and in noise were examined for a large group of children who were followed as part of the Outcomes of Children with Hearing Loss study. Design Parent ratings on auditory development questionnaires and children’s speech recognition were assessed for 306 children who are hard of hearing. Children ranged in age from 12 months to 9 years of age. Three questionnaires involving parent ratings of auditory skill development and behavior were used, including the LittlEARS Auditory Questionnaire, Parents Evaluation of Oral/Aural Performance in Children Rating Scale, and an adaptation of the Speech, Spatial and Qualities of Hearing scale. Speech recognition in quiet was assessed using the Open and Closed set task, Early Speech Perception Test, Lexical Neighborhood Test, and Phonetically-balanced Kindergarten word lists. Speech recognition in noise was assessed using the Computer-Assisted Speech Perception Assessment. Children who are hard of hearing were compared to peers with normal hearing matched for age, maternal educational level and nonverbal intelligence. The effects of aided audibility, HA use and language ability on parent responses to auditory development questionnaires and on children’s speech recognition were also examined. Results Children who are hard of hearing had poorer performance than peers with normal hearing on parent ratings of auditory skills and had poorer speech recognition. Significant individual variability among children who are hard of hearing was observed. Children with greater

IMAGE PROCESSING BASED OPTICAL CHARACTER RECOGNITION USING MATLAB

OpenAIRE

Jyoti Dalal*1 & Sumiran Daiya2

2018-01-01

Character recognition techniques associate a symbolic identity with the image of character. In a typical OCR systems input characters are digitized by an optical scanner. Each character is then located and segmented, and the resulting character image is fed into a pre-processor for noise reduction and normalization. Certain characteristics are the extracted from the character for classification. The feature extraction is critical and many different techniques exist, each having its strengths ...

Object recognition with hierarchical discriminant saliency networks

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Sunhyoung eHan

2014-09-01

Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION

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Amol D. Rahulkar

2010-11-01

Full Text Available The feature extraction plays a very important role in iris recognition. Recent researches on multiscale analysis provide good opportunity to extract more accurate information for iris recognition. In this work, a new directional iris texture features based on 2-D Fast Discrete Curvelet Transform (FDCT is proposed. The proposed approach divides the normalized iris image into six sub-images and the curvelet transform is applied independently on each sub-image. The anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet coefficients. These six feature vectors are combined to create the resultant feature vector. During recognition, the nearest neighbor classifier based on Euclidean distance has been used for authentication. The effectiveness of the proposed approach has been tested on two different databases namely UBIRIS and MMU1. Experimental results show the superiority of the proposed approach.

Validating Models of Clinical Word Recognition Tests for Spanish/English Bilinguals

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Shi, Lu-Feng

2014-01-01

Purpose: Shi and Sánchez (2010) developed models to predict the optimal test language for evaluating Spanish/English (S/E) bilinguals' word recognition. The current study intended to validate their conclusions in a separate bilingual listener sample. Method: Seventy normal-hearing S/E bilinguals varying in language profile were included.…

Study on recognition algorithm for paper currency numbers based on neural network

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Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

2008-12-01

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

Fitting and verification of frequency modulation systems on children with normal hearing.

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Schafer, Erin C; Bryant, Danielle; Sanders, Katie; Baldus, Nicole; Algier, Katherine; Lewis, Audrey; Traber, Jordan; Layden, Paige; Amin, Aneeqa

2014-06-01

Several recent investigations support the use of frequency modulation (FM) systems in children with normal hearing and auditory processing or listening disorders such as those diagnosed with auditory processing disorders, autism spectrum disorders, attention-deficit hyperactivity disorder, Friedreich ataxia, and dyslexia. The American Academy of Audiology (AAA) published suggested procedures, but these guidelines do not cite research evidence to support the validity of the recommended procedures for fitting and verifying nonoccluding open-ear FM systems on children with normal hearing. Documenting the validity of these fitting procedures is critical to maximize the potential FM-system benefit in the above-mentioned populations of children with normal hearing and those with auditory-listening problems. The primary goal of this investigation was to determine the validity of the AAA real-ear approach to fitting FM systems on children with normal hearing. The secondary goal of this study was to examine speech-recognition performance in noise and loudness ratings without and with FM systems in children with normal hearing sensitivity. A two-group, cross-sectional design was used in the present study. Twenty-six typically functioning children, ages 5-12 yr, with normal hearing sensitivity participated in the study. Participants used a nonoccluding open-ear FM receiver during laboratory-based testing. Participants completed three laboratory tests: (1) real-ear measures, (2) speech recognition performance in noise, and (3) loudness ratings. Four real-ear measures were conducted to (1) verify that measured output met prescribed-gain targets across the 1000-4000 Hz frequency range for speech stimuli, (2) confirm that the FM-receiver volume did not exceed predicted uncomfortable loudness levels, and (3 and 4) measure changes to the real-ear unaided response when placing the FM receiver in the child's ear. After completion of the fitting, speech recognition in noise at a -5

How does susceptibility to proactive interference relate to speech recognition in aided and unaided conditions?

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Ellis, Rachel J; Rönnberg, Jerker

2015-01-01

Proactive interference (PI) is the capacity to resist interference to the acquisition of new memories from information stored in the long-term memory. Previous research has shown that PI correlates significantly with the speech-in-noise recognition scores of younger adults with normal hearing. In this study, we report the results of an experiment designed to investigate the extent to which tests of visual PI relate to the speech-in-noise recognition scores of older adults with hearing loss, in aided and unaided conditions. The results suggest that measures of PI correlate significantly with speech-in-noise recognition only in the unaided condition. Furthermore the relation between PI and speech-in-noise recognition differs to that observed in younger listeners without hearing loss. The findings suggest that the relation between PI tests and the speech-in-noise recognition scores of older adults with hearing loss relates to capability of the test to index cognitive flexibility.

How does susceptibility to proactive interference relate to speech recognition in aided and unaided conditions?

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Rachel Jane Ellis

2015-08-01

Full Text Available Proactive interference (PI is the capacity to resist interference to the acquisition of new memories from information stored in the long-term memory. Previous research has shown that PI correlates significantly with the speech-in-noise recognition scores of younger adults with normal hearing. In this study, we report the results of an experiment designed to investigate the extent to which tests of visual PI relate to the speech-in-noise recognition scores of older adults with hearing loss, in aided and unaided conditions. The results suggest that measures of PI correlate significantly with speech-in-noise recognition only in the unaided condition. Furthermore the relation between PI and speech-in-noise recognition differs to that observed in younger listeners without hearing loss. The findings suggest that the relation between PI tests and the speech-in-noise recognition scores of older adults with hearing loss relates to capability of the test to index cognitive flexibility.

Re-thinking employee recognition: understanding employee experiences of recognition

OpenAIRE

Smith, Charlotte

2013-01-01

Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

[Structure of maxillary sinus mucous membrane under normal conditions and in odontogenic perforative sinusitis].

Science.gov (United States)

Baĭdik, O D; Logvinov, S V; Zubarev, S G; Sysoliatin, P G; Gurin, A A

2011-01-01

Methods of light, electron microscopy and immunohistochemistry were used to study the samples of maxillary sinus (MS) mucous membrane (MM) under normal conditions and in odontogenic sinusitis. To study the normal structure, the samples were obtained at autopsy from 26 human corpses 12-24 hours after death. Electron microscopic and immunohistochemical study was performed on biopsies of grossly morphologically unchanged MS MM, obtained during the operations for retention cysts in 6 patients. MS MM in perforative sinusitis was studied using the biopsies obtained from 43 patients. The material is broken into 4 groups depending on perforative sinusitis duration. Under normal conditions, MS MM is lined with a pseudostratified columnar ciliated epithelium. Degenerative changes of ciliated epithelial cells were already detected at short time intervals after MS perforations and become apparent due to reduction of specific volume of mitochondria and, rough endoplasmic reticulum, and increase of nuclear-cytoplasmic ratio. In the globlet cells, the reduction of nuclear-cytoplasmic ratio was associated with the disturbance of the secretory product release. At time intervals exceeding 3 months, epithelium underwent metaplasia into simple cuboidal and stratified squamous keratinized, while in MS MM lamina propria, cellular infiltration was increased. CD4+ cell content in sinus MM gradually increased, while at late periods after perforation occurrence it decreased. Low CD4+ cell count within the epithelium and the absence of muromidase on the surface of MS MM was detected. With the increase of the time interval since MS perforation, the number of CD8+ and CD20+ cells in MS MM was found to increase.

Comparison of Oral Stereognosis in 6 and 7 Old Normal Children

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Amir Shiani

2004-06-01

Full Text Available Objective: This research determined oral stereognosis (form recognition and spent time to recognize in normal children in north and south of Tehran city to use it in assessment and therapy of oral senses and speech in children with articulation disorders. Materials & Methods: This research was done in 200 children who were 6 & 7 years old and normal in Tehran city. 20 items with different shapes were used and children were wanted to recognize the shapes which were put in their mouth and they should choice one of three shapes located in front of them. Responses and the spent time were calculated. Results: The mean scores of form recognition in children of 6 years old is 17/34 and in children of 7 years old is 17/59. There was no significant difference between them in their scores (P=0.31. In addition, the time of formation diagnosis in 6 years old children is 2/67s (seconds and in 7 years old children is 2/82s, there was no significant difference between them (P=0.11.The northern city children responded slower than the other group (P=0.000. The only statistically significant score between two sexes was the time of formation recognition which was shorter in girls relative to the boys (P=0.043. Conclusion: Based on this study, a significant correlation could not be found in ability of oral stereognosis in 6 and 7 years old children. But in south of city children can recognize faster than children in northern city. Based on importance of this sense in speech, we suggest normalization of it in different ages.

Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

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Jizheng Yi

Full Text Available Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1 we optimize the surround function; (2 we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

Science.gov (United States)

Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Rovetta, Alberto; Caleanu, Catalin-Daniel

2015-01-01

Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1) we optimize the surround function; (2) we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

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

Science.gov (United States)

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.

Vasopressin infusion into the lateral septum of adult male rats rescues progesterone induced impairment in social recognition

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Bychowski, Meaghan E.; Mena, Jesus D.; Auger, Catherine J.

2013-01-01

It is well established that social recognition memory is mediated, in part, by arginine vasopressin (AVP). AVP cells within the bed nucleus of the stria terminalis (BST) and medial amygdala (MeA) send AVP-ergic projections to the lateral septum (LS). We have demonstrated that progesterone treatment decreases AVP immunoreactivity within the BST, the MeA and the LS, and that progesterone treatment impairs social recognition. These data suggested that progesterone may impair social recognition memory by decreasing AVP. In the present experiment, we hypothesized that infusions of AVP into the LS would rescue the progesterone induced impairment in social recognition within adult male rats. One week after adult male rats underwent cannula surgery, they were given systemic injections of either a physiological dose of progesterone or oil control for three days. Four hours after the last injection, we tested social recognition memory using the social discrimination paradigm, a two-trial test that is based on the natural propensity for rats to be highly motivated to investigate novel conspecifics. Immediately after the first exposure to a juvenile, each animal received bilateral infusions of either AVP or artificial CSF (aCSF) into the LS. Our results show that, as expected, control animals exhibited normal social discrimination. In corroboration with our previous results, animals given progesterone have impaired social discrimination. Interestingly, animals treated with progesterone and AVP exhibited normal social discrimination, suggesting that AVP treatment rescued the impairment in social recognition caused by progesterone. These data also further support a role for progesterone in modulating vasopressin dependent behavior within the male brain. PMID:23639881

Face identity recognition in autism spectrum disorders: a review of behavioral studies.

Science.gov (United States)

Weigelt, Sarah; Koldewyn, Kami; Kanwisher, Nancy

2012-03-01

Face recognition--the ability to recognize a person from their facial appearance--is essential for normal social interaction. Face recognition deficits have been implicated in the most common disorder of social interaction: autism. Here we ask: is face identity recognition in fact impaired in people with autism? Reviewing behavioral studies we find no strong evidence for a qualitative difference in how facial identity is processed between those with and without autism: markers of typical face identity recognition, such as the face inversion effect, seem to be present in people with autism. However, quantitatively--i.e., how well facial identity is remembered or discriminated--people with autism perform worse than typical individuals. This impairment is particularly clear in face memory and in face perception tasks in which a delay intervenes between sample and test, and less so in tasks with no memory demand. Although some evidence suggests that this deficit may be specific to faces, further evidence on this question is necessary. Copyright © 2011 Elsevier Ltd. All rights reserved.

Graphical symbol recognition

OpenAIRE

K.C. , Santosh; Wendling , Laurent

2015-01-01

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

Illumination normalization based on simplified local binary patterns for a face verification system

NARCIS (Netherlands)

Tao, Q.; Veldhuis, Raymond N.J.

2007-01-01

Illumination normalization is a very important step in face recognition. In this paper we propose a simple implementation of Local Binary Patterns, which effectively reduces the variability caused by illumination changes. In combination with a likelihood ratio classifier, this illumination

Histogram equalization with Bayesian estimation for noise robust speech recognition.

Science.gov (United States)

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Research on Normal Human Plantar Pressure Test

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Liu Xi Yang

2016-01-01

Full Text Available FSR400 pressure sensor, nRF905 wireless transceiver and MSP40 SCM are used to design the insole pressure collection system, LabVIEW is used to make HMI of data acquisition, collecting a certain amount of normal human foot pressure data, statistical analysis of pressure distribution relations about five stages of swing phase during walking, using the grid closeness degree to identify plantar pressure distribution pattern recognition, and the algorithm simulation, experimental results demonstrated this method feasible.

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

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

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

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Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines

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Ayşegül Uçar

2014-01-01

Full Text Available This paper presents a novel color face recognition algorithm by means of fusing color and local information. The proposed algorithm fuses the multiple features derived from different color spaces. Multiorientation and multiscale information relating to the color face features are extracted by applying Steerable Pyramid Transform (SPT to the local face regions. In this paper, the new three hybrid color spaces, YSCr, ZnSCr, and BnSCr, are firstly constructed using the Cb and Cr component images of the YCbCr color space, the S color component of the HSV color spaces, and the Zn and Bn color components of the normalized XYZ color space. Secondly, the color component face images are partitioned into the local patches. Thirdly, SPT is applied to local face regions and some statistical features are extracted. Fourthly, all features are fused according to decision fusion frame and the combinations of Extreme Learning Machines classifiers are applied to achieve color face recognition with fast and high correctness. The experiments show that the proposed Local Color Steerable Pyramid Transform (LCSPT face recognition algorithm improves seriously face recognition performance by using the new color spaces compared to the conventional and some hybrid ones. Furthermore, it achieves faster recognition compared with state-of-the-art studies.

The role of spectral and temporal cues in voice gender discrimination by normal-hearing listeners and cochlear implant users.

Science.gov (United States)

Fu, Qian-Jie; Chinchilla, Sherol; Galvin, John J

2004-09-01

The present study investigated the relative importance of temporal and spectral cues in voice gender discrimination and vowel recognition by normal-hearing subjects listening to an acoustic simulation of cochlear implant speech processing and by cochlear implant users. In the simulation, the number of speech processing channels ranged from 4 to 32, thereby varying the spectral resolution; the cutoff frequencies of the channels' envelope filters ranged from 20 to 320 Hz, thereby manipulating the available temporal cues. For normal-hearing subjects, results showed that both voice gender discrimination and vowel recognition scores improved as the number of spectral channels was increased. When only 4 spectral channels were available, voice gender discrimination significantly improved as the envelope filter cutoff frequency was increased from 20 to 320 Hz. For all spectral conditions, increasing the amount of temporal information had no significant effect on vowel recognition. Both voice gender discrimination and vowel recognition scores were highly variable among implant users. The performance of cochlear implant listeners was similar to that of normal-hearing subjects listening to comparable speech processing (4-8 spectral channels). The results suggest that both spectral and temporal cues contribute to voice gender discrimination and that temporal cues are especially important for cochlear implant users to identify the voice gender when there is reduced spectral resolution.

Understanding Emotions from Standardized Facial Expressions in Autism and Normal Development

Science.gov (United States)

Castelli, Fulvia

2005-01-01

The study investigated the recognition of standardized facial expressions of emotion (anger, fear, disgust, happiness, sadness, surprise) at a perceptual level (experiment 1) and at a semantic level (experiments 2 and 3) in children with autism (N= 20) and normally developing children (N= 20). Results revealed that children with autism were as…

Common impairments of emotional facial expression recognition in schizophrenia across French and Japanese cultures

Directory of Open Access Journals (Sweden)

Takashi eOkada

2015-07-01

Full Text Available To address whether the recognition of emotional facial expressions is impaired in schizophrenia across different cultures, patients with schizophrenia and age-matched normal controls in France and Japan were tested with a labeling task of emotional facial expressions and a matching task of unfamiliar faces. Schizophrenia patients in both France and Japan were less accurate in labeling fearful facial expressions. There was no correlation between the scores of facial emotion labeling and face matching. These results suggest that the impaired recognition of emotional facial expressions in schizophrenia is common across different cultures.

Statistical Pattern Recognition

CERN Document Server

Webb, Andrew R

2011-01-01

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

ANFIS Based Methodology for Sign Language Recognition and Translating to Number in Kannada Language

Directory of Open Access Journals (Sweden)

Ramesh Mahadev kagalkar

2017-03-01

Full Text Available In the world of signing and gestures, lots of analysis work has been done over the past three decades. This has led to a gradual transition from isolated to continuous, and static to dynamic gesture recognition for operations on a restricted vocabulary. In gift state of affairs, human machine interactive systems facilitate communication between the deaf, and hearing impaired in universe things. So as to boost the accuracy of recognition, several researchers have deployed strategies like HMM, Artificial Neural Networks, and Kinect platform. Effective algorithms for segmentation, classification, pattern matching and recognition have evolved. The most purpose of this paper is to investigate these strategies and to effectively compare them, which can alter the reader to succeed in associate in nursing optimum resolution. This creates each, challenges and opportunities for signing recognition connected analysis. Normal 0 false false false DE JA X-NONE

Reducing Error Rates for Iris Image using higher Contrast in Normalization process

Science.gov (United States)

Aminu Ghali, Abdulrahman; Jamel, Sapiee; Abubakar Pindar, Zahraddeen; Hasssan Disina, Abdulkadir; Mat Daris, Mustafa

2017-08-01

Iris recognition system is the most secured, and faster means of identification and authentication. However, iris recognition system suffers a setback from blurring, low contrast and illumination due to low quality image which compromises the accuracy of the system. The acceptance or rejection rates of verified user depend solely on the quality of the image. In many cases, iris recognition system with low image contrast could falsely accept or reject user. Therefore this paper adopts Histogram Equalization Technique to address the problem of False Rejection Rate (FRR) and False Acceptance Rate (FAR) by enhancing the contrast of the iris image. A histogram equalization technique enhances the image quality and neutralizes the low contrast of the image at normalization stage. The experimental result shows that Histogram Equalization Technique has reduced FRR and FAR compared to the existing techniques.

Application of Video Recognition Technology in Landslide Monitoring System

Directory of Open Access Journals (Sweden)

Qingjia Meng

2018-01-01

Full Text Available The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.

Reading component skills in dyslexia: word recognition, comprehension and processing speed.

Science.gov (United States)

de Oliveira, Darlene G; da Silva, Patrícia B; Dias, Natália M; Seabra, Alessandra G; Macedo, Elizeu C

2014-01-01

The cognitive model of reading comprehension (RC) posits that RC is a result of the interaction between decoding and linguistic comprehension. Recently, the notion of decoding skill was expanded to include word recognition. In addition, some studies suggest that other skills could be integrated into this model, like processing speed, and have consistently indicated that this skill influences and is an important predictor of the main components of the model, such as vocabulary for comprehension and phonological awareness of word recognition. The following study evaluated the components of the RC model and predictive skills in children and adolescents with dyslexia. 40 children and adolescents (8-13 years) were divided in a Dyslexic Group (DG; 18 children, MA = 10.78, SD = 1.66) and control group (CG 22 children, MA = 10.59, SD = 1.86). All were students from the 2nd to 8th grade of elementary school and groups were equivalent in school grade, age, gender, and IQ. Oral and RC, word recognition, processing speed, picture naming, receptive vocabulary, and phonological awareness were assessed. There were no group differences regarding the accuracy in oral and RC, phonological awareness, naming, and vocabulary scores. DG performed worse than the CG in word recognition (general score and orthographic confusion items) and were slower in naming. Results corroborated the literature regarding word recognition and processing speed deficits in dyslexia. However, dyslexics can achieve normal scores on RC test. Data supports the importance of delimitation of different reading strategies embedded in the word recognition component. The role of processing speed in reading problems remain unclear.

Improving speech-in-noise recognition for children with hearing loss: potential effects of language abilities, binaural summation, and head shadow.

Science.gov (United States)

Nittrouer, Susan; Caldwell-Tarr, Amanda; Tarr, Eric; Lowenstein, Joanna H; Rice, Caitlin; Moberly, Aaron C

2013-08-01

This study examined speech recognition in noise for children with hearing loss, compared it to recognition for children with normal hearing, and examined mechanisms that might explain variance in children's abilities to recognize speech in noise. Word recognition was measured in two levels of noise, both when the speech and noise were co-located in front and when the noise came separately from one side. Four mechanisms were examined as factors possibly explaining variance: vocabulary knowledge, sensitivity to phonological structure, binaural summation, and head shadow. Participants were 113 eight-year-old children. Forty-eight had normal hearing (NH) and 65 had hearing loss: 18 with hearing aids (HAs), 19 with one cochlear implant (CI), and 28 with two CIs. Phonological sensitivity explained a significant amount of between-groups variance in speech-in-noise recognition. Little evidence of binaural summation was found. Head shadow was similar in magnitude for children with NH and with CIs, regardless of whether they wore one or two CIs. Children with HAs showed reduced head shadow effects. These outcomes suggest that in order to improve speech-in-noise recognition for children with hearing loss, intervention needs to be comprehensive, focusing on both language abilities and auditory mechanisms.

Low empathy in deaf and hard of hearing (preadolescents compared to normal hearing controls.

Directory of Open Access Journals (Sweden)

Anouk P Netten

Full Text Available The purpose of this study was to examine the level of empathy in deaf and hard of hearing (preadolescents compared to normal hearing controls and to define the influence of language and various hearing loss characteristics on the development of empathy.The study group (mean age 11.9 years consisted of 122 deaf and hard of hearing children (52 children with cochlear implants and 70 children with conventional hearing aids and 162 normal hearing children. The two groups were compared using self-reports, a parent-report and observation tasks to rate the children's level of empathy, their attendance to others' emotions, emotion recognition, and supportive behavior.Deaf and hard of hearing children reported lower levels of cognitive empathy and prosocial motivation than normal hearing children, regardless of their type of hearing device. The level of emotion recognition was equal in both groups. During observations, deaf and hard of hearing children showed more attention to the emotion evoking events but less supportive behavior compared to their normal hearing peers. Deaf and hard of hearing children attending mainstream education or using oral language show higher levels of cognitive empathy and prosocial motivation than deaf and hard of hearing children who use sign (supported language or attend special education. However, they are still outperformed by normal hearing children.Deaf and hard of hearing children, especially those in special education, show lower levels of empathy than normal hearing children, which can have consequences for initiating and maintaining relationships.

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

Science.gov (United States)

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

1992-01-01

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

Joint variable frame rate and length analysis for speech recognition under adverse conditions

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Kraljevski, Ivan

2014-01-01

This paper presents a method that combines variable frame length and rate analysis for speech recognition in noisy environments, together with an investigation of the effect of different frame lengths on speech recognition performance. The method adopts frame selection using an a posteriori signal......-to-noise (SNR) ratio weighted energy distance and increases the length of the selected frames, according to the number of non-selected preceding frames. It assigns a higher frame rate and a normal frame length to a rapidly changing and high SNR region of a speech signal, and a lower frame rate and an increased...... frame length to a steady or low SNR region. The speech recognition results show that the proposed variable frame rate and length method outperforms fixed frame rate and length analysis, as well as standalone variable frame rate analysis in terms of noise-robustness....

Vasopressin infusion into the lateral septum of adult male rats rescues progesterone-induced impairment in social recognition.

Science.gov (United States)

Bychowski, M E; Mena, J D; Auger, C J

2013-08-29

It is well established that social recognition memory is mediated, in part, by arginine vasopressin (AVP). AVP cells within the bed nucleus of the stria terminalis (BST) and medial amygdala (MeA) send AVP-ergic projections to the lateral septum (LS). We have demonstrated that progesterone treatment decreases AVP immunoreactivity within the BST, the MeA and the LS, and that progesterone treatment impairs social recognition. These data suggested that progesterone may impair social recognition memory by decreasing AVP. In the present experiment, we hypothesized that infusions of AVP into the LS would rescue the progesterone-induced impairment in social recognition within adult male rats. One week after adult male rats underwent cannula surgery, they were given systemic injections of either a physiological dose of progesterone or oil control for 3 days. Four hours after the last injection, we tested social recognition memory using the social discrimination paradigm, a two-trial test that is based on the natural propensity for rats to be highly motivated to investigate novel conspecifics. Immediately after the first exposure to a juvenile, each animal received bilateral infusions of either AVP or artificial cerebrospinal fluid into the LS. Our results show that, as expected, control animals exhibited normal social discrimination. In corroboration with our previous results, animals given progesterone have impaired social discrimination. Interestingly, animals treated with progesterone and AVP exhibited normal social discrimination, suggesting that AVP treatment rescued the impairment in social recognition caused by progesterone. These data also further support a role for progesterone in modulating vasopressin-dependent behavior within the male brain. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

2017-01-01

of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

Speech emotion recognition based on statistical pitch model

Institute of Scientific and Technical Information of China (English)

WANG Zhiping; ZHAO Li; ZOU Cairong

2006-01-01

A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.

An Epidemiologic Investigation of Health Effects in Air Force Personnel Following Exposure to Herbicides. Volume 2. First Followup Examination Results.

Science.gov (United States)

1987-10-01

ABNORMAL___________________________________ -ESSENTIAL NORM. SKILLED ACTS - - ESSENTIAL AB -g-NTENTION NORM SPEECH ARTICULATION. APHASIA. AGNOSIA ) miN~rNTCGN AB...DYSARTHRIA *OTHER NORMAL GROSSLY APHASIA -~ miABNORMAL AGNOSIA NCS Trons.Optic EPOI-21159 321 A8900 W* -ABNORMAL - NORMAL LE F7 RIGHT BOTH- STRAIGH-T

Facial Expression Recognition: Can Preschoolers with Cochlear Implants and Hearing Aids Catch It?

Science.gov (United States)

Wang, Yifang; Su, Yanjie; Fang, Ping; Zhou, Qingxia

2011-01-01

Tager-Flusberg and Sullivan (2000) presented a cognitive model of theory of mind (ToM), in which they thought ToM included two components--a social-perceptual component and a social-cognitive component. Facial expression recognition (FER) is an ability tapping the social-perceptual component. Previous findings suggested that normal hearing…

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

Science.gov (United States)

Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

2002-01-01

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can

Common constraints limit Korean and English character recognition in peripheral vision.

Science.gov (United States)

He, Yingchen; Kwon, MiYoung; Legge, Gordon E

2018-01-01

The visual span refers to the number of adjacent characters that can be recognized in a single glance. It is viewed as a sensory bottleneck in reading for both normal and clinical populations. In peripheral vision, the visual span for English characters can be enlarged after training with a letter-recognition task. Here, we examined the transfer of training from Korean to English characters for a group of bilingual Korean native speakers. In the pre- and posttests, we measured visual spans for Korean characters and English letters. Training (1.5 hours × 4 days) consisted of repetitive visual-span measurements for Korean trigrams (strings of three characters). Our training enlarged the visual spans for Korean single characters and trigrams, and the benefit transferred to untrained English symbols. The improvement was largely due to a reduction of within-character and between-character crowding in Korean recognition, as well as between-letter crowding in English recognition. We also found a negative correlation between the size of the visual span and the average pattern complexity of the symbol set. Together, our results showed that the visual span is limited by common sensory (crowding) and physical (pattern complexity) factors regardless of the language script, providing evidence that the visual span reflects a universal bottleneck for text recognition.

Emotion Recognition in Frontotemporal Dementia and Alzheimer's Disease: A New Film-Based Assessment

Science.gov (United States)

Goodkind, Madeleine S.; Sturm, Virginia E.; Ascher, Elizabeth A.; Shdo, Suzanne M.; Miller, Bruce L.; Rankin, Katherine P.; Levenson, Robert W.

2015-01-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. PMID:26010574

Emotion recognition in frontotemporal dementia and Alzheimer's disease: A new film-based assessment.

Science.gov (United States)

Goodkind, Madeleine S; Sturm, Virginia E; Ascher, Elizabeth A; Shdo, Suzanne M; Miller, Bruce L; Rankin, Katherine P; Levenson, Robert W

2015-08-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. (c) 2015 APA, all rights reserved).

Effects of lexical characteristics and demographic factors on mandarin chinese open-set word recognition in children with cochlear implants.

Science.gov (United States)

Liu, Haihong; Liu, Sha; Wang, Suju; Liu, Chang; Kong, Ying; Zhang, Ning; Li, Shujing; Yang, Yilin; Han, Demin; Zhang, Luo

2013-01-01

The purpose of this study was to examine the open-set word recognition performance of Mandarin Chinese-speaking children who had received a multichannel cochlear implant (CI) and examine the effects of lexical characteristics and demographic factors (i.e., age at implantation and duration of implant use) on Mandarin Chinese open-set word recognition in these children. Participants were 230 prelingually deafened children with CIs. Age at implantation ranged from 0.9 to 16.0 years, with a mean of 3.9 years. The Standard-Chinese version of the Monosyllabic Lexical Neighborhood test and the Multisyllabic Lexical Neighborhood test were used to evaluate the open-set word identification abilities of the children. A two-way analysis of variance was performed to delineate the lexical effects on the open-set word identification, with word difficulty and syllable length as the two main factors. The effects of age at implantation and duration of implant use on open-set, word-recognition performance were examined using correlational/regressional models. First, the average percent-correct scores for the disyllabic "easy" list, disyllabic "hard" list, monosyllabic "easy" list, and monosyllabic "hard" list were 65.0%, 51.3%, 58.9%, and 46.2%, respectively. For both the easy and hard lists, the percentage of words correctly identified was higher for disyllabic words than for monosyllabic words, Second, the CI group scored 26.3%, 31.3%, and 18.8 % points lower than their hearing-age-matched normal-hearing peers for 4, 5, and 6 years of hearing age, respectively. The corresponding gaps between the CI group and the chronological-age-matched normal-hearing group were 47.6, 49.6, and 42.4, respectively. The individual variations in performance were much greater in the CI group than in the normal-hearing group, Third, the children exhibited steady improvements in performance as the duration of implant use increased, especially 1 to 6 years postimplantation. Last, age at implantation had

Antibody-Unfolding and Metastable-State Binding in Force Spectroscopy and Recognition Imaging

Science.gov (United States)

Kaur, Parminder; Qiang-Fu; Fuhrmann, Alexander; Ros, Robert; Kutner, Linda Obenauer; Schneeweis, Lumelle A.; Navoa, Ryman; Steger, Kirby; Xie, Lei; Yonan, Christopher; Abraham, Ralph; Grace, Michael J.; Lindsay, Stuart

2011-01-01

Force spectroscopy and recognition imaging are important techniques for characterizing and mapping molecular interactions. In both cases, an antibody is pulled away from its target in times that are much less than the normal residence time of the antibody on its target. The distribution of pulling lengths in force spectroscopy shows the development of additional peaks at high loading rates, indicating that part of the antibody frequently unfolds. This propensity to unfold is reversible, indicating that exposure to high loading rates induces a structural transition to a metastable state. Weakened interactions of the antibody in this metastable state could account for reduced specificity in recognition imaging where the loading rates are always high. The much weaker interaction between the partially unfolded antibody and target, while still specific (as shown by control experiments), results in unbinding on millisecond timescales, giving rise to rapid switching noise in the recognition images. At the lower loading rates used in force spectroscopy, we still find discrepancies between the binding kinetics determined by force spectroscopy and those determined by surface plasmon resonance—possibly a consequence of the short tethers used in recognition imaging. Recognition imaging is nonetheless a powerful tool for interpreting complex atomic force microscopy images, so long as specificity is calibrated in situ, and not inferred from equilibrium binding kinetics. PMID:21190677

Hilar height ratio in normal Korea

International Nuclear Information System (INIS)

Yoo, Kyung Ho; Lee, Nam Joon; Seol, Hae Young; Chung, Kyoo Byung

1979-01-01

Hilar displacement is one of the significant sign of pulmonary volume change. The hilar height ratio (HHR) is a value that express the normal position of hilum in its hemithorax, and it is calculated by dividing the distance from the hilum to the lung apex by the distance from the hilum to the diaphragm. Displacement of one hilum is usually easy to detect but both are displaced in the same direction especially, recognition is more difficult. Knowledge of normal HHR allows evaluation of hilar positional change even when the relative hilar position are not altered. Normal chest PA views of 275 cases taken at Korea University Hospital during the period of April 1978 to Jun 1979 were analyzed. The right hilum is positioned in lower half of the right hemithorax, while the left hilum is situated in the upper half of left hemithorax. The difference of hilar ratio according to age group is slight, but there is significant difference between right-HHR and left-HHR. The value of right-HHR is 1.28 ± 0.14, the value of left-HHR is 0.88 ± 0.09.

Binaural pitch perception in normal-hearing and hearing-impaired listeners

DEFF Research Database (Denmark)

Santurette, Sébastien; Dau, Torsten

2007-01-01

The effects of hearing impairment on the perception of binaural-pitch stimuli were investigated. Several experiments were performed with normal-hearing and hearing-impaired listeners, including detection and discrimination of binaural pitch, and melody recognition using different types of binaural...... pitches. For the normal-hearing listeners, all types of binaural pitches could be perceived immediately and were musical. The hearing-impaired listeners could be divided into three groups based on their results: (a) some perceived all types of binaural pitches, but with decreased salience or musicality...... compared to normal-hearing listeners; (b) some could only perceive the strongest pitch types; (c) some were unable to perceive any binaural pitch at all. The performance of the listeners was not correlated with audibility. Additional experiments investigated the correlation between performance in binaural...

Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

Science.gov (United States)

Barsics, Catherine; Brédart, Serge

2010-11-01

Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

Reading component skills in dyslexia: word recognition, comprehension and processing speed

Directory of Open Access Journals (Sweden)

Darlene Godoy Oliveira

2014-11-01

Full Text Available The cognitive model of reading comprehension posits that reading comprehension is a result of the interaction between decoding and linguistic comprehension. Recently, the notion of decoding skill was expanded to include word recognition. In addition, some studies suggest that other skills could be integrated into this model, like processing speed, and have consistently indicated that this skill influences and is an important predictor of the main components of the model, such as vocabulary for comprehension and phonological awareness of word recognition. The following study evaluated the components of the reading comprehension model and predictive skills in children and adolescents with dyslexia. 40 children and adolescents (8-13 years were divided in a Dyslexic Group (DG, 18 children, MA = 10.78, SD = 1.66 and Control Group (CG 22 children, MA = 10.59, SD = 1.86. All were students from the 2nd to 8th grade of elementary school and groups were equivalent in school grade, age, gender, and IQ. Oral and reading comprehension, word recognition, processing speed, picture naming, receptive vocabulary and phonological awareness were assessed. There were no group differences regarding the accuracy in oral and reading comprehension, phonological awareness, naming, and vocabulary scores. DG performed worse than the CG in word recognition (general score and orthographic confusion items and were slower in naming. Results corroborated the literature regarding word recognition and processing speed deficits in dyslexia. However, dyslexics can achieve normal scores on reading comprehension test. Data supports the importance of delimitation of different reading strategies embedded in the word recognition component. The role of processing speed in reading problems remain unclear.

Acute cortisol effects on immediate free recall and recognition of nouns depend on stimulus valence

NARCIS (Netherlands)

Tops, M.; van der Pompe, G.; Baas, D; Mulder, L.J.M.; Den Boer, J.A.; Meijman, T.F.; Korf, J

The present study investigated the acute effects of cortisol administration in normal healthy male volunteers on immediate free recall and recognition of pleasant, unpleasant, and neutral nouns using a between-subjects double-blind design. Two hours after cortisol (10 mg) or placebo administration,

Low empathy in deaf and hard of hearing (pre)adolescents compared to normal hearing controls.

Science.gov (United States)

Netten, Anouk P; Rieffe, Carolien; Theunissen, Stephanie C P M; Soede, Wim; Dirks, Evelien; Briaire, Jeroen J; Frijns, Johan H M

2015-01-01

The purpose of this study was to examine the level of empathy in deaf and hard of hearing (pre)adolescents compared to normal hearing controls and to define the influence of language and various hearing loss characteristics on the development of empathy. The study group (mean age 11.9 years) consisted of 122 deaf and hard of hearing children (52 children with cochlear implants and 70 children with conventional hearing aids) and 162 normal hearing children. The two groups were compared using self-reports, a parent-report and observation tasks to rate the children's level of empathy, their attendance to others' emotions, emotion recognition, and supportive behavior. Deaf and hard of hearing children reported lower levels of cognitive empathy and prosocial motivation than normal hearing children, regardless of their type of hearing device. The level of emotion recognition was equal in both groups. During observations, deaf and hard of hearing children showed more attention to the emotion evoking events but less supportive behavior compared to their normal hearing peers. Deaf and hard of hearing children attending mainstream education or using oral language show higher levels of cognitive empathy and prosocial motivation than deaf and hard of hearing children who use sign (supported) language or attend special education. However, they are still outperformed by normal hearing children. Deaf and hard of hearing children, especially those in special education, show lower levels of empathy than normal hearing children, which can have consequences for initiating and maintaining relationships.

Recognition of sign language with an inertial sensor-based data glove.

Science.gov (United States)

Kim, Kyung-Won; Lee, Mi-So; Soon, Bo-Ram; Ryu, Mun-Ho; Kim, Je-Nam

2015-01-01

Communication between people with normal hearing and hearing impairment is difficult. Recently, a variety of studies on sign language recognition have presented benefits from the development of information technology. This study presents a sign language recognition system using a data glove composed of 3-axis accelerometers, magnetometers, and gyroscopes. Each data obtained by the data glove is transmitted to a host application (implemented in a Window program on a PC). Next, the data is converted into angle data, and the angle information is displayed on the host application and verified by outputting three-dimensional models to the display. An experiment was performed with five subjects, three females and two males, and a performance set comprising numbers from one to nine was repeated five times. The system achieves a 99.26% movement detection rate, and approximately 98% recognition rate for each finger's state. The proposed system is expected to be a more portable and useful system when this algorithm is applied to smartphone applications for use in some situations such as in emergencies.

[Prosopagnosia and facial expression recognition].

Science.gov (United States)

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.

Erasmus MC at CLEF eHealth 2016: Concept recognition and coding in French texts

NARCIS (Netherlands)

E.M. Van Mulligen (Erik M.); Z. Afzal (Zubair); S.A. Akhondi (Saber); D. Vo (Dang); J.A. Kors (Jan)

2016-01-01

textabstractWe participated in task 2 of the CLEF eHealth 2016 chal-lenge. Two subtasks were addressed: entity recognition and normalization in a corpus of French drug labels and Medline titles, and ICD-10 coding of French death certificates. For both subtasks we used a dictionary-based approach.

Abnormal Facial Emotion Recognition in Depression: Serial Testing in an Ultra-Rapid-Cycling Patient.

Science.gov (United States)

George, Mark S.; Huggins, Teresa; McDermut, Wilson; Parekh, Priti I.; Rubinow, David; Post, Robert M.

1998-01-01

Mood disorder subjects have a selective deficit in recognizing human facial emotion. Whether the facial emotion recognition errors persist during normal mood states (i.e., are state vs. trait dependent) was studied in one male bipolar II patient. Results of five sessions are presented and discussed. (Author/EMK)

Eye-movement strategies in developmental prosopagnosia and "super" face recognition.

Science.gov (United States)

Bobak, Anna K; Parris, Benjamin A; Gregory, Nicola J; Bennetts, Rachel J; Bate, Sarah

2017-02-01

Developmental prosopagnosia (DP) is a cognitive condition characterized by a severe deficit in face recognition. Few investigations have examined whether impairments at the early stages of processing may underpin the condition, and it is also unknown whether DP is simply the "bottom end" of the typical face-processing spectrum. To address these issues, we monitored the eye-movements of DPs, typical perceivers, and "super recognizers" (SRs) while they viewed a set of static images displaying people engaged in naturalistic social scenarios. Three key findings emerged: (a) Individuals with more severe prosopagnosia spent less time examining the internal facial region, (b) as observed in acquired prosopagnosia, some DPs spent less time examining the eyes and more time examining the mouth than controls, and (c) SRs spent more time examining the nose-a measure that also correlated with face recognition ability in controls. These findings support previous suggestions that DP is a heterogeneous condition, but suggest that at least the most severe cases represent a group of individuals that qualitatively differ from the typical population. While SRs seem to merely be those at the "top end" of normal, this work identifies the nose as a critical region for successful face recognition.

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

Science.gov (United States)

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.

Kernel learning algorithms for face recognition

CERN Document Server

Li, Jun-Bao; Pan, Jeng-Shyang

2013-01-01

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

Body schema and corporeal self-recognition in the alien hand syndrome.

Science.gov (United States)

Olgiati, Elena; Maravita, Angelo; Spandri, Viviana; Casati, Roberta; Ferraro, Francesco; Tedesco, Lucia; Agostoni, Elio Clemente; Bolognini, Nadia

2017-07-01

The alien hand syndrome (AHS) is a rare neuropsychological disorder characterized by involuntary, yet purposeful, hand movements. Patients with the AHS typically complain about a loss of agency associated with a feeling of estrangement for actions performed by the affected limb. The present study explores the integrity of the body representation in AHS, focusing on 2 main processes: multisensory integration and visual self-recognition of body parts. Three patients affected by AHS following a right-hemisphere stroke, with clinical symptoms akin to the posterior variant of AHS, were tested and their performance was compared with that of 18 age-matched healthy controls. AHS patients and controls underwent 2 experimental tasks: a same-different visual matching task for body postures, which assessed the ability of using your own body schema for encoding others' body postural changes (Experiment 1), and an explicit self-hand recognition task, which assessed the ability to visually recognize your own hands (Experiment 2). As compared to controls, all AHS patients were unable to access a reliable multisensory representation of their alien hand and use it for decoding others' postural changes; however, they could rely on an efficient multisensory representation of their intact (ipsilesional) hand. Two AHS patients also presented with a specific impairment in the visual self-recognition of their alien hand, but normal recognition of their intact hand. This evidence suggests that the AHS following a right-hemisphere stroke may involve a disruption of the multisensory representation of the alien limb; instead, self-hand recognition mechanisms may be spared. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Chloroplastic protein NRIP1 mediates innate immune receptor recognition of a viral effector

Science.gov (United States)

Caplan, Jeffrey L.; Mamillapalli, Padmavathi; Burch-Smith, Tessa M.; Czymmek, Kirk; Dinesh-Kumar, S.P.

2008-01-01

Summary Plant innate immunity relies on the recognition of pathogen effector molecules by nucleotide-binding-leucine-rich repeat (NB-LRR) immune receptor families. Previously we have shown the N immune receptor, a member of TIR-NB-LRR family, indirectly recognizes the 50-kDa helicase (p50) domain of Tobacco mosaic virus (TMV) through its TIR domain. We have identified an N receptor-interacting protein, NRIP1, that directly interacts with both N's TIR domain and p50. NRIP1 is a functional rhodanese sulfurtransferase and is required for N to provide complete resistance to TMV. Interestingly, NRIP1 that normally localizes to the chloroplasts is recruited to the cytoplasm and nucleus by the p50 effector. As a consequence, NRIP1 interacts with N only in the presence of the p50 effector. Our findings show that a chloroplastic protein is intimately involved in pathogen recognition. We propose that N's activation requires a pre-recognition complex containing the p50 effector and NRIP1. PMID:18267075

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

Science.gov (United States)

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

2017-11-26

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

The "parts and wholes" of face recognition: A review of the literature.

Science.gov (United States)

Tanaka, James W; Simonyi, Diana

2016-10-01

It has been claimed that faces are recognized as a "whole" rather than by the recognition of individual parts. In a paper published in the Quarterly Journal of Experimental Psychology in 1993, Martha Farah and I attempted to operationalize the holistic claim using the part/whole task. In this task, participants studied a face and then their memory presented in isolation and in the whole face. Consistent with the holistic view, recognition of the part was superior when tested in the whole-face condition compared to when it was tested in isolation. The "whole face" or holistic advantage was not found for faces that were inverted, or scrambled, nor for non-face objects, suggesting that holistic encoding was specific to normal, intact faces. In this paper, we reflect on the part/whole paradigm and how it has contributed to our understanding of what it means to recognize a face as a "whole" stimulus. We describe the value of part/whole task for developing theories of holistic and non-holistic recognition of faces and objects. We discuss the research that has probed the neural substrates of holistic processing in healthy adults and people with prosopagnosia and autism. Finally, we examine how experience shapes holistic face recognition in children and recognition of own- and other-race faces in adults. The goal of this article is to summarize the research on the part/whole task and speculate on how it has informed our understanding of holistic face processing.

Sudden Event Recognition: A Survey

Directory of Open Access Journals (Sweden)

Mohd Asyraf Zulkifley

2013-08-01

Full Text Available 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.

Recognition versus Resolution: a Comparison of Visual Acuity Results Using Two Alternative Test Chart Optotype

OpenAIRE

Jonathan S. Pointer

2008-01-01

Purpose: To quantify the difference between recognition (letter) and resolution (Landolt) visual acuity (VA) in a group of normally sighted subjects. Is it reasonable to assume that the two acuity measures are clinically equivalent? Methods: A pair of 6 m acuity test charts was produced: one comprised letters and the other Landolt broken rings. Construction of both charts conformed to the logMAR design format. Monocular VA was determined for the dominant eye of 300 screened and normally si...

Low Empathy in Deaf and Hard of Hearing (Pre)Adolescents Compared to Normal Hearing Controls

Science.gov (United States)

Netten, Anouk P.; Rieffe, Carolien; Theunissen, Stephanie C. P. M.; Soede, Wim; Dirks, Evelien; Briaire, Jeroen J.; Frijns, Johan H. M.

2015-01-01

Objective The purpose of this study was to examine the level of empathy in deaf and hard of hearing (pre)adolescents compared to normal hearing controls and to define the influence of language and various hearing loss characteristics on the development of empathy. Methods The study group (mean age 11.9 years) consisted of 122 deaf and hard of hearing children (52 children with cochlear implants and 70 children with conventional hearing aids) and 162 normal hearing children. The two groups were compared using self-reports, a parent-report and observation tasks to rate the children’s level of empathy, their attendance to others’ emotions, emotion recognition, and supportive behavior. Results Deaf and hard of hearing children reported lower levels of cognitive empathy and prosocial motivation than normal hearing children, regardless of their type of hearing device. The level of emotion recognition was equal in both groups. During observations, deaf and hard of hearing children showed more attention to the emotion evoking events but less supportive behavior compared to their normal hearing peers. Deaf and hard of hearing children attending mainstream education or using oral language show higher levels of cognitive empathy and prosocial motivation than deaf and hard of hearing children who use sign (supported) language or attend special education. However, they are still outperformed by normal hearing children. Conclusions Deaf and hard of hearing children, especially those in special education, show lower levels of empathy than normal hearing children, which can have consequences for initiating and maintaining relationships. PMID:25906365

3D Interest Point Detection using Local Surface Characteristics with Application in Action Recognition

DEFF Research Database (Denmark)

Holte, Michael Boelstoft

2014-01-01

. The proposed Difference-of-Normals (DoN) 3D IP detector operates on the surface mesh, and evaluates the surface structure (curvature) locally (per vertex) in the mesh data. We present an exam- ple of application in action recognition from a sequence of 3-dimensional geometrical data, where local 3D motion de...

Improving Shadow Suppression for Illumination Robust Face Recognition

KAUST Repository

Zhang, Wuming

2017-10-13

2D face analysis techniques, such as face landmarking, face recognition and face verification, are reasonably dependent on illumination conditions which are usually uncontrolled and unpredictable in the real world. An illumination robust preprocessing method thus remains a significant challenge in reliable face analysis. In this paper we propose a novel approach for improving lighting normalization through building the underlying reflectance model which characterizes interactions between skin surface, lighting source and camera sensor, and elaborates the formation of face color appearance. Specifically, the proposed illumination processing pipeline enables the generation of Chromaticity Intrinsic Image (CII) in a log chromaticity space which is robust to illumination variations. Moreover, as an advantage over most prevailing methods, a photo-realistic color face image is subsequently reconstructed which eliminates a wide variety of shadows whilst retaining the color information and identity details. Experimental results under different scenarios and using various face databases show the effectiveness of the proposed approach to deal with lighting variations, including both soft and hard shadows, in face recognition.

Stimulation over primary motor cortex during action observation impairs effector recognition.

Science.gov (United States)

Naish, Katherine R; Barnes, Brittany; Obhi, Sukhvinder S

2016-04-01

Recent work suggests that motor cortical processing during action observation plays a role in later recognition of the object involved in the action. Here, we investigated whether recognition of the effector making an action is also impaired when transcranial magnetic stimulation (TMS) - thought to interfere with normal cortical activity - is applied over the primary motor cortex (M1) during action observation. In two experiments, single-pulse TMS was delivered over the hand area of M1 while participants watched short clips of hand actions. Participants were then asked whether an image (experiment 1) or a video (experiment 2) of a hand presented later in the trial was the same or different to the hand in the preceding video. In Experiment 1, we found that participants' ability to recognise static images of hands was significantly impaired when TMS was delivered over M1 during action observation, compared to when no TMS was delivered, or when stimulation was applied over the vertex. Conversely, stimulation over M1 did not affect recognition of dot configurations, or recognition of hands that were previously presented as static images (rather than action movie clips) with no object. In Experiment 2, we found that effector recognition was impaired when stimulation was applied part way through (300ms) and at the end (500ms) of the action observation period, indicating that 200ms of action-viewing following stimulation was not long enough to form a new representation that could be used for later recognition. The findings of both experiments suggest that interfering with cortical motor activity during action observation impairs subsequent recognition of the effector involved in the action, which complements previous findings of motor system involvement in object memory. This work provides some of the first evidence that motor processing during action observation is involved in forming representations of the effector that are useful beyond the action observation period

Wavelet-based moment invariants for pattern recognition

Science.gov (United States)

Chen, Guangyi; Xie, Wenfang

2011-07-01

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

The Improvement of Behavior Recognition Accuracy of Micro Inertial Accelerometer by Secondary Recognition Algorithm

Directory of Open Access Journals (Sweden)

Yu Liu

2014-05-01

Full Text Available Behaviors of “still”, “walking”, “running”, “jumping”, “upstairs” and “downstairs” can be recognized by micro inertial accelerometer of low cost. By using the features as inputs to the well-trained BP artificial neural network which is selected as classifier, those behaviors can be recognized. But the experimental results show that the recognition accuracy is not satisfactory. This paper presents secondary recognition algorithm and combine it with BP artificial neural network to improving the recognition accuracy. The Algorithm is verified by the Android mobile platform, and the recognition accuracy can be improved more than 8 %. Through extensive testing statistic analysis, the recognition accuracy can reach 95 % through BP artificial neural network and the secondary recognition, which is a reasonable good result from practical point of view.

Making Activity Recognition Robust against Deceptive Behavior.

Directory of Open Access Journals (Sweden)

Sohrab Saeb

Full Text Available Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shaking the phone while seated to make the classifier detect walking. If they succeeded, we used their motion data to retrain the classifier, and asked them to try to trick it again. The experiment ended when subjects could no longer cheat. We found that some subjects were not able to trick the classifier at all, while others required five rounds of retraining. While classifiers trained on normal activity data predicted true activity with ~38% accuracy, training on the data gathered during the deceptive behavior increased their accuracy to ~84%. We conclude that learning the deceptive behavior of one individual helps to detect the deceptive behavior of others. Thus, we can make current activity recognition robust to deception by including deceptive activity data from a few individuals.

Robust Face Recognition Based on Texture Analysis

Directory of Open Access Journals (Sweden)

Sanun Srisuk

2013-01-01

Full Text Available In this paper, we present a new framework for face recognition with varying illumination based on DCT total variation minimization (DTV, a Gabor filter, a sub-micro-pattern analysis (SMP and discriminated accumulative feature transform (DAFT. We first suppress the illumination effect by using the DCT with the help of TV as a tool for face normalization. The DTV image is then emphasized by the Gabor filter. The facial features are encoded by our proposed method - the SMP. The SMP image is then transformed to the 2D histogram using DAFT. Our system is verified with experiments on the AR and the Yale face database B.

Data set for Tifinagh handwriting character recognition

Directory of Open Access Journals (Sweden)

Omar Bencharef

2015-09-01

Full Text Available The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for handwritten Tifinagh characters composed of 1376 image; 43 Image For Each character. The dataset can be used to train a Tifinagh character recognition system, or to extract the meaning characteristics of each character.

The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital.

Science.gov (United States)

Harris, Patricia R E

2016-09-01

The electrocardiogram (ECG) is a well-established diagnostic tool extensively used in clinical settings. Knowledge of cardiac rhythm and mastery of cardiac waveform interpretation are fundamental for intensive care nurses. Recognition of the normal findings for the 12-lead ECG and understanding the significance of changes from baseline in continuous cardiac monitoring are essential steps toward ensuring safe patient care. This article highlights historical developments in electrocardiography, describes the normal resting 12-lead ECG, and discusses the need for continuous cardiac monitoring. In addition, future directions for the ECG are explored briefly. Copyright © 2016 Elsevier Inc. All rights reserved.

Molecularly imprinted titania nanoparticles for selective recognition and assay of uric acid

Science.gov (United States)

Mujahid, Adnan; Khan, Aimen Idrees; Afzal, Adeel; Hussain, Tajamal; Raza, Muhammad Hamid; Shah, Asma Tufail; uz Zaman, Waheed

2015-06-01

Molecularly imprinted titania nanoparticles are su ccessfully synthesized by sol-gel method for the selective recognition of uric acid. Atomic force microscopy is used to study the morphology of uric acid imprinted titania nanoparticles with diameter in the range of 100-150 nm. Scanning electron microscopy images of thick titania layer indicate the formation of fine network of titania nanoparticles with uniform distribution. Molecular imprinting of uric acid as well as its subsequent washing is confirmed by Fourier transformation infrared spectroscopy measurements. Uric acid rebinding studies reveal the recognition capability of imprinted particles in the range of 0.01-0.095 mmol, which is applicable in monitoring normal to elevated levels of uric acid in human blood. The optical shift (signal) of imprinted particles is six times higher in comparison with non-imprinted particles for the same concentration of uric acid. Imprinted titania particles have shown substantially reduced binding affinity toward interfering and structurally related substances, e.g. ascorbic acid and guanine. These results suggest the possible application of titania nanoparticles in uric acid recognition and quantification in blood serum.

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

Science.gov (United States)

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.

Normal-range verbal-declarative memory in schizophrenia.

Science.gov (United States)

Heinrichs, R Walter; Parlar, Melissa; Pinnock, Farena

2017-10-01

Cognitive impairment is prevalent and related to functional outcome in schizophrenia, but a significant minority of the patient population overlaps with healthy controls on many performance measures, including declarative-verbal-memory tasks. In this study, we assessed the validity, clinical, and functional implications of normal-range (NR), verbal-declarative memory in schizophrenia. Performance normality was defined using normative data for 8 basic California Verbal Learning Test (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000) recall and recognition trials. Schizophrenia patients (n = 155) and healthy control participants (n = 74) were assessed for performance normality, defined as scores within 1 SD of the normative mean on all 8 trials, and assigned to normal- and below-NR memory groups. NR schizophrenia patients (n = 26) and control participants (n = 51) did not differ in general verbal ability, on a reading-based estimate of premorbid ability, across all 8 CVLT-II-score comparisons or in terms of intrusion and false-positive errors and auditory working memory. NR memory patients did not differ from memory-impaired patients (n = 129) in symptom severity, and both patient groups were significantly and similarly disabled in terms of functional status in the community. These results confirm a subpopulation of schizophrenia patients with normal, verbal-declarative-memory performance and no evidence of decline from higher premorbid ability levels. However, NR patients did not experience less severe psychopathology, nor did they show advantage in community adjustment relative to impaired patients. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Pose-invariant face recognition using Markov random fields.

Science.gov (United States)

Ho, Huy Tho; Chellappa, Rama

2013-04-01

One of the key challenges for current face recognition techniques is how to handle pose variations between the probe and gallery face images. In this paper, we present a method for reconstructing the virtual frontal view from a given nonfrontal face image using Markov random fields (MRFs) and an efficient variant of the belief propagation algorithm. In the proposed approach, the input face image is divided into a grid of overlapping patches, and a globally optimal set of local warps is estimated to synthesize the patches at the frontal view. A set of possible warps for each patch is obtained by aligning it with images from a training database of frontal faces. The alignments are performed efficiently in the Fourier domain using an extension of the Lucas-Kanade algorithm that can handle illumination variations. The problem of finding the optimal warps is then formulated as a discrete labeling problem using an MRF. The reconstructed frontal face image can then be used with any face recognition technique. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, we also present an algorithm for classifying whether a given face image is at a frontal or nonfrontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach.

The Legal Recognition of Sign Languages

Science.gov (United States)

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…

Cognitive aspects of haptic form recognition by blind and sighted subjects.

Science.gov (United States)

Bailes, S M; Lambert, R M

1986-11-01

Studies using haptic form recognition tasks have generally concluded that the adventitiously blind perform better than the congenitally blind, implicating the importance of early visual experience in improved spatial functioning. The hypothesis was tested that the adventitiously blind have retained some ability to encode successive information obtained haptically in terms of a global visual representation, while the congenitally blind use a coding system based on successive inputs. Eighteen blind (adventitiously and congenitally) and 18 sighted (blindfolded and performing with vision) subjects were tested on their recognition of raised line patterns when the standard was presented in segments: in immediate succession, or with unfilled intersegmental delays of 5, 10, or 15 seconds. The results did not support the above hypothesis. Three main findings were obtained: normally sighted subjects were both faster and more accurate than the other groups; all groups improved in accuracy of recognition as a function of length of interstimulus interval; sighted subjects tended to report using strategies with a strong verbal component while the blind tended to rely on imagery coding. These results are explained in terms of information-processing theory consistent with dual encoding systems in working memory.

Human gait recognition by pyramid of HOG feature on silhouette images

Science.gov (United States)

Yang, Guang; Yin, Yafeng; Park, Jeanrok; Man, Hong

2013-03-01

As a uncommon biometric modality, human gait recognition has a great advantage of identify people at a distance without high resolution images. It has attracted much attention in recent years, especially in the fields of computer vision and remote sensing. In this paper, we propose a human gait recognition framework that consists of a reliable background subtraction method followed by the pyramid of Histogram of Gradient (pHOG) feature extraction on the silhouette image, and a Hidden Markov Model (HMM) based classifier. Through background subtraction, the silhouette of human gait in each frame is extracted and normalized from the raw video sequence. After removing the shadow and noise in each region of interest (ROI), pHOG feature is computed on the silhouettes images. Then the pHOG features of each gait class will be used to train a corresponding HMM. In the test stage, pHOG feature will be extracted from each test sequence and used to calculate the posterior probability toward each trained HMM model. Experimental results on the CASIA Gait Dataset B1 demonstrate that with our proposed method can achieve very competitive recognition rate.

Human activity recognition and prediction

CERN Document Server

2016-01-01

This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

Using Regression to Measure Holistic Face Processing Reveals a Strong Link with Face Recognition Ability

Science.gov (United States)

DeGutis, Joseph; Wilmer, Jeremy; Mercado, Rogelio J.; Cohan, Sarah

2013-01-01

Although holistic processing is thought to underlie normal face recognition ability, widely discrepant reports have recently emerged about this link in an individual differences context. Progress in this domain may have been impeded by the widespread use of subtraction scores, which lack validity due to their contamination with control condition…

Online and unsupervised face recognition for continuous video stream

Science.gov (United States)

Huo, Hongwen; Feng, Jufu

2009-10-01

We present a novel online face recognition approach for video stream in this paper. Our method includes two stages: pre-training and online training. In the pre-training phase, our method observes interactions, collects batches of input data, and attempts to estimate their distributions (Box-Cox transformation is adopted here to normalize rough estimates). In the online training phase, our method incrementally improves classifiers' knowledge of the face space and updates it continuously with incremental eigenspace analysis. The performance achieved by our method shows its great potential in video stream processing.

Recognition memory span in autopsy-confirmed Dementia with Lewy Bodies and Alzheimer's Disease.

Science.gov (United States)

Salmon, David P; Heindel, William C; Hamilton, Joanne M; Vincent Filoteo, J; Cidambi, Varun; Hansen, Lawrence A; Masliah, Eliezer; Galasko, Douglas

2015-08-01

Evidence from patients with amnesia suggests that recognition memory span tasks engage both long-term memory (i.e., secondary memory) processes mediated by the diencephalic-medial temporal lobe memory system and working memory processes mediated by fronto-striatal systems. Thus, the recognition memory span task may be particularly effective for detecting memory deficits in disorders that disrupt both memory systems. The presence of unique pathology in fronto-striatal circuits in Dementia with Lewy Bodies (DLB) compared to AD suggests that performance on the recognition memory span task might be differentially affected in the two disorders even though they have quantitatively similar deficits in secondary memory. In the present study, patients with autopsy-confirmed DLB or AD, and Normal Control (NC) participants, were tested on separate recognition memory span tasks that required them to retain increasing amounts of verbal, spatial, or visual object (i.e., faces) information across trials. Results showed that recognition memory spans for verbal and spatial stimuli, but not face stimuli, were lower in patients with DLB than in those with AD, and more impaired relative to NC performance. This was despite similar deficits in the two patient groups on independent measures of secondary memory such as the total number of words recalled from long-term storage on the Buschke Selective Reminding Test. The disproportionate vulnerability of recognition memory span task performance in DLB compared to AD may be due to greater fronto-striatal involvement in DLB and a corresponding decrement in cooperative interaction between working memory and secondary memory processes. Assessment of recognition memory span may contribute to the ability to distinguish between DLB and AD relatively early in the course of disease. Copyright © 2015 Elsevier Ltd. All rights reserved.

State-dependent alteration in face emotion recognition in depression.

Science.gov (United States)

Anderson, Ian M; Shippen, Clare; Juhasz, Gabriella; Chase, Diana; Thomas, Emma; Downey, Darragh; Toth, Zoltan G; Lloyd-Williams, Kathryn; Elliott, Rebecca; Deakin, J F William

2011-04-01

Negative biases in emotional processing are well recognised in people who are currently depressed but are less well described in those with a history of depression, where such biases may contribute to vulnerability to relapse. To compare accuracy, discrimination and bias in face emotion recognition in those with current and remitted depression. The sample comprised a control group (n = 101), a currently depressed group (n = 30) and a remitted depression group (n = 99). Participants provided valid data after receiving a computerised face emotion recognition task following standardised assessment of diagnosis and mood symptoms. In the control group women were more accurate in recognising emotions than men owing to greater discrimination. Among participants with depression, those in remission correctly identified more emotions than controls owing to increased response bias, whereas those currently depressed recognised fewer emotions owing to decreased discrimination. These effects were most marked for anger, fear and sadness but there was no significant emotion × group interaction, and a similar pattern tended to be seen for happiness although not for surprise or disgust. These differences were confined to participants who were antidepressant-free, with those taking antidepressants having similar results to the control group. Abnormalities in face emotion recognition differ between people with current depression and those in remission. Reduced discrimination in depressed participants may reflect withdrawal from the emotions of others, whereas the increased bias in those with a history of depression could contribute to vulnerability to relapse. The normal face emotion recognition seen in those taking medication may relate to the known effects of antidepressants on emotional processing and could contribute to their ability to protect against depressive relapse.

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

CERN Document Server

Blacknell, David

2013-01-01

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

Recognition and Toleration

DEFF Research Database (Denmark)

Lægaard, Sune

2010-01-01

Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms or inter...

Comparative analysis of face recognition techniques with illumination variation

International Nuclear Information System (INIS)

Jondhale, K C; Waghmare, L M

2010-01-01

Illumination variation is one of the major challenges in the face recognition. To deal with this problem, this paper presents comparative analysis of three different techniques. First, the DCT is employed to compensate for illumination variations in the logarithm domain. Since illumination variation lies mainly in the low frequency band, an appropriate number of DCT coefficients are truncated to reduce the variations under different lighting conditions. The nearest neighbor classifier based on Euclidean distance is employed for classification. Second, the performance of PCA is checked on normalized image. PCA is a technique used to reduce multidimensional data sets to a lower dimension for analysis. Third, LDA based methods gives a satisfactory result under controlled lighting condition. But its performance under large illumination variation is not satisfactory. So, the performance of LDA is checked on normalized image. Experimental results on the Yale B and ORL database show that the proposed approach of application of PCA and LDA on normalized dataset improves the performance significantly for the face images with large illumination variations.

The novel dehydroepiandrosterone (DHEA) derivative BNN27 counteracts delay-dependent and scopolamine-induced recognition memory deficits in rats.

Science.gov (United States)

Pitsikas, Nikolaos; Gravanis, Achille

2017-04-01

Experimental evidence indicates that the neurosteroids dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulphate (DHEAS) are involved in cognition. BNN27 is a novel 17C spiroepoxy-DHEA derivative, which devoid of steroidogenic activity. The neuroprotective effects of BNN27 have been recently reported. The present study was designed to investigate the effects of BNN27 on recognition memory in rats. For this purpose, the novel object task (NOT), a procedure assessing non-spatial recognition memory and the novel location task (NLT), a procedure evaluating spatial recognition memory were used. Intraperitoneal (i.p.) administration of BNN27 (3 and 10mg/kg) antagonized delay-dependent deficits in the NOT in the normal rat, suggesting that this DHEA derivative affected acquisition, storage and retrieval of information. In addition, BNN27 (3 and 10mg/kg, i.p.) counteracted the scopolamine [0.2mg/kg, subcutaneously (s.c.)]-induced non-spatial and spatial recognition memory deficits. These findings suggest that BNN27 may modulate different aspects of recognition memory, potentially interacting with the cholinergic system, relevant to cognition. Copyright © 2017 Elsevier Inc. All rights reserved.

Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Pattern recognition & machine learning

CERN Document Server

Anzai, Y

1992-01-01

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

Can You See Me Now Visualizing Battlefield Facial Recognition Technology in 2035

Science.gov (United States)

2010-04-01

this analogy: Assume that a normal individual, Tom, is very good at identifying different types of fruit juice such as orange juice , apple juice ...either compositing multiple images together to produce a more complete image or by creating a new algorithm to better deal with these problems...captures multiple frames of video and composites them into an appropriately high-resolution image that can be processed by the facial recognition software

A REVIEW: OPTICAL CHARACTER RECOGNITION

OpenAIRE

Swati Tomar*1 & Amit Kishore2

2018-01-01

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

Implicit and Explicit Memory Bias in Opiate Dependent, Abstinent and Normal Individuals

Directory of Open Access Journals (Sweden)

Jafar Hasani

2013-07-01

Full Text Available Objective: The aim of current research was to assess implicit and explicit memory bias to drug related stimuli in opiate Dependent, abstinent and normal Individuals. Method: Three groups including opiate Dependent, abstinent and normal Individuals (n=25 were selected by available sampling method. After matching on the base of age, education level and type of substance use all participants assessed by recognition task (explicit memory bias and stem completion task (implicit memory bias. Results: The analysis of data showed that opiate dependent and abstinent groups in comparison with normal individual had implicit memory bias, whereas in explicit memory only opiate dependent individuals showed bias. Conclusion: The identification of explicit and implicit memory governing addiction may have practical implications in diagnosis, treatment and prevention of substance abuse.

Challenging ocular image recognition

Science.gov (United States)

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.

Assessing spoken word recognition in children who are deaf or hard of hearing: a translational approach.

Science.gov (United States)

Kirk, Karen Iler; Prusick, Lindsay; French, Brian; Gotch, Chad; Eisenberg, Laurie S; Young, Nancy

2012-06-01

Under natural conditions, listeners use both auditory and visual speech cues to extract meaning from speech signals containing many sources of variability. However, traditional clinical tests of spoken word recognition routinely employ isolated words or sentences produced by a single talker in an auditory-only presentation format. The more central cognitive processes used during multimodal integration, perceptual normalization, and lexical discrimination that may contribute to individual variation in spoken word recognition performance are not assessed in conventional tests of this kind. In this article, we review our past and current research activities aimed at developing a series of new assessment tools designed to evaluate spoken word recognition in children who are deaf or hard of hearing. These measures are theoretically motivated by a current model of spoken word recognition and also incorporate "real-world" stimulus variability in the form of multiple talkers and presentation formats. The goal of this research is to enhance our ability to estimate real-world listening skills and to predict benefit from sensory aid use in children with varying degrees of hearing loss. American Academy of Audiology.

A statistical approach to identify candidate cues for nestmate recognition

DEFF Research Database (Denmark)

van Zweden, Jelle; Pontieri, Luigi; Pedersen, Jes Søe

2014-01-01

normalization, centroid,and distance calculation is most diagnostic to discriminate between NMR cues andother compounds. We find that using a “global centroid” instead of a “colony centroid”significantly improves the analysis. One reason may be that this new approach, unlikeprevious ones, provides...... than forF. exsecta, possibly due to less than ideal datasets. Nonetheless, some compound setsperformed better than others, showing that this approach can be used to identify candidatecompounds to be tested in bio-assays, and eventually crack the sophisticated code thatgoverns nestmate recognition....

Genetic specificity of face recognition.

Science.gov (United States)

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.

Face Detection and Recognition

National Research Council Canada - National Science Library

Jain, Anil K

2004-01-01

This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...

Levels-of-processing effect on word recognition in schizophrenia.

Science.gov (United States)

Ragland, J Daniel; Moelter, Stephen T; McGrath, Claire; Hill, S Kristian; Gur, Raquel E; Bilker, Warren B; Siegel, Steven J; Gur, Ruben C

2003-12-01

Individuals with schizophrenia have difficulty organizing words semantically to facilitate encoding. This is commonly attributed to organizational rather than semantic processing limitations. By requiring participants to classify and encode words on either a shallow (e.g., uppercase/lowercase) or deep level (e.g., concrete/abstract), the levels-of-processing paradigm eliminates the need to generate organizational strategies. This paradigm was administered to 30 patients with schizophrenia and 30 healthy comparison subjects to test whether providing a strategy would improve patient performance. Word classification during shallow and deep encoding was slower and less accurate in patients. Patients also responded slowly during recognition testing and maintained a more conservative response bias following deep encoding; however, both groups showed a robust levels-of-processing effect on recognition accuracy, with unimpaired patient performance following both shallow and deep encoding. This normal levels-of-processing effect in the patient sample suggests that semantic processing is sufficiently intact for patients to benefit from organizational cues. Memory remediation efforts may therefore be most successful if they focus on teaching patients to form organizational strategies during initial encoding.

Forensic Face Recognition: A Survey

NARCIS (Netherlands)

Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Quaglia, Adamo; Epifano, Calogera M.

2012-01-01

The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a

Did depressive symptoms affect recognition of emotional prosody in Parkinson’s disease?

Directory of Open Access Journals (Sweden)

Adriana Vélez Feijó

2008-06-01

Full Text Available Adriana Vélez Feijó1, Carlos RM Rieder3, Márcia LF Chaves21Medical Sciences Post-Graduate Course; 2Internal Medicine Department, School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; 3Movement Disorders Clinic Coordinator, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, BrazilObjective: Evaluate the influence of depressive symptoms on the recognition of emotional prosody in Parkinson’s disease (PD patients, and identify types of emotion on spoken sentences.Methods: Thirty-five PD patients and 65 normal participants were studied. Dementia was checked with the Mini Mental State Examination, Clinical Dementia Rating scale, and DSM IV. Recognition of emotional prosody was tested by asking subjects to listen to 12 recorded statements with neutral affective content that were read with a strong affective expression. Subjects had to recognize the correct emotion by one of four descriptors (angry, sad, cheerful, and neutral. The Beck Depression Inventory (BDI was employed to rate depressive symptoms with the cutoff 14.Results: Total ratings of emotions correctly recognized by participants below and above the BDI cutoff were similar among PD patients and normal individuals. PD patients who correctly identified neutral and anger inflections presented higher rates of depressive symptoms (p = 0.011 and 0.044, respectively. No significant differences were observed in the normal group.Conclusions: Depression may modify some modalities of emotional prosody perception in PD, by increasing the perception of non-pleasant emotions or lack of affection, such as anger or indifference.Keywords: emotional prosody, Parkinson’s disease, depression, emotion

Invariant Face recognition Using Infrared Images

International Nuclear Information System (INIS)

Zahran, E.G.

2012-01-01

Over the past few decades, face recognition has become a rapidly growing research topic due to the increasing demands in many applications of our daily life such as airport surveillance, personal identification in law enforcement, surveillance systems, information safety, securing financial transactions, and computer security. The objective of this thesis is to develop a face recognition system capable of recognizing persons with a high recognition capability, low processing time, and under different illumination conditions, and different facial expressions. The thesis presents a study for the performance of the face recognition system using two techniques; the Principal Component Analysis (PCA), and the Zernike Moments (ZM). The performance of the recognition system is evaluated according to several aspects including the recognition rate, and the processing time. Face recognition systems that use visual images are sensitive to variations in the lighting conditions and facial expressions. The performance of these systems may be degraded under poor illumination conditions or for subjects of various skin colors. Several solutions have been proposed to overcome these limitations. One of these solutions is to work in the Infrared (IR) spectrum. IR images have been suggested as an alternative source of information for detection and recognition of faces, when there is little or no control over lighting conditions. This arises from the fact that these images are formed due to thermal emissions from skin, which is an intrinsic property because these emissions depend on the distribution of blood vessels under the skin. On the other hand IR face recognition systems still have limitations with temperature variations and recognition of persons wearing eye glasses. In this thesis we will fuse IR images with visible images to enhance the performance of face recognition systems. Images are fused using the wavelet transform. Simulation results show that the fusion of visible and

Cell line name recognition in support of the identification of synthetic lethality in cancer from text

Science.gov (United States)

Kaewphan, Suwisa; Van Landeghem, Sofie; Ohta, Tomoko; Van de Peer, Yves; Ginter, Filip; Pyysalo, Sampo

2016-01-01

Motivation: The recognition and normalization of cell line names in text is an important task in biomedical text mining research, facilitating for instance the identification of synthetically lethal genes from the literature. While several tools have previously been developed to address cell line recognition, it is unclear whether available systems can perform sufficiently well in realistic and broad-coverage applications such as extracting synthetically lethal genes from the cancer literature. In this study, we revisit the cell line name recognition task, evaluating both available systems and newly introduced methods on various resources to obtain a reliable tagger not tied to any specific subdomain. In support of this task, we introduce two text collections manually annotated for cell line names: the broad-coverage corpus Gellus and CLL, a focused target domain corpus. Results: We find that the best performance is achieved using NERsuite, a machine learning system based on Conditional Random Fields, trained on the Gellus corpus and supported with a dictionary of cell line names. The system achieves an F-score of 88.46% on the test set of Gellus and 85.98% on the independently annotated CLL corpus. It was further applied at large scale to 24 302 102 unannotated articles, resulting in the identification of 5 181 342 cell line mentions, normalized to 11 755 unique cell line database identifiers. Availability and implementation: The manually annotated datasets, the cell line dictionary, derived corpora, NERsuite models and the results of the large-scale run on unannotated texts are available under open licenses at http://turkunlp.github.io/Cell-line-recognition/. Contact: sukaew@utu.fi PMID:26428294

End-Stop Exemplar Based Recognition

DEFF Research Database (Denmark)

Olsen, Søren I.

2003-01-01

An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....

Speech Recognition on Mobile Devices

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Lindberg, Børge

2010-01-01

in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within......The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...

Markov Models for Handwriting Recognition

CERN Document Server

Plotz, Thomas

2011-01-01

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

Science.gov (United States)

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

Science.gov (United States)

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

Examining ERP correlates of recognition memory: Evidence of accurate source recognition without recollection

Science.gov (United States)

Addante, Richard, J.; Ranganath, Charan; Yonelinas, Andrew, P.

2012-01-01

Recollection is typically associated with high recognition confidence and accurate source memory. However, subjects sometimes make accurate source memory judgments even for items that are not confidently recognized, and it is not known whether these responses are based on recollection or some other memory process. In the current study, we measured event related potentials (ERPs) while subjects made item and source memory confidence judgments in order to determine whether recollection supported accurate source recognition responses for items that were not confidently recognized. In line with previous studies, we found that recognition memory was associated with two ERP effects: an early on-setting FN400 effect, and a later parietal old-new effect [Late Positive Component (LPC)], which have been associated with familiarity and recollection, respectively. The FN400 increased gradually with item recognition confidence, whereas the LPC was only observed for highly confident recognition responses. The LPC was also related to source accuracy, but only for items that had received a high confidence item recognition response; accurate source judgments to items that were less confidently recognized did not exhibit the typical ERP correlate of recollection or familiarity, but rather showed a late, broadly distributed negative ERP difference. The results indicate that accurate source judgments of episodic context can occur even when recollection fails. PMID:22548808

Evaluating music emotion recognition:Lessons from music genre recognition?

OpenAIRE

Sturm, Bob L.

2013-01-01

A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER syste...

A benefit of context reinstatement to recognition memory in aging: the role of familiarity processes.

Science.gov (United States)

Ward, Emma V; Maylor, Elizabeth A; Poirier, Marie; Korko, Malgorzata; Ruud, Jens C M

2017-11-01

Reinstatement of encoding context facilitates memory for targets in young and older individuals (e.g., a word studied on a particular background scene is more likely to be remembered later if it is presented on the same rather than a different scene or no scene), yet older adults are typically inferior at recalling and recognizing target-context pairings. This study examined the mechanisms of the context effect in normal aging. Age differences in word recognition by context condition (original, switched, none, new), and the ability to explicitly remember target-context pairings were investigated using word-scene pairs (Experiment 1) and word-word pairs (Experiment 2). Both age groups benefited from context reinstatement in item recognition, although older adults were significantly worse than young adults at identifying original pairings and at discriminating between original and switched pairings. In Experiment 3, participants were given a three-alternative forced-choice recognition task that allowed older individuals to draw upon intact familiarity processes in selecting original pairings. Performance was age equivalent. Findings suggest that heightened familiarity associated with context reinstatement is useful for boosting recognition memory in aging.

Word Recognition in Auditory Cortex

Science.gov (United States)

DeWitt, Iain D. J.

2013-01-01

Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

[Comparative studies of face recognition].

Science.gov (United States)

Kawai, Nobuyuki

2012-07-01

Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.

Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis

Directory of Open Access Journals (Sweden)

Taeho Hur

2017-04-01

Full Text Available Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recognition system to differentiate among some specific commuting activities (e.g., bus and subway that normally involve similar postures. In this work, we recognize those activities by analyzing the vibrations of the vehicle in which the user is traveling. We extract natural vibration features of buses and subways to distinguish between them and address the confusion that can arise because the activities are both static in terms of user movement. We use the gyroscope to fix the accelerometer to the direction of gravity to achieve an orientation-free use of the sensor. We also propose a correction algorithm to increase the accuracy when used in free living conditions and a battery saving algorithm to consume less power without reducing performance. Our experimental results show that the proposed system can adequately recognize each activity, yielding better accuracy in the detection of bus and subway activities than existing methods.

Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis.

Science.gov (United States)

Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Banos, Oresti; Lee, Sungyoung

2017-04-23

Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recognition system to differentiate among some specific commuting activities (e.g., bus and subway) that normally involve similar postures. In this work, we recognize those activities by analyzing the vibrations of the vehicle in which the user is traveling. We extract natural vibration features of buses and subways to distinguish between them and address the confusion that can arise because the activities are both static in terms of user movement. We use the gyroscope to fix the accelerometer to the direction of gravity to achieve an orientation-free use of the sensor. We also propose a correction algorithm to increase the accuracy when used in free living conditions and a battery saving algorithm to consume less power without reducing performance. Our experimental results show that the proposed system can adequately recognize each activity, yielding better accuracy in the detection of bus and subway activities than existing methods.

Normal variants and artifacts in bone scan: potential for errors in interpretation

International Nuclear Information System (INIS)

Sohn, Myung Hee

2004-01-01

Bone scan is one of the most frequently performed studies in nuclear medicine. In bone scan, the amount of radioisotope taken up by lesion depends primarily on the local rate of bone turnover rather than on the bone mass. Bone scan is extremely sensitive for detecting bony abnormalities. However, abnormalities that appear on bone scan may not always represent disease. The normal scan appearances may be affected not only by skeletal physiology and anatomy but also by a variety of technical factors which can influence image quality. Many normal variants and artifacts may appear on bone scan. They could simulate a pathologic process and could mislead into the wrong diagnostic interpretation. Therefore, their recognition is necessary to avoid misdiagnosis. A nuclear medicine physician should be aware of variable appearance of the normal variants and artifacts on bone scan. In this article, a variety of normal variants and artifacts mimicking real pathologic lesion in bone scan interpretation are discussed and illustrated

AN EFFICIENT SELF-UPDATING FACE RECOGNITION SYSTEM FOR PLASTIC SURGERY FACE

Directory of Open Access Journals (Sweden)

A. Devi

2016-08-01

Full Text Available Facial recognition system is fundamental a computer application for the automatic identification of a person through a digitized image or a video source. The major cause for the overall poor performance is related to the transformations in appearance of the user based on the aspects akin to ageing, beard growth, sun-tan etc. In order to overcome the above drawback, Self-update process has been developed in which, the system learns the biometric attributes of the user every time the user interacts with the system and the information gets updated automatically. The procedures of Plastic surgery yield a skilled and endurable means of enhancing the facial appearance by means of correcting the anomalies in the feature and then treating the facial skin with the aim of getting a youthful look. When plastic surgery is performed on an individual, the features of the face undergo reconstruction either locally or globally. But, the changes which are introduced new by plastic surgery remain hard to get modeled by the available face recognition systems and they deteriorate the performances of the face recognition algorithm. Hence the Facial plastic surgery produces changes in the facial features to larger extent and thereby creates a significant challenge to the face recognition system. This work introduces a fresh Multimodal Biometric approach making use of novel approaches to boost the rate of recognition and security. The proposed method consists of various processes like Face segmentation using Active Appearance Model (AAM, Face Normalization using Kernel Density Estimate/ Point Distribution Model (KDE-PDM, Feature extraction using Local Gabor XOR Patterns (LGXP and Classification using Independent Component Analysis (ICA. Efficient techniques have been used in each phase of the FRAS in order to obtain improved results.

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

Science.gov (United States)

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

2017-12-01

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

Effects of prior exposure on music liking and recognition in patients with temporal lobe lesions.

Science.gov (United States)

Samson, Séverine; Peretz, Isabelle

2005-12-01

Prior exposure to music typically increases liking. This manifestation of implicit memory can be dissociated from explicit memory recognition. To examine the contribution of the medial temporal lobe to musical preference and recognition, we tested patients with either left (LTL) or right (RTL) temporal lobe lesions as well as normal control (NC) participants using the procedure of Peretz et al. The results in the affect task showed that NC and LTL participants preferred the studied over nonstudied melodies, thereby demonstrating an implicit exposure effect on liking judgments, whereas RTL patients failed to exhibit this effect. Explicit recognition was impaired in both LTL and RTL patients as compared to NC participants. On the basis of these findings, we suggest that RTL structures play a critical role in the formation of melody representations that support both priming and memory recognition, whereas LTL structures are more involved in the explicit retrieval of melodies. Furthermore, we were able to test an amnesic patient (PC) with bilateral lesions of the temporal lobe. In this case, the exposure effect on liking was also absent. However, repeated exposure to melodies was found to enhance both liking and recognition judgments. This remarkable sparing of memory observed through melody repetition suggests that extensive exposure may assist both implicit and explicit memory in the presence of global amnesia.

Visual Recognition Memory across Contexts

Science.gov (United States)

Jones, Emily J. H.; Pascalis, Olivier; Eacott, Madeline J.; Herbert, Jane S.

2011-01-01

In two experiments, we investigated the development of representational flexibility in visual recognition memory during infancy using the Visual Paired Comparison (VPC) task. In Experiment 1, 6- and 9-month-old infants exhibited recognition when familiarization and test occurred in the same room, but showed no evidence of recognition when…

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words

Science.gov (United States)

Gordon-Salant, Sandra; Yeni-Komshian, Grace H.; Fitzgibbons, Peter J.; Cohen, Julie I.

2015-01-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech. PMID:25698021

The “parts and wholes” of face recognition: a review of the literature

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Tanaka, James W.; Simonyi, Diana

2016-01-01

It has been claimed that faces are recognized as a “whole” rather than the recognition of individual parts. In a paper published in the Quarterly Journal of Experimental Psychology in 1993, Martha Farah and I attempted to operationalize the holistic claim using the part/whole task. In this task, participants studied a face and then their memory presented in isolation and in the whole face. Consistent with the holistic view, recognition of the part was superior when tested in the whole-face condition compared to when it was tested in isolation. The “whole face” or holistic advantage was not found for faces that were inverted, or scrambled, nor for non-face objects suggesting that holistic encoding was specific to normal, intact faces. In this paper, we reflect on the part/whole paradigm and how it has contributed to our understanding of what it means to recognize a face as a “whole” stimulus. We describe the value of part/whole task for developing theories of holistic and non-holistic recognition of faces and objects. We discuss the research that has probed the neural substrates of holistic processing in healthy adults and people with prosopagnosia and autism. Finally, we examine how experience shapes holistic face recognition in children and recognition of own- and other-race faces in adults. The goal of this article is to summarize the research on the part/whole task and speculate on how it has informed our understanding of holistic face processing. PMID:26886495

Learning through hand- or typewriting influences visual recognition of new graphic shapes: behavioral and functional imaging evidence.

Science.gov (United States)

Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Anton, Jean-Luc; Roth, Muriel; Nazarian, Bruno; Velay, Jean-Luc

2008-05-01

Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.

Fetus in fetu in the scrotal sac of newborn

African Journals Online (AJOL)

scrotal ultrasound showed a well-defined fetiform mass measuring 3 Â 2 cm, which showed bone elements resembling ... were evident as a part of the mass. A tiny atrophied testis ... normal skin; (c) have grossly recognizable anatomic parts;.

Emotional availability, understanding emotions, and recognition of facial emotions in obese mothers with young children.

Science.gov (United States)

Bergmann, Sarah; von Klitzing, Kai; Keitel-Korndörfer, Anja; Wendt, Verena; Grube, Matthias; Herpertz, Sarah; Schütz, Astrid; Klein, Annette M

2016-01-01

Recent research has identified mother-child relationships of low quality as possible risk factors for childhood obesity. However, it remains open how mothers' own obesity influences the quality of mother-child interaction, and particularly emotional availability (EA). Also unclear is the influence of maternal emotional competencies, i.e. understanding emotions and recognizing facial emotions. This study aimed to (1) investigate differences between obese and normal-weight mothers regarding mother-child EA, maternal understanding emotions and recognition of facial emotions, and (2) explore how maternal emotional competencies and maternal weight interact with each other in predicting EA. A better understanding of these associations could inform strategies of obesity prevention especially in children at risk. We assessed EA, understanding emotions and recognition of facial emotions in 73 obese versus 73 normal-weight mothers, and their children aged 6 to 47 months (Mchild age=24.49, 80 females). Obese mothers showed lower EA and understanding emotions. Mothers' normal weight and their ability to understand emotions were positively associated with EA. The ability to recognize facial emotions was positively associated with EA in obese but not in normal-weight mothers. Maternal weight status indirectly influenced EA through its effect on understanding emotions. Maternal emotional competencies may play an important role for establishing high EA in interaction with the child. Children of obese mothers experience lower EA, which may contribute to overweight development. We suggest including elements that aim to improve maternal emotional competencies and mother-child EA in prevention or intervention programmes targeting childhood obesity. Copyright © 2015 Elsevier Inc. All rights reserved.

Non Audio-Video gesture recognition system

DEFF Research Database (Denmark)

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

2016-01-01

Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...

Comparing Face Detection and Recognition Techniques

OpenAIRE

Korra, Jyothi

2016-01-01

This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

Exemplar Based Recognition of Visual Shapes

DEFF Research Database (Denmark)

Olsen, Søren I.

2005-01-01

This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoint....... The matching is insensitive to rotations, limited scalings and small deformations. The recognition is robust to noise, background clutter and partial occlusion. Recognition is possible from few training images and improve with the number of training images.......This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoints...

Superficial Priming in Episodic Recognition

Science.gov (United States)

Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

2010-01-01

We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…

Chronic minocycline treatment improves social recognition memory in adult male Fmr1 knockout mice.

Science.gov (United States)

Yau, Suk Yu; Chiu, Christine; Vetrici, Mariana; Christie, Brian R

2016-10-01

Fragile X syndrome (FXS) is caused by a mutation in the Fmr1 gene that leads to silencing of the gene and a loss of its gene product, Fragile X mental retardation protein (FMRP). Some of the key behavioral phenotypes for FXS include abnormal social anxiety and sociability. Here we show that Fmr1 knock-out (KO) mice exhibit impaired social recognition when presented with a novel mouse, and they display normal social interactions in other sociability tests. Administering minocycline to Fmr1 KO mice throughout critical stages of neural development improved social recognition memory in the novel mouse recognition task. To determine if synaptic changes in the prefrontal cortex (PFC) could have played a role in this improvement, we examined PSD-95, a member of the membrane-associated guanylate kinase family, and signaling molecules (ERK1/2, and Akt) linked to synaptic plasticity in the PFC. Our analyses indicated that while minocycline treatment can enhance behavioral performance, it does not enhance expression of PSD-95, ERK1/2 or Akt in the PFC. Copyright © 2016 Elsevier B.V. All rights reserved.

Specification for projects of radiogeologic recognition

International Nuclear Information System (INIS)

1979-01-01

This instruction is a guidance to achievement of radiogeologic recognition projects. The radiogeologic recognition is a prospecting method that join the classic geologic recognition with measures of rock radioactivity. (C.M.)

Why recognition is rational

Directory of Open Access Journals (Sweden)

Clintin P. Davis-Stober

2010-07-01

Full Text Available The Recognition Heuristic (Gigerenzer and Goldstein, 1996; Goldstein and Gigerenzer, 2002 makes the counter-intuitive prediction that a decision maker utilizing less information may do as well as, or outperform, an idealized decision maker utilizing more information. We lay a theoretical foundation for the use of single-variable heuristics such as the Recognition Heuristic as an optimal decision strategy within a linear modeling framework. We identify conditions under which over-weighting a single predictor is a mini-max strategy among a class of a priori chosen weights based on decision heuristics with respect to a measure of statistical lack of fit we call ``risk''. These strategies, in turn, outperform standard multiple regression as long as the amount of data available is limited. We also show that, under related conditions, weighting only one variable and ignoring all others produces the same risk as ignoring the single variable and weighting all others. This approach has the advantage of generalizing beyond the original environment of the Recognition Heuristic to situations with more than two choice options, binary or continuous representations of recognition, and to other single variable heuristics. We analyze the structure of data used in some prior recognition tasks and find that it matches the sufficient conditions for optimality in our results. Rather than being a poor or adequate substitute for a compensatory model, the Recognition Heuristic closely approximates an optimal strategy when a decision maker has finite data about the world.

Infant visual attention and object recognition.

Science.gov (United States)

Reynolds, Greg D

2015-05-15

This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. Copyright © 2015 Elsevier B.V. All rights reserved.

Automated robust registration of grossly misregistered whole-slide images with varying stains

Science.gov (United States)

Litjens, G.; Safferling, K.; Grabe, N.

2016-03-01

Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

Directory of Open Access Journals (Sweden)

TIMCHENKO, L.

2012-11-01

Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

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

International Nuclear Information System (INIS)

Nascimento, J.A. do.

1982-02-01

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

Probabilistic Open Set Recognition

Science.gov (United States)

Jain, Lalit Prithviraj

Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

Recognition versus Resolution: a Comparison of Visual Acuity Results Using Two Alternative Test Chart Optotype

Directory of Open Access Journals (Sweden)

Jonathan S. Pointer

2008-01-01

Conclusions: For normally sighted subjects wearing an optimal refractive correction, a bias was recorded in favour of recognition over resolution acuity: the clinical difference amounted to approximately 40% of one logMAR chart line, with similar high repeatability for either chart optotype. We conclude that the assumption of clinical equivalence between letter and Landolt acuity is reasonable under optimum test conditions.

Hemispheric lateralization of linguistic prosody recognition in comparison to speech and speaker recognition.

Science.gov (United States)

Kreitewolf, Jens; Friederici, Angela D; von Kriegstein, Katharina

2014-11-15

Hemispheric specialization for linguistic prosody is a controversial issue. While it is commonly assumed that linguistic prosody and emotional prosody are preferentially processed in the right hemisphere, neuropsychological work directly comparing processes of linguistic prosody and emotional prosody suggests a predominant role of the left hemisphere for linguistic prosody processing. Here, we used two functional magnetic resonance imaging (fMRI) experiments to clarify the role of left and right hemispheres in the neural processing of linguistic prosody. In the first experiment, we sought to confirm previous findings showing that linguistic prosody processing compared to other speech-related processes predominantly involves the right hemisphere. Unlike previous studies, we controlled for stimulus influences by employing a prosody and speech task using the same speech material. The second experiment was designed to investigate whether a left-hemispheric involvement in linguistic prosody processing is specific to contrasts between linguistic prosody and emotional prosody or whether it also occurs when linguistic prosody is contrasted against other non-linguistic processes (i.e., speaker recognition). Prosody and speaker tasks were performed on the same stimulus material. In both experiments, linguistic prosody processing was associated with activity in temporal, frontal, parietal and cerebellar regions. Activation in temporo-frontal regions showed differential lateralization depending on whether the control task required recognition of speech or speaker: recognition of linguistic prosody predominantly involved right temporo-frontal areas when it was contrasted against speech recognition; when contrasted against speaker recognition, recognition of linguistic prosody predominantly involved left temporo-frontal areas. The results show that linguistic prosody processing involves functions of both hemispheres and suggest that recognition of linguistic prosody is based on

Yes/No Versus Forced-Choice Recognition Memory in Mild Cognitive Impairment and Alzheimer’s Disease: Patterns of Impairment and Associations with Dementia Severity

Science.gov (United States)

Clark, Lindsay R.; Stricker, Nikki H.; Libon, David J.; Delano-Wood, Lisa; Salmon, David P.; Delis, Dean C.; Bondi, Mark W.

2012-01-01

Memory tests are sensitive to early identification of Alzheimer’s disease (AD) but less useful as the disease advances. However, assessing particular types of recognition memory may better characterize dementia severity in later stages of AD. We sought to examine patterns of recognition memory deficits in individuals with AD and mild cognitive impairment (MCI). Memory performance and global cognition data were collected from participants with AD (n=37), MCI (n=37), and cognitively intact older adults (normal controls, NC; n=35). One-way analyses of variance (ANOVAs) examined differences between groups on yes/no and forced-choice recognition measures. Individuals with amnestic MCI performed worse than NC and nonamnestic MCI participants on yes/no recognition, but were comparable on forced-choice recognition. AD patients were more impaired across yes/no and forced-choice recognition tasks. Individuals with mild AD (≥120 Dementia Rating Scale, DRS) performed better than those with moderate-to-severe AD (recognition, but were equally impaired on yes/no recognition. There were differences in the relationships between learning, recall, and recognition performance across groups. Although yes/no recognition testing may be sensitive to MCI, forced-choice procedures may provide utility in assessing severity of anterograde amnesia in later stages of AD. Implications for assessment of insufficient effort and malingering are also discussed. PMID:23030301

Antral follicle count in normal (fertility-proven) and infertile Indian women.

Science.gov (United States)

Agarwal, Arjit; Verma, Ashish; Agarwal, Shubhra; Shukla, Ram Chandra; Jain, Madhu; Srivastava, Arvind

2014-07-01

Antral follicle count (AFC) has been labeled as the most accurate biomarker to assess female fecundity. Unfortunately, no baseline Indian data exists, and we continue using surrogate values from the Western literature (inferred from studies on women, grossly different than Indian women in morphology and genetic makeup). (1) To establish the role of AFC as a function of ovarian reserve in fertility-proven and in subfertile Indian women. (2) To establish baseline cut-off AFC values for Indian women. Prospective observational case-control study. Thirty patients undergoing workup for infertility were included and compared to equal number of controls (women with proven fertility). The basal ovarian volume and AFC were measured by endovaginal. USG the relevant clinical data and hormonal assays were charted for every patient. SPSS platform was used to perform the Student's t-test and Mann-Whitney U-test for intergroup comparisons. Correlations were determined by Pearson's ranked correlation coefficient. Regression analysis revealed the highest correlation of AFC and age in fertile and infertile patients with difference in mean AFC of both the groups. Comparison of the data recorded for cases and controls showed no significant difference in the mean ovarian volume. AFC has the closest association with chronological age in normal and infertile Indian women. The same is lower in infertile women than in matched controls. Baseline and cut-off values in Indian women are lower than that mentioned in the Western literature.

An electrophysiological analysis of altered cognitive functions in Huntington disease.

Science.gov (United States)

Münte, T F; Ridao-Alonso, M E; Preinfalk, J; Jung, A; Wieringa, B M; Matzke, M; Dengler, R; Johannes, S

1997-09-01

Neuropsychological deficits are a main feature of Huntington disease (HD) with previous data suggesting involvement of memory functions and visual processing. To increase the knowledge about cognitive malfunction in HD in the domains of visual processing and memory by the use of modern electrophysiological techniques (event-related potentials [ERPs]). A case-control design was used. Three ERP paradigms were used; a parallel visual search paradigm allowed for the simultaneous processing of a multi-element visual array in search of a target stimulus, while a serial search paradigm with varied numbers of distractor items necessitated a serial one by one scanning of the arrays. The third experiment was a word-recognition memory task. The measurements were obtained in a neurophysiological laboratory of a university hospital. Nine patients with HD and 9 control subjects matched for age, sex, and education were studied. Components of averaged ERPs were quantified by latency and amplitude measures and subjected to statistical analysis. Behavioral measures (search time, hit rate, and recognition accuracy) were assessed as well. The early visual components showed a significant latency shift (delay of about 50 milliseconds) in HD. In the search paradigms the P3 components differentiating target and standard stimuli were virtually absent in HD as was the ERP effect indexing word recognition. This was accompanied by a marked delay in search times and lower hit rates in the search tasks and a grossly reduced recognition accuracy in the memory task. The results suggest marked impairments of patients with HD in early visual sensory processing (early components). Deficits in visual search might be attributed to an impairment to deploy attentional resources across the visual field and/or an inability to control eye movements. The ERPs in the memory task differed grossly from similar data obtained by others in patients with Alzheimer disease, suggesting a different neural basis for

Viewpoint Manifolds for Action Recognition

Directory of Open Access Journals (Sweden)

Souvenir Richard

2009-01-01

Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

Test battery for measuring the perception and recognition of facial expressions of emotion

Science.gov (United States)

Wilhelm, Oliver; Hildebrandt, Andrea; Manske, Karsten; Schacht, Annekathrin; Sommer, Werner

2014-01-01

Despite the importance of perceiving and recognizing facial expressions in everyday life, there is no comprehensive test battery for the multivariate assessment of these abilities. As a first step toward such a compilation, we present 16 tasks that measure the perception and recognition of facial emotion expressions, and data illustrating each task's difficulty and reliability. The scoring of these tasks focuses on either the speed or accuracy of performance. A sample of 269 healthy young adults completed all tasks. In general, accuracy and reaction time measures for emotion-general scores showed acceptable and high estimates of internal consistency and factor reliability. Emotion-specific scores yielded lower reliabilities, yet high enough to encourage further studies with such measures. Analyses of task difficulty revealed that all tasks are suitable for measuring emotion perception and emotion recognition related abilities in normal populations. PMID:24860528

DCT-based iris recognition.

Science.gov (United States)

Monro, Donald M; Rakshit, Soumyadip; Zhang, Dexin

2007-04-01

This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent Correct Recognition Rate (CRR) and perfect Receiver-Operating Characteristic (ROC) Curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical Equal Error Rate (EER) is predicted to be as low as 2.59 x 10(-4) on the available data sets.

Visual object recognition and category-specificity

DEFF Research Database (Denmark)

Gerlach, Christian

This thesis is based on seven published papers. The majority of the papers address two topics in visual object recognition: (i) category-effects at pre-semantic stages, and (ii) the integration of visual elements into elaborate shape descriptions corresponding to whole objects or large object parts...... (shape configuration). In the early writings these two topics were examined more or less independently. In later works, findings concerning category-effects and shape configuration merge into an integrated model, termed RACE, advanced to explain category-effects arising at pre-semantic stages in visual...... in visual long-term memory. In the thesis it is described how this simple model can account for a wide range of findings on category-specificity in both patients with brain damage and normal subjects. Finally, two hypotheses regarding the neural substrates of the model's components - and how activation...

Physiological arousal in processing recognition information

Directory of Open Access Journals (Sweden)

Guy Hochman

2010-07-01

Full Text Available The recognition heuristic (RH; Goldstein and Gigerenzer, 2002 suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

Page Recognition: Quantum Leap In Recognition Technology

Science.gov (United States)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

A selective deficit in the appreciation and recognition of brightness: brightness agnosia?

Science.gov (United States)

Nijboer, Tanja C W; Nys, Gudrun M S; van der Smagt, Maarten J; de Haan, Edward H F

2009-01-01

We report a patient with extensive brain damage in the right hemisphere who demonstrated a severe impairment in the appreciation of brightness. Acuity, contrast sensitivity as well as luminance discrimination were normal, suggesting her brightness impairment is not a mere consequence of low-level sensory impairments. The patient was not able to indicate the darker or the lighter of two grey squares, even though she was able to see that they differed. In addition, she could not indicate whether the lights in a room were switched on or off, nor was she able to differentiate between normal greyscale images and inverted greyscale images. As the patient recognised objects, colours, and shapes correctly, the impairment is specific for brightness. As low-level, sensory processing is normal, this specific deficit in the recognition and appreciation of brightness appears to be of a higher, cognitive level, the level of semantic knowledge. This appears to be the first report of 'brightness agnosia'.

The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Directory of Open Access Journals (Sweden)

Xiliang Zheng

2015-04-01

Full Text Available We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity, the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

Traffic sign recognition based on deep convolutional neural network

Science.gov (United States)

Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

2017-11-01

Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

Online handwritten mathematical expression recognition

Science.gov (United States)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

Side-View Face Recognition

NARCIS (Netherlands)

Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; van den Biggelaar, Olivier

As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss

[Neurological disease and facial recognition].

Science.gov (United States)

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

2012-07-01

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

Recognition of an Independent Self-Consciousness

DEFF Research Database (Denmark)

Bjerre, Henrik Jøker

2009-01-01

Hegel's concept in the Phenomenology of the Spirit of the "recognition of an independent self-consciousness" is investigated as a point of separation for contemporary philosophy of recognition. I claim that multiculturalism and the theories of recognition (such as Axel Honneth's) based on empiric...... psychology neglect or deny crucial metaphysical aspects of the Hegelian legacy. Instead, I seek to point at an additional, "spiritual", level of recognition, based on the concept of the subject in Lacanian psychoanalysis....

Case-Based Policy and Goal Recognition

Science.gov (United States)

2015-09-30

Policy and Goal Recognizer (PaGR), a case- based system for multiagent keyhole recognition. PaGR is a knowledge recognition component within a decision...However, unlike our agent in the BVR domain, these recognition agents have access to perfect information. Single-agent keyhole plan recognition can be...listed below: 1. Facing Target 2. Closing on Target 3. Target Range 4. Within a Target’s Weapon Range 5. Has Target within Weapon Range 6. Is in Danger

Harmonization versus Mutual Recognition

DEFF Research Database (Denmark)

Jørgensen, Jan Guldager; Schröder, Philipp

The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired with the oppor......The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired...... countries and three firms, where firms first lobby for the policy coordination regime (harmonization versus mutual recognition), and subsequently, in case of harmonization, the global standard is auctioned among the firms. We discuss welfare effects and conclude with policy implications. In particular......, harmonized standards may fail to harvest the full pro-competitive effects from trade liberalization compared to mutual recognition; moreover, the issue is most pronounced in markets featuring price competition....

Self-face recognition in children with autism spectrum disorders: a near-infrared spectroscopy study.

Science.gov (United States)

Kita, Yosuke; Gunji, Atsuko; Inoue, Yuki; Goto, Takaaki; Sakihara, Kotoe; Kaga, Makiko; Inagaki, Masumi; Hosokawa, Toru

2011-06-01

It is assumed that children with autism spectrum disorders (ASD) have specificities for self-face recognition, which is known to be a basic cognitive ability for social development. In the present study, we investigated neurological substrates and potentially influential factors for self-face recognition of ASD patients using near-infrared spectroscopy (NIRS). The subjects were 11 healthy adult men, 13 normally developing boys, and 10 boys with ASD. Their hemodynamic activities in the frontal area and their scanning strategies (eye-movement) were examined during self-face recognition. Other factors such as ASD severities and self-consciousness were also evaluated by parents and patients, respectively. Oxygenated hemoglobin levels were higher in the regions corresponding to the right inferior frontal gyrus than in those corresponding to the left inferior frontal gyrus. In two groups of children these activities reflected ASD severities, such that the more serious ASD characteristics corresponded with lower activity levels. Moreover, higher levels of public self-consciousness intensified the activities, which were not influenced by the scanning strategies. These findings suggest that dysfunction in the right inferior frontal gyrus areas responsible for self-face recognition is one of the crucial neural substrates underlying ASD characteristics, which could potentially be used to evaluate psychological aspects such as public self-consciousness. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

ERK pathway activation bidirectionally affects visual recognition memory and synaptic plasticity in the perirhinal cortex

Directory of Open Access Journals (Sweden)

Davide eSilingardi

2011-12-01

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

[False recognition of faces associated with fronto-temporal dementia with prosopagnosia].

Science.gov (United States)

Verstichel, P

2005-09-01

The association of prosopagnosia and false recognition of faces is unusual and contributes to our understanding of the generation of facial familiarity. A 67-year-old man with a left prefrontal traumatic lesion, developed a temporal variety of fronto-temporal dementia (semantic dementia) with amyotrophic lateral sclerosis. Cerebral imagery demonstrated a bilateral, temporal anterior atrophy predominating in the right hemisphere. The main cognitive signs consisted in severe difficulties to recognize faces of familiar people (prosopagnosia), associated with systematic false recognition of unfamiliar people. Neuropsychological testing indicated that the prosopagnosia probably resulted from the association of an associative/mnemonic mechanism (inability to activate the Face Recognition Units (FRU) from the visual input) and a semantic mechanism (degradation of semantic/biographical information or deconnexion between FRU and this information). At the early stage of the disease, the patient could activate residual semantic information about individuals from their names, but after a 4-year course, he failed to do so. This worsening could be attributed to the extension of the degenerative lesions to the left temporal lobe. Familiar and unfamiliar faces triggered a marked feeling of knowing. False recognition concerned all the unfamiliar faces, and the patient claimed spontaneously that they corresponded to actors, but he could not provide any additional information about their specific identities. The coexistence of prosopagnosia and false recognition suggests the existence of different interconnected systems processing face recognition, one intended to identification of individuals, and the other producing the sense of familiarity. Dysfunctions at different stages of one or the other of these two processes could result in distortions in the feeling of knowing. From this case and others reported in literature, we propose to complete the classical model of face processing

State Toleration, Religious Recognition and Equality

DEFF Research Database (Denmark)

Lægaard, Sune

2013-01-01

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

Vision-Based Navigation and Recognition

National Research Council Canada - National Science Library

Rosenfeld, Azriel

1998-01-01

.... (4) Invariants: both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

Vision-Based Navigation and Recognition

National Research Council Canada - National Science Library

Rosenfeld, Azriel

1996-01-01

.... (4) Invariants -- both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

Voice congruency facilitates word recognition.

Science.gov (United States)

Campeanu, Sandra; Craik, Fergus I M; Alain, Claude

2013-01-01

Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs) while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent) varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

Voice congruency facilitates word recognition.

Directory of Open Access Journals (Sweden)

Sandra Campeanu

Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

Listening effort and perceived clarity for normal-hearing children with the use of digital noise reduction.

Science.gov (United States)

Gustafson, Samantha; McCreery, Ryan; Hoover, Brenda; Kopun, Judy G; Stelmachowicz, Pat

2014-01-01

The goal of this study was to evaluate how digital noise reduction (DNR) impacts listening effort and judgment of sound clarity in children with normal hearing. It was hypothesized that when two DNR algorithms differing in signal-to-noise ratio (SNR) output are compared, the algorithm that provides the greatest improvement in overall output SNR will reduce listening effort and receive a better clarity rating from child listeners. A secondary goal was to evaluate the relation between the inversion method measurements and listening effort with DNR processing. Twenty-four children with normal hearing (ages 7 to 12 years) participated in a speech recognition task in which consonant-vowel-consonant nonwords were presented in broadband background noise. Test stimuli were recorded through two hearing aids with DNR off and DNR on at 0 dB and +5 dB input SNR. Stimuli were presented to listeners and verbal response time (VRT) and phoneme recognition scores were measured. The underlying assumption was that an increase in VRT reflects an increase in listening effort. Children rated the sound clarity for each condition. The two commercially available HAs were chosen based on: (1) an inversion technique, which was used to quantify the magnitude of change in SNR with the activation of DNR, and (2) a measure of magnitude-squared coherence, which was used to ensure that DNR in both devices preserved the spectrum. One device provided a greater improvement in overall output SNR than the other. Both DNR algorithms resulted in minimal spectral distortion as measured using coherence. For both devices, VRT decreased for the DNR-on condition, suggesting that listening effort decreased with DNR in both devices. Clarity ratings were also better in the DNR-on condition for both devices. The device showing the greatest improvement in output SNR with DNR engaged improved phoneme recognition scores. The magnitude of this improved phoneme recognition was not accurately predicted with

Side-View Face Recognition

NARCIS (Netherlands)

Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2010-01-01

Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face

Pharmacologic suppression of target cell recognition by engineered T cells expressing chimeric T-cell receptors.

Science.gov (United States)

Alvarez-Vallina, L; Yañez, R; Blanco, B; Gil, M; Russell, S J

2000-04-01

Adoptive therapy with autologous T cells expressing chimeric T-cell receptors (chTCRs) is of potential interest for the treatment of malignancy. To limit possible T-cell-mediated damage to normal tissues that weakly express the targeted tumor antigen (Ag), we have tested a strategy for the suppression of target cell recognition by engineered T cells. Jurkat T cells were transduced with an anti-hapten chTCR tinder the control of a tetracycline-suppressible promoter and were shown to respond to Ag-positive (hapten-coated) but not to Ag-negative target cells. The engineered T cells were then reacted with hapten-coated target cells at different effector to target cell ratios before and after exposure to tetracycline. When the engineered T cells were treated with tetracycline, expression of the chTCR was greatly decreased and recognition of the hapten-coated target cells was completely suppressed. Tetracycline-mediated suppression of target cell recognition by engineered T cells may be a useful strategy to limit the toxicity of the approach to cancer gene therapy.

Recognition versus Resolution: a Comparison of Visual Acuity Results Using Two Alternative Test Chart Optotype

Science.gov (United States)

Pointer, Jonathan S.

2010-01-01

Purpose To quantify the difference between recognition (letter) and resolution (Landolt) visual acuity (VA) in a group of normally sighted subjects. Is it reasonable to assume that the two acuity measures are clinically equivalent? Methods A pair of 6 m acuity test charts was produced: one comprised letters and the other Landolt broken rings. Construction of both charts conformed to the logMAR design format. Monocular VA was determined for the dominant eye of 300 screened and normally sighted optometric patients aged 16 to 40, each wearing an optical refractive (spectacle) correction. Results Letter acuity was superior to Landolt acuity (P≤0.0001). The mean paired acuity difference was -0.041 logMAR (standard deviation 0.034): the 95% limits of agreement were ±0.067 logMAR units or ±3.3 chart optotype. Repeatability was high and similar for each chart type (±2.1 and ±2.4 optotype for letter and Landolt, respectively). Gender, test sequence, and laterality of the dominant eye (left or right) were each non-statistically significant variables. Conclusions For normally sighted subjects wearing an optimal refractive correction, a bias was recorded in favour of recognition over resolution acuity: the clinical difference amounted to approximately 40% of one logMAR chart line, with similar high repeatability for either chart optotype. We conclude that the assumption of clinical equivalence between letter and Landolt acuity is reasonable under optimum test conditions.

Self-Assembled Core-Satellite Gold Nanoparticle Networks for Ultrasensitive Detection of Chiral Molecules by Recognition Tunneling Current.

Science.gov (United States)

Zhang, Yuanchao; Liu, Jingquan; Li, Da; Dai, Xing; Yan, Fuhua; Conlan, Xavier A; Zhou, Ruhong; Barrow, Colin J; He, Jin; Wang, Xin; Yang, Wenrong

2016-05-24

Chirality sensing is a very challenging task. Here, we report a method for ultrasensitive detection of chiral molecule l/d-carnitine based on changes in the recognition tunneling current across self-assembled core-satellite gold nanoparticle (GNP) networks. The recognition tunneling technique has been demonstrated to work at the single molecule level where the binding between the reader molecules and the analytes in a nanojunction. This process was observed to generate a unique and sensitive change in tunneling current, which can be used to identify the analytes of interest. The molecular recognition mechanism between amino acid l-cysteine and l/d-carnitine has been studied with the aid of SERS. The different binding strength between homo- or heterochiral pairs can be effectively probed by the copper ion replacement fracture. The device resistance was measured before and after the sequential exposures to l/d-carnitine and copper ions. The normalized resistance change was found to be extremely sensitive to the chirality of carnitine molecule. The results suggested that a GNP networks device optimized for recognition tunneling was successfully built and that such a device can be used for ultrasensitive detection of chiral molecules.

Document recognition serving people with disabilities

Science.gov (United States)

Fruchterman, James R.

2007-01-01

Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

Infant Visual Recognition Memory

Science.gov (United States)

Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.

2004-01-01

Visual recognition memory is a robust form of memory that is evident from early infancy, shows pronounced developmental change, and is influenced by many of the same factors that affect adult memory; it is surprisingly resistant to decay and interference. Infant visual recognition memory shows (a) modest reliability, (b) good discriminant…

Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective.

Science.gov (United States)

Corcoran, C M; Keilp, J G; Kayser, J; Klim, C; Butler, P D; Bruder, G E; Gur, R C; Javitt, D C

2015-10-01

Schizophrenia is characterized by profound and disabling deficits in the ability to recognize emotion in facial expression and tone of voice. Although these deficits are well documented in established schizophrenia using recently validated tasks, their predictive utility in at-risk populations has not been formally evaluated. The Penn Emotion Recognition and Discrimination tasks, and recently developed measures of auditory emotion recognition, were administered to 49 clinical high-risk subjects prospectively followed for 2 years for schizophrenia outcome, and 31 healthy controls, and a developmental cohort of 43 individuals aged 7-26 years. Deficit in emotion recognition in at-risk subjects was compared with deficit in established schizophrenia, and with normal neurocognitive growth curves from childhood to early adulthood. Deficits in emotion recognition significantly distinguished at-risk patients who transitioned to schizophrenia. By contrast, more general neurocognitive measures, such as attention vigilance or processing speed, were non-predictive. The best classification model for schizophrenia onset included both face emotion processing and negative symptoms, with accuracy of 96%, and area under the receiver-operating characteristic curve of 0.99. In a parallel developmental study, emotion recognition abilities were found to reach maturity prior to traditional age of risk for schizophrenia, suggesting they may serve as objective markers of early developmental insult. Profound deficits in emotion recognition exist in at-risk patients prior to schizophrenia onset. They may serve as an index of early developmental insult, and represent an effective target for early identification and remediation. Future studies investigating emotion recognition deficits at both mechanistic and predictive levels are strongly encouraged.

Hidden State Conditional Random Field for Abnormal Activity Recognition in Smart Homes

Directory of Open Access Journals (Sweden)

Yu Tong

2015-03-01

Full Text Available As the number of elderly people has increased worldwide, there has been a surge of research into assistive technologies to provide them with better care by recognizing their normal and abnormal activities. However, existing abnormal activity recognition (AAR algorithms rarely consider sub-activity relations when recognizing abnormal activities. This paper presents an application of the Hidden State Conditional Random Field (HCRF method to detect and assess abnormal activities that often occur in elderly persons’ homes. Based on HCRF, this paper designs two AAR algorithms, and validates them by comparing them with a feature vector distance based algorithm in two experiments. The results demonstrate that the proposed algorithms favorably outperform the competitor, especially when abnormal activities have same sensor type and sensor number as normal activities.

The location and recognition of anti-counterfeiting code image with complex background

Science.gov (United States)

Ni, Jing; Liu, Quan; Lou, Ping; Han, Ping

2017-07-01

The order of cigarette market is a key issue in the tobacco business system. The anti-counterfeiting code, as a kind of effective anti-counterfeiting technology, can identify counterfeit goods, and effectively maintain the normal order of market and consumers' rights and interests. There are complex backgrounds, light interference and other problems in the anti-counterfeiting code images obtained by the tobacco recognizer. To solve these problems, the paper proposes a locating method based on Susan operator, combined with sliding window and line scanning,. In order to reduce the interference of background and noise, we extract the red component of the image and convert the color image into gray image. For the confusing characters, recognition results correction based on the template matching method has been adopted to improve the recognition rate. In this method, the anti-counterfeiting code can be located and recognized correctly in the image with complex background. The experiment results show the effectiveness and feasibility of the approach.

Similarity measures for face recognition

CERN Document Server

Vezzetti, Enrico

2015-01-01

Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

Associations between facial emotion recognition, cognition and alexithymia in patients with schizophrenia: comparison of photographic and virtual reality presentations.

Science.gov (United States)

Gutiérrez-Maldonado, J; Rus-Calafell, M; Márquez-Rejón, S; Ribas-Sabaté, J

2012-01-01

Emotion recognition is known to be impaired in schizophrenia patients. Although cognitive deficits and symptomatology have been associated with this impairment there are other patient characteristics, such as alexithymia, which have not been widely explored. Emotion recognition is normally assessed by means of photographs, although they do not reproduce the dynamism of human expressions. Our group has designed and validated a virtual reality (VR) task to assess and subsequently train schizophrenia patients. The present study uses this VR task to evaluate the impaired recognition of facial affect in patients with schizophrenia and to examine its association with cognitive deficit and the patients' inability to express feelings. Thirty clinically stabilized outpatients with a well-established diagnosis of schizophrenia or schizoaffective disorder were assessed in neuropsychological, symptomatic and affective domains. They then performed the facial emotion recognition task. Statistical analyses revealed no significant differences between the two presentation conditions (photographs and VR) in terms of overall errors made. However, anger and fear were easier to recognize in VR than in photographs. Moreover, strong correlations were found between psychopathology and the errors made.

Famous face recognition, face matching, and extraversion.

Science.gov (United States)

Lander, Karen; Poyarekar, Siddhi

2015-01-01

It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

Testing Measurement Invariance across Groups of Children with and without Attention-Deficit/ Hyperactivity Disorder: Applications for Word Recognition and Spelling Tasks.

Science.gov (United States)

Lúcio, Patrícia S; Salum, Giovanni; Swardfager, Walter; Mari, Jair de Jesus; Pan, Pedro M; Bressan, Rodrigo A; Gadelha, Ary; Rohde, Luis A; Cogo-Moreira, Hugo

2017-01-01

Although studies have consistently demonstrated that children with attention-deficit/hyperactivity disorder (ADHD) perform significantly lower than controls on word recognition and spelling tests, such studies rely on the assumption that those groups are comparable in these measures. This study investigates comparability of word recognition and spelling tests based on diagnostic status for ADHD through measurement invariance methods. The participants ( n = 1,935; 47% female; 11% ADHD) were children aged 6-15 with normal IQ (≥70). Measurement invariance was investigated through Confirmatory Factor Analysis and Multiple Indicators Multiple Causes models. Measurement invariance was attested in both methods, demonstrating the direct comparability of the groups. Children with ADHD were 0.51 SD lower in word recognition and 0.33 SD lower in spelling tests than controls. Results suggest that differences in performance on word recognition and spelling tests are related to true mean differences based on ADHD diagnostic status. Implications for clinical practice and research are discussed.

Kazakh Traditional Dance Gesture Recognition

Science.gov (United States)

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

2014-04-01

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

Fine-grained recognition of plants from images.

Science.gov (United States)

Šulc, Milan; Matas, Jiří

2017-01-01

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

CONCEPTUAL AND THEORETICAL DIMENSIONS REGARDING THE RECOGNITION OF STOCKS IN PUBLIC INSTITUTIONS

Directory of Open Access Journals (Sweden)

Cristina Otilia, Ţenovici

2013-01-01

Full Text Available The process of normalization leads to harmonization and accounting convergence by formalizing and materializing the objectives, concepts, methods, rules and procedures for the production and use of accounting information. The purpose of this study is to analyze the evolution of Romanian accounting and accounting harmonization and convergence with IPSAS 12 "Inventories". Also, a comparison of the main features related to current national and international regulations, presenting similarities and differences related to the recognition of stocks to identify the set of converging or diverging elements.

Transfer-Appropriate Processing in Recognition Memory: Perceptual and Conceptual Effects on Recognition Memory Depend on Task Demands

Science.gov (United States)

Parks, Colleen M.

2013-01-01

Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which…

Recognition

DEFF Research Database (Denmark)

Gimmler, Antje

2017-01-01

In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory mus...

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

Science.gov (United States)

Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

2015-01-01

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

Fault diagnosis and performance monitoring for pumps by means of vibration measurement and pattern recognition

International Nuclear Information System (INIS)

Grabner, A.; Weiss, F.P.

1984-12-01

In recent years the early detection of malfunctions with noise and vibration analysis techniques has become a more and more important method for increasing availability and safety of various components in technical plants. The possibility of pattern recognition assisted vibration monitoring and its practical realization are demonstrated by failure diagnosis and trend analysis of the condition of large centrifugal pumps in hydraulic circuits. Some problems as, e.g., the finding of dynamic failure models, signal analysis, feature extraction and statistical pattern recognition, which helps automatically to decide whether the pump works normally or not, are discussed in more detail. In the paper it is shown that for various types of machines the chance of success of condition based maintenance can be enhanced by such an automatic vibration monitoring. (author)

Face Recognition in Humans and Machines

Science.gov (United States)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

An Introduction to Face Recognition Technology

Directory of Open Access Journals (Sweden)

Shang-Hung Lin

2000-01-01

Full Text Available Recently face recognition is attracting much attention in the society of network multimedia information access.  Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video.  Network access control via face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction.  Indexing and/or retrieving video data based on the appearances of particular persons will be useful for users such as news reporters, political scientists, and moviegoers.  For the applications of videophone and teleconferencing, the assistance of face recognition also provides a more efficient coding scheme.  In this paper, we give an introductory course of this new information processing technology.  The paper shows the readers the generic framework for the face recognition system, and the variants that are frequently encountered by the face recognizer.  Several famous face recognition algorithms, such as eigenfaces and neural networks, will also be explained.

Paradigms in object recognition

International Nuclear Information System (INIS)

Mutihac, R.; Mutihac, R.C.

1999-09-01

A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)

The coevolution of recognition and social behavior.

Science.gov (United States)

Smead, Rory; Forber, Patrick

2016-05-26

Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation.

Application of PSO for solving problems of pattern recognition

Directory of Open Access Journals (Sweden)

S. N. Chukanov

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Minglin Wu

2016-10-01

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

Case report

African Journals Online (AJOL)

abp

2017-11-01

Nov 1, 2017 ... Non-Hodgkin's lymphomas (NHL) with intracranial origin are very rare and constitutes ... Diffuse large B cell lymphoma (DLBCL) is the most common subtype of NHL ... revealed grossly normal complete blood count (CBC) with slightly .... of chemotherapeutic drugs and autologous stem cell transplantation.

Electrographic imaging of recognition memory in 34-38 week gestation intrauterine growth restricted newborns.

Science.gov (United States)

Black, Linda S; deRegnier, Raye-Ann; Long, Jeffrey; Georgieff, Michael K; Nelson, Charles A

2004-11-01

Electrophysiological imaging of recognition memory using event-related potentials (ERPs) in intrauterine growth-restricted (IUGR) newborns allows assessment of recognition memory before the onset of multiple confounding variables. Animal models that reproduce the physiologic components associated with IUGR have demonstrated adverse effects on the hippocampus, a structure that is essential to normal memory processing. Previous electrophysiologic studies have demonstrated shortened auditory-evoked potential (AEP) and visual-evoked potential (VEP) latencies in IUGR infants suggesting accelerated neural maturation in response to the adverse in-utero environment. The hypothesis of the current study was that newborns with IUGR and head-sparing would demonstrate altered auditory recognition memory when compared to controls and that the configuration of the alteration would evidence advanced maturation but still be different from that of typically grown newborns. Twelve IUGR newborns born at 34-38 weeks gestation with head-sparing and 16 age-matched control newborns were tested with both a speech/nonspeech paradigm to assess auditory sensory processing and a novel (stranger's voice) and familiar (mother's voice) paradigm to assess recognition memory. In the recognition memory experiment, a three-way interaction of condition, lead, and group was identified for the lateral leads T4, CM3, and CM4 with the response to the mother being of much greater area in the IUGR cohort than in the controls. This ERP configuration has previously been reported for the midline leads in term newborns. The findings indicate that IUGR newborns with head-sparing have electrophysiologic evidence of accelerated maturation of cognitive processing suggesting an atypical process of maturation that may not support typical cognitive development.

The recognition heuristic: A decade of research

Directory of Open Access Journals (Sweden)

Gerd Gigerenzer

2011-02-01

Full Text Available The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein and Gigerenzer, 1999, 2002, including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.

Bilingual Language Switching: Production vs. Recognition

Science.gov (United States)

Mosca, Michela; de Bot, Kees

2017-01-01

This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. PMID:28638361

Stereotype Associations and Emotion Recognition

NARCIS (Netherlands)

Bijlstra, Gijsbert; Holland, Rob W.; Dotsch, Ron; Hugenberg, Kurt; Wigboldus, Daniel H. J.

We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static

The activation of visual face memory and explicit face recognition are delayed in developmental prosopagnosia.

Science.gov (United States)

Parketny, Joanna; Towler, John; Eimer, Martin

2015-08-01

Individuals with developmental prosopagnosia (DP) are strongly impaired in recognizing faces, but the causes of this deficit are not well understood. We employed event-related brain potentials (ERPs) to study the time-course of neural processes involved in the recognition of previously unfamiliar faces in DPs and in age-matched control participants with normal face recognition abilities. Faces of different individuals were presented sequentially in one of three possible views, and participants had to detect a specific Target Face ("Joe"). EEG was recorded during task performance to Target Faces, Nontarget Faces, or the participants' Own Face (which had to be ignored). The N250 component was measured as a marker of the match between a seen face and a stored representation in visual face memory. The subsequent P600f was measured as an index of attentional processes associated with the conscious awareness and recognition of a particular face. Target Faces elicited reliable N250 and P600f in the DP group, but both of these components emerged later in DPs than in control participants. This shows that the activation of visual face memory for previously unknown learned faces and the subsequent attentional processing and conscious recognition of these faces are delayed in DP. N250 and P600f components to Own Faces did not differ between the two groups, indicating that the processing of long-term familiar faces is less affected in DP. However, P600f components to Own Faces were absent in two participants with DP who failed to recognize their Own Face during the experiment. These results provide new evidence that face recognition deficits in DP may be linked to a delayed activation of visual face memory and explicit identity recognition mechanisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

1Interaction between serum BDNF and aerobic fitness predicts recognition memory in healthy young adults

Science.gov (United States)

Whiteman, Andrew; Young, Daniel E.; He, Xuemei; Chen, Tai C.; Wagenaar, Robert C.; Stern, Chantal; Schon, Karin

2013-01-01

Convergent evidence from human and non-human animal studies suggests aerobic exercise and increased aerobic capacity may be beneficial for brain health and cognition. It is thought growth factors may mediate this putative relationship, particularly by augmenting plasticity mechanisms in the hippocampus, a brain region critical for learning and memory. Among these factors, glucocorticoids, brain derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), and vascular endothelial growth factor (VEGF), hormones that have considerable and diverse physiological importance, are thought to effect normal and exercise-induced hippocampal plasticity. Despite these predictions, relatively few published human studies have tested hypotheses that relate exercise and fitness to the hippocampus, and none have considered the potential links to all of these hormonal components. Here we present cross-sectional data from a study of recognition memory; serum BDNF, cortisol, IGF-1, and VEGF levels; and aerobic capacity in healthy young adults. We measured circulating levels of these hormones together with performance on a recognition memory task, and a standard graded treadmill test of aerobic fitness. Regression analyses demonstrated BDNF and aerobic fitness predict recognition memory in an interactive manner. In addition, IGF-1 was positively associated with aerobic fitness, but not with recognition memory. Our results may suggest an exercise adaptation-related change in the BDNF dose-response curve that relates to hippocampal memory. PMID:24269495

Galeotti on recognition as inclusion

DEFF Research Database (Denmark)

Lægaard, Sune

2008-01-01

Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells ...

Recognition of names of eminent psychologists.

Science.gov (United States)

Duncan, C P

1976-10-01

Faculty members, graduate students, undergraduate majors, and introductory psychology students checked those names they recognized in the list of 228 deceased psychologists, rated for eminence, provided by Annin, Boring, and Watson. Mean percentage recognition was less than 50% for the 128 American psychologists, and less than 25% for the 100 foreign psychologists, by the faculty subjects. The other three groups of subjects gave even lower recognition scores. Recognition was probably also influenced by recency; median year of death of the American psychologists was 1955, of the foreign psychologists, 1943. High recognition (defined as recognition by 80% or more of the faculty group) was achieved by only 34 psychologists, almost all of them American. These highly recognized psychologists also had high eminence ratings, but there was an equal number of psychologists with high eminence ratings that were poorly recognized.

Evaluating Recall and Recognition Memory Using the Montreal Cognitive Assessment: Applicability for Alzheimer's and Huntington's Diseases.

Science.gov (United States)

Van Liew, Charles; Santoro, Maya S; Goldstein, Jody; Gluhm, Shea; Gilbert, Paul E; Corey-Bloom, Jody

2016-12-01

We sought to investigate whether the Montreal Cognitive Assessment (MoCA) could provide a brief assessment of recall and recognition using Huntington disease (HD) and Alzheimer disease (AD) as disorders characterized by different memory deficits. This study included 80 participants with HD, 64 participants with AD, and 183 community-dwelling control participants. Random-effects hierarchical logistic regressions were performed to assess the relative performance of the normal control (NC), participants with HD, and participants with AD on verbal free recall, cued recall, and multiple-choice recognition on the MoCA. The NC participants performed significantly better than participants with AD at all the 3 levels of assessment. No difference existed between participants with HD and NC for cued recall, but NC participants performed significantly better than participants with HD on free recall and recognition. The participants with HD performed significantly better than participants with AD at all the 3 levels of assessment. The MoCA appears to be a valuable, brief cognitive assessment capable of identifying specific memory deficits consistent with known differences in memory profiles. © The Author(s) 2016.

Assessing spoken word recognition in children who are deaf or hard of hearing: A translational approach

OpenAIRE

Kirk, Karen Iler; Prusick, Lindsay; French, Brian; Gotch, Chad; Eisenberg, Laurie S.; Young, Nancy

2012-01-01

Under natural conditions, listeners use both auditory and visual speech cues to extract meaning from speech signals containing many sources of variability. However, traditional clinical tests of spoken word recognition routinely employ isolated words or sentences produced by a single talker in an auditory-only presentation format. The more central cognitive processes used during multimodal integration, perceptual normalization and lexical discrimination that may contribute to individual varia...

Multivariate statistical pattern recognition system for reactor noise analysis

International Nuclear Information System (INIS)

Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

1976-01-01

A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system

Multivariate statistical pattern recognition system for reactor noise analysis

International Nuclear Information System (INIS)

Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

1975-01-01

A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references

A Spatially Constrained Multi-autoencoder Approach for Multivariate Geochemical Anomaly Recognition

Science.gov (United States)

Lirong, C.; Qingfeng, G.; Renguang, Z.; Yihui, X.

2017-12-01

Separating and recognizing geochemical anomalies from the geochemical background is one of the key tasks in geochemical exploration. Many methods have been developed, such as calculating the mean ±2 standard deviation, and fractal/multifractal models. In recent years, deep autoencoder, a deep learning approach, have been used for multivariate geochemical anomaly recognition. While being able to deal with the non-normal distributions of geochemical concentrations and the non-linear relationships among them, this self-supervised learning method does not take into account the spatial heterogeneity of geochemical background and the uncertainty induced by the randomly initialized weights of neurons, leading to ineffective recognition of weak anomalies. In this paper, we introduce a spatially constrained multi-autoencoder (SCMA) approach for multivariate geochemical anomaly recognition, which includes two steps: spatial partitioning and anomaly score computation. The first step divides the study area into multiple sub-regions to segregate the geochemical background, by grouping the geochemical samples through K-means clustering, spatial filtering, and spatial constraining rules. In the second step, for each sub-region, a group of autoencoder neural networks are constructed with an identical structure but different initial weights on neurons. Each autoencoder is trained using the geochemical samples within the corresponding sub-region to learn the sub-regional geochemical background. The best autoencoder of a group is chosen as the final model for the corresponding sub-region. The anomaly score at each location can then be calculated as the euclidean distance between the observed concentrations and reconstructed concentrations of geochemical elements.The experiments using the geochemical data and Fe deposits in the southwestern Fujian province of China showed that our SCMA approach greatly improved the recognition of weak anomalies, achieving the AUC of 0.89, compared

[Face recognition in patients with schizophrenia].

Science.gov (United States)

Doi, Hirokazu; Shinohara, Kazuyuki

2012-07-01

It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

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Pavol Partila

2015-01-01

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

Speech Clarity Index (Ψ): A Distance-Based Speech Quality Indicator and Recognition Rate Prediction for Dysarthric Speakers with Cerebral Palsy

Science.gov (United States)

Kayasith, Prakasith; Theeramunkong, Thanaruk

It is a tedious and subjective task to measure severity of a dysarthria by manually evaluating his/her speech using available standard assessment methods based on human perception. This paper presents an automated approach to assess speech quality of a dysarthric speaker with cerebral palsy. With the consideration of two complementary factors, speech consistency and speech distinction, a speech quality indicator called speech clarity index (Ψ) is proposed as a measure of the speaker's ability to produce consistent speech signal for a certain word and distinguished speech signal for different words. As an application, it can be used to assess speech quality and forecast speech recognition rate of speech made by an individual dysarthric speaker before actual exhaustive implementation of an automatic speech recognition system for the speaker. The effectiveness of Ψ as a speech recognition rate predictor is evaluated by rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). The results show that Ψ is a promising indicator for predicting recognition rate of dysarthric speech. All experiments had been done on speech corpus composed of speech data from eight normal speakers and eight dysarthric speakers.

ProNormz--an integrated approach for human proteins and protein kinases normalization.

Science.gov (United States)

Subramani, Suresh; Raja, Kalpana; Natarajan, Jeyakumar

2014-02-01

The task of recognizing and normalizing protein name mentions in biomedical literature is a challenging task and important for text mining applications such as protein-protein interactions, pathway reconstruction and many more. In this paper, we present ProNormz, an integrated approach for human proteins (HPs) tagging and normalization. In Homo sapiens, a greater number of biological processes are regulated by a large human gene family called protein kinases by post translational phosphorylation. Recognition and normalization of human protein kinases (HPKs) is considered to be important for the extraction of the underlying information on its regulatory mechanism from biomedical literature. ProNormz distinguishes HPKs from other HPs besides tagging and normalization. To our knowledge, ProNormz is the first normalization system available to distinguish HPKs from other HPs in addition to gene normalization task. ProNormz incorporates a specialized synonyms dictionary for human proteins and protein kinases, a set of 15 string matching rules and a disambiguation module to achieve the normalization. Experimental results on benchmark BioCreative II training and test datasets show that our integrated approach achieve a fairly good performance and outperforms more sophisticated semantic similarity and disambiguation systems presented in BioCreative II GN task. As a freely available web tool, ProNormz is useful to developers as extensible gene normalization implementation, to researchers as a standard for comparing their innovative techniques, and to biologists for normalization and categorization of HPs and HPKs mentions in biomedical literature. URL: http://www.biominingbu.org/pronormz. Copyright © 2013 Elsevier Inc. All rights reserved.

The development of the University of Jordan word recognition test.

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Garadat, Soha N; Abdulbaqi, Khader J; Haj-Tas, Maisa A

2017-06-01

To develop and validate a digitally recorded speech test battery to assess speech perception in Jordanian Arabic-speaking adults. Selected stimuli were digitally recorded and were divided into four lists of 25 words each. Speech audiometry was completed for all listeners. Participants were divided into two equal groups of 30 listeners each with equal male to female ratio. The first group of participants completed speech reception thresholds (SRTs) and word recognition testing on each of the four lists using a fixed intensity. The second group of listeners was tested on each of the four lists at different intensity levels in order to obtain the performance-intensity function. Sixty normal-hearing listeners in the age range of 19-25 years. All participants were native speakers of Jordanian Arabic. Results revealed that there were no significant differences between SRTs and pure tone average. Additionally, there were no differences across lists at multiple intensity levels. In general, the current study was successful in producing recorded speech materials for Jordanian Arabic population. This suggests that the speech stimuli generated by this study are suitable for measuring speech recognition in Jordanian Arabic-speaking listeners.

Strabismus Recognition Using Eye-Tracking Data and Convolutional Neural Networks

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Zenghai Chen

2018-01-01

Full Text Available Strabismus is one of the most common vision diseases that would cause amblyopia and even permanent vision loss. Timely diagnosis is crucial for well treating strabismus. In contrast to manual diagnosis, automatic recognition can significantly reduce labor cost and increase diagnosis efficiency. In this paper, we propose to recognize strabismus using eye-tracking data and convolutional neural networks. In particular, an eye tracker is first exploited to record a subject’s eye movements. A gaze deviation (GaDe image is then proposed to characterize the subject’s eye-tracking data according to the accuracies of gaze points. The GaDe image is fed to a convolutional neural network (CNN that has been trained on a large image database called ImageNet. The outputs of the full connection layers of the CNN are used as the GaDe image’s features for strabismus recognition. A dataset containing eye-tracking data of both strabismic subjects and normal subjects is established for experiments. Experimental results demonstrate that the natural image features can be well transferred to represent eye-tracking data, and strabismus can be effectively recognized by our proposed method.

Recognition of lyso-phospholipids by human natural killer T lymphocytes.

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Lisa M Fox

2009-10-01

Full Text Available Natural killer T (NKT cells are a subset of T lymphocytes with potent immunoregulatory properties. Recognition of self-antigens presented by CD1d molecules is an important route of NKT cell activation; however, the molecular identity of specific autoantigens that stimulate human NKT cells remains unclear. Here, we have analyzed human NKT cell recognition of CD1d cellular ligands. The most clearly antigenic species was lyso-phosphatidylcholine (LPC. Diacylated phosphatidylcholine and lyso-phosphoglycerols differing in the chemistry of the head group stimulated only weak responses from human NKT cells. However, lyso-sphingomyelin, which shares the phosphocholine head group of LPC, also activated NKT cells. Antigen-presenting cells pulsed with LPC were capable of stimulating increased cytokine responses by NKT cell clones and by freshly isolated peripheral blood lymphocytes. These results demonstrate that human NKT cells recognize cholinated lyso-phospholipids as antigens presented by CD1d. Since these lyso-phospholipids serve as lipid messengers in normal physiological processes and are present at elevated levels during inflammatory responses, these findings point to a novel link between NKT cells and cellular signaling pathways that are associated with human disease pathophysiology.

Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.

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Tao, Dapeng; Jin, Lianwen; Yuan, Yuan; Xue, Yang

2016-06-01

With the rapid development of mobile devices and pervasive computing technologies, acceleration-based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. Different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. We thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. Therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (EMRP) algorithm. EMRP simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. Experiments are conducted on the South China University of Technology naturalistic 3-D acceleration-based activity dataset and the naturalistic mobile-devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration-based human activity recognition.

Facial recognition in education system

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Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

2017-11-01

Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

Maturational changes in ear advantage for monaural word recognition in noise among listeners with central auditory processing disorders

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Mohsin Ahmed Shaikh

2017-02-01

Full Text Available This study aimed to investigate differences between ears in performance on a monaural word recognition in noise test among individuals across a broad range of ages assessed for (CAPD. Word recognition scores in quiet and in speech noise were collected retrospectively from the medical files of 107 individuals between the ages of 7 and 30 years who were diagnosed with (CAPD. No ear advantage was found on the word recognition in noise task in groups less than ten years. Performance in both ears was equally poor. Right ear performance improved across age groups, with scores of individuals above age 10 years falling within the normal range. In contrast, left ear performance remained essentially stable and in the impaired range across all age groups. Findings indicate poor left hemispheric dominance for speech perception in noise in children below the age of 10 years with (CAPD. However, a right ear advantage on this monaural speech in noise task was observed for individuals 10 years and older.

Stimulus-independent semantic bias misdirects word recognition in older adults.

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Rogers, Chad S; Wingfield, Arthur

2015-07-01

Older adults' normally adaptive use of semantic context to aid in word recognition can have a negative consequence of causing misrecognitions, especially when the word actually spoken sounds similar to a word that more closely fits the context. Word-pairs were presented to young and older adults, with the second word of the pair masked by multi-talker babble varying in signal-to-noise ratio. Results confirmed older adults' greater tendency to misidentify words based on their semantic context compared to the young adults, and to do so with a higher level of confidence. This age difference was unaffected by differences in the relative level of acoustic masking.

Kinome signaling through regulated protein-protein interactions in normal and cancer cells.

Science.gov (United States)

Pawson, Tony; Kofler, Michael

2009-04-01

The flow of molecular information through normal and oncogenic signaling pathways frequently depends on protein phosphorylation, mediated by specific kinases, and the selective binding of the resulting phosphorylation sites to interaction domains present on downstream targets. This physical and functional interplay of catalytic and interaction domains can be clearly seen in cytoplasmic tyrosine kinases such as Src, Abl, Fes, and ZAP-70. Although the kinase and SH2 domains of these proteins possess similar intrinsic properties of phosphorylating tyrosine residues or binding phosphotyrosine sites, they also undergo intramolecular interactions when linked together, in a fashion that varies from protein to protein. These cooperative interactions can have diverse effects on substrate recognition and kinase activity, and provide a variety of mechanisms to link the stimulation of catalytic activity to substrate recognition. Taken together, these data have suggested how protein kinases, and the signaling pathways in which they are embedded, can evolve complex properties through the stepwise linkage of domains within single polypeptides or multi-protein assemblies.

School IPM Recognition and Certification

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Schools and school districts can get support and recognition for implementation of school IPM. EPA is developing a program to provide recognition for school districts that are working towards or have achieved a level of success with school IPM programs.

Implicit recognition based on lateralized perceptual fluency.

Science.gov (United States)

Vargas, Iliana M; Voss, Joel L; Paller, Ken A

2012-02-06

In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this "implicit recognition" results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

Fusing Facial Features for Face Recognition

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Jamal Ahmad Dargham

2012-06-01

Full Text Available Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three selection methods. It was found out that fusing the facial features gives better recognition rate than either facial feature used individually regardless of the landmark selection method.

Face Recognition and Tracking in Videos

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Swapnil Vitthal Tathe

2017-07-01

Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

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

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Abdu Gumaei

2018-01-01

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

Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

Science.gov (United States)

Xu, Haiyan; Xie, Yingjuan; Li, Min; Zhang, Zhuo; Zhang, Xuewu

2017-11-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

Science.gov (United States)

Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

2012-01-01

Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

The Recognition Of Fatigue

DEFF Research Database (Denmark)

Elsass, Peter; Jensen, Bodil; Mørup, Rikke

2007-01-01

Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87......Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87...

Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls

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Wolfgang Gaissmeier

2011-02-01

Full Text Available We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naive recognition-based election forecasts computed from convenience samples of citizens' recognition of party names to (i standard polling forecasts computed from representative samples of citizens' voting intentions, and to (ii simple---and typically very accurate---wisdom-of-crowds-forecasts computed from the same convenience samples of citizens' aggregated hunches about election results. Results from four major German elections show that mere recognition of party names forecast the parties' electoral success fairly well. Recognition-based forecasts were most competitive with the other models when forecasting the smaller parties' success and for small sample sizes. However, wisdom-of-crowds-forecasts outperformed recognition-based forecasts in most cases. It seems that wisdom-of-crowds-forecasts are able to draw on the benefits of recognition while at the same time avoiding its downsides, such as lack of discrimination among very famous parties or recognition caused by factors unrelated to electoral success. Yet it seems that a simple extension of the recognition-based forecasts---asking people what proportion of the population would recognize a party instead of whether they themselves recognize it---is also able to eliminate these downsides.

Indoor navigation by image recognition

Science.gov (United States)

Choi, Io Teng; Leong, Chi Chong; Hong, Ka Wo; Pun, Chi-Man

2017-07-01

With the progress of smartphones hardware, it is simple on smartphone using image recognition technique such as face detection. In addition, indoor navigation system development is much slower than outdoor navigation system. Hence, this research proves a usage of image recognition technique for navigation in indoor environment. In this paper, we introduced an indoor navigation application that uses the indoor environment features to locate user's location and a route calculating algorithm to generate an appropriate path for user. The application is implemented on Android smartphone rather than iPhone. Yet, the application design can also be applied on iOS because the design is implemented without using special features only for Android. We found that digital navigation system provides better and clearer location information than paper map. Also, the indoor environment is ideal for Image recognition processing. Hence, the results motivate us to design an indoor navigation system using image recognition.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report.

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Poth, Christian H; Schneider, Werner X

2016-01-01

Human vision is organized in discrete processing episodes (e.g., eye fixations or task-steps). Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM), which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of 10 letters and reported as many as possible after a retention interval (whole report). Next, participants viewed a probe letter and indicated whether it had been one of the 10 letters (probe recognition). In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters) compared with non-encoded letters (non-reported letters). Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2, participants reported only one of 10 letters (partial report) and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report

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Christian H. Poth

2016-09-01

Full Text Available Human vision is organized in discrete processing episodes (e.g. eye fixations or task-steps. Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM, which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of ten letters and reported as many as possible after a retention interval (whole report. Next, participants viewed a probe letter and indicated whether it had been one of the ten letters (probe recognition. In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters compared with non-encoded letters (non-reported letters. Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2 participants reported only one of ten letters (partial report and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

Hirschsprung’s Disease in Patients of Advanced Age

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Ina Vrints

2012-03-01

Full Text Available Hirschsprung’s disease is a congenital motility disorder that is easily overlooked as a cause of chronic refractory constipation in adults. We present a case of Hirschsprung’s disease in a patient 70 years of age with a history of long-standing constipation, chronic use of laxatives, and recurrent episodes of colonic obstruction. Presumptive preoperative diagnosis was chronic ischemic sigmoid stenosis or intermittent sigmoid volvulus before Hirschsprung’s disease was suspected based on intraoperative colonoscopy and surgical findings. The diagnosis was confirmed by the absence of intrinsic ganglion cells on histopathologic examination of the surgical specimen and the absence of the rectoanal inhibitory reflex on postoperative manometry. A conservative surgical approach that limited the resection to the grossly diseased rectum successfully restored normal defecation despite the anastomosis being performed on the distal aganglionic rectum. This approach, which avoids extensive rectal dissection, may be suitable for older or frail patients. Heightened awareness of Hirschsprung’s disease is necessary to ensure its prompt recognition in the elderly.

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

CERN Document Server

Pisharady, Pramod Kumar; Poh, Loh Ai

2014-01-01

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

Mirror self-recognition: a review and critique of attempts to promote and engineer self-recognition in primates.

Science.gov (United States)

Anderson, James R; Gallup, Gordon G

2015-10-01

We review research on reactions to mirrors and self-recognition in nonhuman primates, focusing on methodological issues. Starting with the initial demonstration in chimpanzees in 1970 and subsequent attempts to extend this to other species, self-recognition in great apes is discussed with emphasis on spontaneous manifestations of mirror-guided self-exploration as well as spontaneous use of the mirror to investigate foreign marks on otherwise nonvisible body parts-the mark test. Attempts to show self-recognition in other primates are examined with particular reference to the lack of convincing examples of spontaneous mirror-guided self-exploration, and efforts to engineer positive mark test responses by modifying the test or using conditioning techniques. Despite intensive efforts to demonstrate self-recognition in other primates, we conclude that to date there is no compelling evidence that prosimians, monkeys, or lesser apes-gibbons and siamangs-are capable of mirror self-recognition.

Plan recognition in modelling of users

International Nuclear Information System (INIS)

Hollnagel, Erik

1988-01-01

In order for an Intelligent Decision Support System to interact properly with a user, it must know what the user is doing. Accident Sequence Modelling (ASM) provides a possible frame of reference for monitoring operator activities, but it cannot be used directly: (1) operators may deviate from the scenario described in ASM, (2) the actual situation may develop differently from the scenario, (3) operators are normally involved in several activities at the same time, and (4) modelling of operator activities must focus on the level of individual actions, while the ASM only addresses the global view. The reference provided by the ASM scenario must therefore be supplemented by a more direct modelling of what the operator does. This requires a recognition of the operator's current plans, i.e. his goals and the strategies he employs to reach them. The paper describes a programme to develop an expert system that does this, within the ESPRIT project Graphical Dialogue Environment. (author)

Algorithms for finding Chomsky and Greibach normal forms for a fuzzy context-free grammar using an algebraic approach

Energy Technology Data Exchange (ETDEWEB)

Lee, E.T.

1983-01-01

Algorithms for the construction of the Chomsky and Greibach normal forms for a fuzzy context-free grammar using the algebraic approach are presented and illustrated by examples. The results obtained in this paper may have useful applications in fuzzy languages, pattern recognition, information storage and retrieval, artificial intelligence, database and pictorial information systems. 16 references.

A new pattern associative memory model for image recognition based on Hebb rules and dot product

Science.gov (United States)

Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

2018-04-01

A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

FILTWAM and Voice Emotion Recognition

NARCIS (Netherlands)

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2014-01-01

This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone

Random-Profiles-Based 3D Face Recognition System

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Joongrock Kim

2014-03-01

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

Iris recognition via plenoptic imaging

Science.gov (United States)

Santos-Villalobos, Hector J.; Boehnen, Chris Bensing; Bolme, David S.

2017-11-07

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios.

Face Recognition using Approximate Arithmetic

DEFF Research Database (Denmark)

Marso, Karol

Face recognition is image processing technique which aims to identify human faces and found its use in various different fields for example in security. Throughout the years this field evolved and there are many approaches and many different algorithms which aim to make the face recognition as effective...... processing applications the results do not need to be completely precise and use of the approximate arithmetic can lead to reduction in terms of delay, space and power consumption. In this paper we examine possible use of approximate arithmetic in face recognition using Eigenfaces algorithm....

Pedestrian recognition using automotive radar sensors

OpenAIRE

A. Bartsch; F. Fitzek; R. H. Rasshofer

2012-01-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insight...

Cognitive object recognition system (CORS)

Science.gov (United States)

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

2010-04-01

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

An audiovisual emotion recognition system

Science.gov (United States)

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

2007-12-01

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

Face recognition in the thermal infrared domain

Science.gov (United States)

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

2017-10-01

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

Micro-Recognition - Erving Goffman as Recognition Thinker

DEFF Research Database (Denmark)

Jacobsen, Michael Hviid; Kristiansen, Søren

2009-01-01

and civil inattention guide the conduct of people in many of their face-to-face encounters with each other. This article therefore shows how Goffman may in fact supplement many of the most fashionable and celebrated contemporary recognition theories as advanced by e.g. Nancy Fraser, Charles Taylor or Axel...

Data structures, computer graphics, and pattern recognition

CERN Document Server

Klinger, A; Kunii, T L

1977-01-01

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

Auditory Modeling for Noisy Speech Recognition

National Research Council Canada - National Science Library

2000-01-01

... digital filtering for noise cancellation which interfaces to speech recognition software. It uses auditory features in speech recognition training, and provides applications to multilingual spoken language translation...

Forensic Face Recognition: A Survey

NARCIS (Netherlands)

Ali, Tauseef; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

2010-01-01

Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is

The recognition heuristic: a review of theory and tests.

Science.gov (United States)

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).

The Recognition Heuristic: A Review of Theory and Tests

Directory of Open Access Journals (Sweden)

Thorsten ePachur

2011-07-01

Full Text Available 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.

The Recognition Heuristic: A Review of Theory and Tests

Science.gov (United States)

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

Research on Face Recognition Based on Embedded System

Directory of Open Access Journals (Sweden)

Hong Zhao

2013-01-01

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

L2 Word Recognition: Influence of L1 Orthography on Multi-Syllabic Word Recognition

Science.gov (United States)

Hamada, Megumi

2017-01-01

L2 reading research suggests that L1 orthographic experience influences L2 word recognition. Nevertheless, the findings on multi-syllabic words in English are still limited despite the fact that a vast majority of words are multi-syllabic. The study investigated whether L1 orthography influences the recognition of multi-syllabic words, focusing on…

Recognition of Prior Learning, Self-Realisation and Identity within Axel Honneth's Theory of Recognition

Science.gov (United States)

Sandberg, Fredrik; Kubiak, Chris

2013-01-01

This paper argues for the significance of Axel Honneth's theory of recognition for understanding recognition of prior learning (RPL). Case studies of the experiences of RPL by paraprofessional workers in health and social care in the UK and Sweden are used to explicate this significance. The results maintain that there are varying conditions of…

Hidden neural networks: application to speech recognition

DEFF Research Database (Denmark)

Riis, Søren Kamaric

1998-01-01

We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...

Pattern recognition and string matching

CERN Document Server

Cheng, Xiuzhen

2002-01-01

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

Mobile Visual Recognition on Smartphones

Directory of Open Access Journals (Sweden)

Zhenwen Gui

2013-01-01

Full Text Available This paper addresses the recognition of large-scale outdoor scenes on smartphones by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows. Firstly, we propose an ORD (overlap region divide method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree-based approach is improved by introducing GAGCC (gravity-aligned geometric consistency constraint. Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent recognition performance, while maintaining the average recognition time about 1 s.

Recognition Using Classification and Segmentation Scoring

National Research Council Canada - National Science Library

Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

1992-01-01

.... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

[Measuring impairment of facial affects recognition in schizophrenia. Preliminary study of the facial emotions recognition task (TREF)].

Science.gov (United States)

Gaudelus, B; Virgile, J; Peyroux, E; Leleu, A; Baudouin, J-Y; Franck, N

2015-06-01

The impairment of social cognition, including facial affects recognition, is a well-established trait in schizophrenia, and specific cognitive remediation programs focusing on facial affects recognition have been developed by different teams worldwide. However, even though social cognitive impairments have been confirmed, previous studies have also shown heterogeneity of the results between different subjects. Therefore, assessment of personal abilities should be measured individually before proposing such programs. Most research teams apply tasks based on facial affects recognition by Ekman et al. or Gur et al. However, these tasks are not easily applicable in a clinical exercise. Here, we present the Facial Emotions Recognition Test (TREF), which is designed to identify facial affects recognition impairments in a clinical practice. The test is composed of 54 photos and evaluates abilities in the recognition of six universal emotions (joy, anger, sadness, fear, disgust and contempt). Each of these emotions is represented with colored photos of 4 different models (two men and two women) at nine intensity levels from 20 to 100%. Each photo is presented during 10 seconds; no time limit for responding is applied. The present study compared the scores of the TREF test in a sample of healthy controls (64 subjects) and people with stabilized schizophrenia (45 subjects) according to the DSM IV-TR criteria. We analysed global scores for all emotions, as well as sub scores for each emotion between these two groups, taking into account gender differences. Our results were coherent with previous findings. Applying TREF, we confirmed an impairment in facial affects recognition in schizophrenia by showing significant differences between the two groups in their global results (76.45% for healthy controls versus 61.28% for people with schizophrenia), as well as in sub scores for each emotion except for joy. Scores for women were significantly higher than for men in the population

Object feature extraction and recognition model

International Nuclear Information System (INIS)

Wan Min; Xiang Rujian; Wan Yongxing

2001-01-01

The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

A Bayesian classifier for symbol recognition

OpenAIRE

Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

2007-01-01

URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Directory of Open Access Journals (Sweden)

Muhammad Hameed Siddiqi

2013-12-01

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

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Science.gov (United States)

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

2013-01-01

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

Improved RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

2016-01-01

years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

Unequal recognition, misrecognition and injustice

DEFF Research Database (Denmark)

Lægaard, Sune

2012-01-01

by the state of religious minorities. It argues that state–religion relations can be analysed as relations of recognition, which are not only unequal but also multi-dimensional, and that it is difficult to answer the question whether multi-dimensional recognitive inequalities are unjust or wrong if one...

Degraded character recognition based on gradient pattern

Science.gov (United States)

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

2010-02-01

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

[Face recognition in patients with autism spectrum disorders].

Science.gov (United States)

Kita, Yosuke; Inagaki, Masumi

2012-07-01

The present study aimed to review previous research conducted on face recognition in patients with autism spectrum disorders (ASD). Face recognition is a key question in the ASD research field because it can provide clues for elucidating the neural substrates responsible for the social impairment of these patients. Historically, behavioral studies have reported low performance and/or unique strategies of face recognition among ASD patients. However, the performance and strategy of ASD patients is comparable to those of the control group, depending on the experimental situation or developmental stage, suggesting that face recognition of ASD patients is not entirely impaired. Recent brain function studies, including event-related potential and functional magnetic resonance imaging studies, have investigated the cognitive process of face recognition in ASD patients, and revealed impaired function in the brain's neural network comprising the fusiform gyrus and amygdala. This impaired function is potentially involved in the diminished preference for faces, and in the atypical development of face recognition, eliciting symptoms of unstable behavioral characteristics in these patients. Additionally, face recognition in ASD patients is examined from a different perspective, namely self-face recognition, and facial emotion recognition. While the former topic is intimately linked to basic social abilities such as self-other discrimination, the latter is closely associated with mentalizing. Further research on face recognition in ASD patients should investigate the connection between behavioral and neurological specifics in these patients, by considering developmental changes and the spectrum clinical condition of ASD.

Progesterone impairs social recognition in male rats.

Science.gov (United States)

Bychowski, Meaghan E; Auger, Catherine J

2012-04-01

The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppress AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependent behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment leads to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. Copyright © 2012 Elsevier Inc. All rights reserved.

H-2 restriction: Independent recognition of H-2 and foreign antigen by a single receptor

Science.gov (United States)

Siliciano, Robert F.; Zacharchuk, Charles M.; Shin, Hyun S.

1980-01-01

We describe two situations in which the recognition of hapten can compensate for the lack of recognition of appropriate H-2 gene products in hapten-specific, H-2 restricted, T lymphocyte-mediated cytolysis. First, we show that although recognition of appropriate H-2 gene products is essential for the lysis of target cells bearing a low hapten density, significant hapten-specific lysis of H-2 inappropriate target cells is observed at high levels of target cell derivatization. Secondly, we show that hapten-conjugated anti-H-2 antibody inhibits cytolysis poorly even though its binding to target cell H-2 antigens is equivalent to that of underivatized antibody. These results suggest that hapten and H-2 are recognized independently and are therefore inconsistent with the altered-self model. Although our data do not exclude the dual-recognition model, we prefer to interpret them within the framework of a single-receptor model in which hapten and H-2 are recognized independently by receptors of identical idiotype on the T cell. We postulate that the affinity of these receptors for the relevant H-2 gene product is low enough so that the T cell is not activated by encounters with normal-self cells expressing that H-2 gene product. However, when self cells express in addition a foreign antigen that can also be recognized by the same receptor, then the force of T cell-target cell interaction may be increased sufficiently to activate T cell effector function. PMID:6966404

RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris

2014-01-01

Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But......, such analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...... algorithm has been developed to use these images. The experimental results show that face recognition using such three modalities provides better results compared to face recognition in any of such modalities in most of the cases....

Intact suppression of increased false recognition in schizophrenia.

Science.gov (United States)

Weiss, Anthony P; Dodson, Chad S; Goff, Donald C; Schacter, Daniel L; Heckers, Stephan

2002-09-01

Recognition memory is impaired in patients with schizophrenia, as they rely largely on item familiarity, rather than conscious recollection, to make mnemonic decisions. False recognition of novel items (foils) is increased in schizophrenia and may relate to this deficit in conscious recollection. By studying pictures of the target word during encoding, healthy adults can suppress false recognition. This study examined the effect of pictorial encoding on subsequent recognition of repeated foils in patients with schizophrenia. The study included 40 patients with schizophrenia and 32 healthy comparison subjects. After incidental encoding of 60 words or pictures, subjects were tested for recognition of target items intermixed with 60 new foils. These new foils were subsequently repeated following either a two- or 24-word delay. Subjects were instructed to label these repeated foils as new and not to mistake them for old target words. Schizophrenic patients showed greater overall false recognition of repeated foils. The rate of false recognition of repeated foils was lower after picture encoding than after word encoding. Despite higher levels of false recognition of repeated new items, patients and comparison subjects demonstrated a similar degree of false recognition suppression after picture, as compared to word, encoding. Patients with schizophrenia displayed greater false recognition of repeated foils than comparison subjects, suggesting both a decrement of item- (or source-) specific recollection and a consequent reliance on familiarity in schizophrenia. Despite these deficits, presenting pictorial information at encoding allowed schizophrenic subjects to suppress false recognition to a similar degree as the comparison group, implying the intact use of a high-level cognitive strategy in this population.

Prevalence of face recognition deficits in middle childhood.

Science.gov (United States)

Bennetts, Rachel J; Murray, Ebony; Boyce, Tian; Bate, Sarah

2017-02-01

Approximately 2-2.5% of the adult population is believed to show severe difficulties with face recognition, in the absence of any neurological injury-a condition known as developmental prosopagnosia (DP). However, to date no research has attempted to estimate the prevalence of face recognition deficits in children, possibly because there are very few child-friendly, well-validated tests of face recognition. In the current study, we examined face and object recognition in a group of primary school children (aged 5-11 years), to establish whether our tests were suitable for children and to provide an estimate of face recognition difficulties in children. In Experiment 1 (n = 184), children completed a pre-existing test of child face memory, the Cambridge Face Memory Test-Kids (CFMT-K), and a bicycle test with the same format. In Experiment 2 (n = 413), children completed three-alternative forced-choice matching tasks with faces and bicycles. All tests showed good psychometric properties. The face and bicycle tests were well matched for difficulty and showed a similar developmental trajectory. Neither the memory nor the matching tests were suitable to detect impairments in the youngest groups of children, but both tests appear suitable to screen for face recognition problems in middle childhood. In the current sample, 1.2-5.2% of children showed difficulties with face recognition; 1.2-4% showed face-specific difficulties-that is, poor face recognition with typical object recognition abilities. This is somewhat higher than previous adult estimates: It is possible that face matching tests overestimate the prevalence of face recognition difficulties in children; alternatively, some children may "outgrow" face recognition difficulties.

Self-Recognition in Autistic Children.

Science.gov (United States)

Dawson, Geraldine; McKissick, Fawn Celeste

1984-01-01

Fifteen autistic children (four to six years old) were assessed for visual self-recognition ability, as well as for object permanence and gestural imitation. It was found that 13 of 15 autistic children showed evidence of self-recognition. Consistent relationships were suggested between self-cognition and object permanence but not between…

Effects of hearing loss and cognitive load on speech recognition with competing talkers

Directory of Open Access Journals (Sweden)

Hartmut eMeister

2016-03-01

Full Text Available Everyday communication frequently comprises situations with more than one talker speaking at a time. These situations are challenging since they pose high attentional and memory demands placing cognitive load on the listener. Hearing impairment additionally exacerbates communication problems under these circumstances. We examined the effects of hearing loss and attention tasks on speech recognition with competing talkers in older adults with and without hearing impairment. We hypothesized that hearing loss would affect word identification, talker separation and word recall and that the difficulties experienced by the hearing impaired listeners would be especially pronounced in a task with high attentional and memory demands. Two listener groups closely matched regarding their age and neuropsychological profile but differing in hearing acuity were examined regarding their speech recognition with competing talkers in two different tasks. One task required repeating back words from one target talker (1TT while ignoring the competing talker whereas the other required repeating back words from both talkers (2TT. The competing talkers differed with respect to their voice characteristics. Moreover, sentences either with low or high context were used in order to consider linguistic properties. Compared to their normal hearing peers, listeners with hearing loss revealed limited speech recognition in both tasks. Their difficulties were especially pronounced in the more demanding 2TT task. In order to shed light on the underlying mechanisms, different error sources, namely having misunderstood, confused, or omitted words were investigated. Misunderstanding and omitting words were more frequently observed in the hearing impaired than in the normal hearing listeners. In line with common speech perception models it is suggested that these effects are related to impaired object formation and taxed working memory capacity (WMC. In a post hoc analysis the

Textual emotion recognition for enhancing enterprise computing

Science.gov (United States)

Quan, Changqin; Ren, Fuji

2016-05-01

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

Efficient Interaction Recognition through Positive Action Representation

Directory of Open Access Journals (Sweden)

Tao Hu

2013-01-01

Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

Face recognition based on improved BP neural network

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Yue Gaili

2017-01-01

Full Text Available In order to improve the recognition rate of face recognition, face recognition algorithm based on histogram equalization, PCA and BP neural network is proposed. First, the face image is preprocessed by histogram equalization. Then, the classical PCA algorithm is used to extract the features of the histogram equalization image, and extract the principal component of the image. And then train the BP neural network using the trained training samples. This improved BP neural network weight adjustment method is used to train the network because the conventional BP algorithm has the disadvantages of slow convergence, easy to fall into local minima and training process. Finally, the BP neural network with the test sample input is trained to classify and identify the face images, and the recognition rate is obtained. Through the use of ORL database face image simulation experiment, the analysis results show that the improved BP neural network face recognition method can effectively improve the recognition rate of face recognition.

Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition

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Yi, Wei-song; Cui, Dian-sheng; Li, Zhi; Wu, Lan-lan; Shen, Ai-guo; Hu, Ji-ming

2013-01-01

The manuscript has investigated the application of near-infrared (NIR) spectroscopy for differentiation gastric cancer. The 90 spectra from cancerous and normal tissues were collected from a total of 30 surgical specimens using Fourier transform near-infrared spectroscopy (FT-NIR) equipped with a fiber-optic probe. Major spectral differences were observed in the CH-stretching second overtone (9000-7000 cm-1), CH-stretching first overtone (6000-5200 cm-1), and CH-stretching combination (4500-4000 cm-1) regions. By use of unsupervised pattern recognition, such as principal component analysis (PCA) and cluster analysis (CA), all spectra were classified into cancerous and normal tissue groups with accuracy up to 81.1%. The sensitivity and specificity was 100% and 68.2%, respectively. These present results indicate that CH-stretching first, combination band and second overtone regions can serve as diagnostic markers for gastric cancer.

Emotion recognition in Chinese people with schizophrenia.

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Chan, Chetwyn C H; Wong, Raymond; Wang, Kai; Lee, Tatia M C

2008-01-15

This study examined whether people with paranoid or nonparanoid schizophrenia would show emotion-recognition deficits, both facial and prosodic. Furthermore, this study examined the neuropsychological predictors of emotion-recognition ability in people with schizophrenia. Participants comprised 86 people, of whom: 43 were people diagnosed with schizophrenia and 43 were controls. The 43 clinical participants were placed in either the paranoid group (n=19) or the nonparanoid group (n=24). Each participant was administered the Facial Emotion Recognition task and the Prosodic Recognition task, together with other neuropsychological measures of attention and visual perception. People suffering from nonparanoid schizophrenia were found to have deficits in both facial and prosodic emotion recognition, after correction for the differences in the intelligence and depression scores between the two groups. Furthermore, spatial perception was observed to be the best predictor of facial emotion identification in individuals with nonparanoid schizophrenia, whereas attentional processing control predicted both prosodic emotion identification and discrimination in nonparanoid schizophrenia patients. Our findings suggest that patients with schizophrenia in remission may still suffer from impairment of certain aspects of emotion recognition.

Implicit Recognition Based on Lateralized Perceptual Fluency

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Iliana M. Vargas

2012-02-01

Full Text Available In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

Dynamic Programming Algorithms in Speech Recognition

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Titus Felix FURTUNA

2008-01-01

Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.

Cortical Networks for Visual Self-Recognition

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Sugiura, Motoaki

This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed.

Cortical networks for visual self-recognition

International Nuclear Information System (INIS)

Sugiura, Motoaki

2007-01-01

This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed. (author)

The role of the hippocampus in recognition memory.

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Bird, Chris M

2017-08-01

Many theories of declarative memory propose that it is supported by partially separable processes underpinned by different brain structures. The hippocampus plays a critical role in binding together item and contextual information together and processing the relationships between individual items. By contrast, the processing of individual items and their later recognition can be supported by extrahippocampal regions of the medial temporal lobes (MTL), particularly when recognition is based on feelings of familiarity without the retrieval of any associated information. These theories are domain-general in that "items" might be words, faces, objects, scenes, etc. However, there is mixed evidence that item recognition does not require the hippocampus, or that familiarity-based recognition can be supported by extrahippocampal regions. By contrast, there is compelling evidence that in humans, hippocampal damage does not affect recognition memory for unfamiliar faces, whilst recognition memory for several other stimulus classes is impaired. I propose that regions outside of the hippocampus can support recognition of unfamiliar faces because they are perceived as discrete items and have no prior conceptual associations. Conversely, extrahippocampal processes are inadequate for recognition of items which (a) have been previously experienced, (b) are conceptually meaningful, or (c) are perceived as being comprised of individual elements. This account reconciles findings from primate and human studies of recognition memory. Furthermore, it suggests that while the hippocampus is critical for binding and relational processing, these processes are required for item recognition memory in most situations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Face recognition : implementation of face recognition on AMIGO

NARCIS (Netherlands)

Geelen, M.J.A.J.; Molengraft, van de M.J.G.; Elfring, J.

2011-01-01

In this (traineeship)report two possible methods of face recognition were presented. The first method describes how to detect and recognize faces by using the SURF algorithm. This algorithm finally was not used for recognizing faces, with the reason that the Eigenface algorithm was an already tested